Reviewerly/exHarmony huggingface dataset:
Artificial Intelligence-Based Approaches for Product Recommendation in E-Commerce

Today's e-commerce is completely dependent on artificial intelligence. Whatever technology was used in the ancient days, there was a huge gap between a customer and a seller. From a seller's point of view, he wanted to sell the maximum product and a customer had to purchase the product whose price was lowest in the market but best in quality. In this situation, we need a system that can automatically recommend a suitable product to the customer so that we can buy his goods easily and at a low price. For this, artificial intelligence is the best method. Artificial intelligence recommendation system is a combination of machine learning algorithms that are used by developers to help users predict their choices and get related suggestions.Through this chapter, the authors show the different processes and uses of artificial intelligence that help the user for an accurate recommendation of a product such as search queries, past purchases, items placed in the shopping cart, viewing history, and the location of the customer or buyer.
COMPUTER VISION FOR INVENTORY MANAGEMENT

COMPUTER VISION FOR INVENTORY MANAGEMENT Aminov Sultan Bulatovich student, Kazakh-British Technical University, Kazakhstan, Almaty &nbsp; КОМПЬЮТЕРНОЕ ЗРЕНИЕ ДЛЯ УПРАВЛЕНИЯ ЗАПАСАМИ Амино
Performance of Parallel K-Means Based on Theatre

K-Means is a well-known clustering algorithm whose goal is partitioning a number of data points into groups (clusters), so as to minimize dissimilarities of data, measured by some metric, within the same group. Due to its simplicity, K-Means is often used in machine learning unsupervised clustering applications. However, the execution performance of K-Means can easily become a bottleneck when dealing with very large datasets, paired with a great number of clusters, as those encountered in many big data ecosystems. Therefore, many efforts are reported in the literature devoted to a parallelization of K-Means, both on shared-nothing and shared-memory architectures. This paper proposes a novel approach to parallel K-Means on multi/many-core machines, which is based on the Theatre actor system developed in Java. The realization is based on message passing for synchronization among actors (workers) but also offers the possibility of sharing data, in a controlled and safe way, among the actors of the same computing node (theatre). The approach proves effective in delivering a high-performance execution. The paper first provides some background information about the basic K-Means algorithm and the Theatre architecture, then an actor-based parallel version of K-Means is described and experimented with.
Selective Storage: Store and Deliver Only What Matters

Video streaming services must satisfy the growing consumer request for having the best video quality (VQ), anywhere, anytime. As such, and to optimize the end-user VQ for various network and end-device capabilities, over-the-top (OTT) video delivery infrastructure massively relies on adaptive bitrate (ABR) streaming technology. In the common scenario, it consists of processing and storing various compressed representations of the content to stream, that is, different couples of resolution and bitrate, also known as the bitrate ladder. As both processing and storage resources are expensive, each content provider must optimize its operating and infrastructure costs. This article discusses the existing limitations in the ABR streaming landscape and introduces an innovative selective storage algorithm that tackles one of the main challenges in ABR streaming: the storage cost. This algorithm reduces up to 30% of the amount of required storage for the same VQ and remains compliant with existing optimizations in the OTT ecosystem.
Based on Lightweight Network and Multiple Supervised Hash for Image Retrieval

At present, most of the depth hash methods use complex convolution neural networks to extract the features of the image, many parameters and large models, and insufficient utilization of feature correlation. A method called LNMSH (lightweight network and multi-supervised hash for Image Retrieval) is proposed based on lightweight network and multiple supervised hash. LNMSH is trained as image inputs to learn hash codes through a designed lightweight convolution neural network and a multiple supervised hash function. A lightweight convolution neural network has few parameters and a small model to efficiently extract the image feature information. The multiple supervised hash function can more efficient utilization of the semantic information and the feature correlation between images, improving the conversion of the feature information extracted by the network to a more distinguished hash code and improving the efficiency of image retrieval. Therefore, a total target loss function is designed. Many comparative experiments have been performed on two widely used datasets, ImageNet and Nus-Wide. Verified by the experimental results, the performance of LNMSH is better than that of other deep hash algorithms.
Property Assertion Constraints for ontologies and knowledge graphs

Purpose The curation of ontologies and knowledge graphs (KGs) is an essential task for industrial knowledge-based applications, as they rely on the contained knowledge to be correct and error-free. Often, a significant amount of a KG is curated by humans. Established validation methods, such as Shapes Constraint Language, Shape Expressions or Web Ontology Language, can detect wrong statements only after their materialization, which can be too late. Instead, an approach that avoids errors and adequately supports users is required. Design/methodology/approach For solving that problem, Property Assertion Constraints (PACs) have been developed. PACs extend the range definition of a property with additional logic expressed with SPARQL. For the context of a given instance and property, a tailored PAC query is dynamically built and triggered on the KG. It can determine all values that will result in valid property value assertions. Findings PACs can avoid the expansion of KGs with invalid property value assertions effectively, as their contained expertise narrows down the valid options a user can choose from. This simplifies the knowledge curation and, most notably, relieves users or machines from knowing and applying this expertise, but instead enables a computer to take care of it. Originality/value PACs are fundamentally different from existing approaches. Instead of detecting erroneous materialized facts, they can determine all semantically correct assertions before materializing them. This avoids invalid property value assertions and provides users an informed, purposeful assistance. To the author's knowledge, PACs are the only such approach.
Analysis of the Relationship between Learning Attitude, Self-directed Learning Ability, Learning Flow, Problem Solving Ability of Learning Community Participants: Focusing on the Extracurricular

This study explored the relationship between learning attitude, self-directed learning ability, learning flow, and problem-solving ability of students who participated in the learning community program. For this purpose, a survey was conducted with students who participated in the learning community. The study results are as follows. First, learning attitude and self-directed learning ability were found to have a significant effect on learning flow. Second, learning attitude and self-directed learning ability were found to have a significant effect on problem solving. Third, as a result of analyzing the mediating effect of learning flow in the effect of learning attitude and self-directed learning ability on problem-solving ability, it was found to have a partial mediating effect. It can be seen that in collaborative learning situations, students maintain a positive learning attitude to achieve their learning goals and have a positive effect on learning outcomes through learning flow experiences.
Modernization of domestic education as a historically determined process

This article is devoted to the problem of studying the methodology and strategies of modernization of education in the Russian socio-cultural tradition. The modernization process currently underway in the national education system of Russia and domestic pedagogical science actualizes the need to analyze educational transformations over the past century. This circumstance is of extremely important fundamental and scientific and practical importance for the development of strategic parameters for the comprehensive modernization of the modern national education system. The methodological significance of the study lies in the urgent need for a projective-analytical reconstruction of the multidimensional process of development of promising strategies for modernization and reform of education. The chronological and analytical correlation of the evolution of Russian studies of educational systems at this historical stage within the dynamics of socio-cultural development is essential here. It also seems timely to study the pedagogical dimensions of the development of the national education system based on the study of the contribution of leading Russian scientists to the understanding of modernization processes. This will allow to harmonize and integrate various research models of the national pedagogical tradition, which will contribute to the development of the theory and practice of the functioning of educational systems. The applied significance of the research is connected with the urgent tasks of rethinking the existing experience of the strategic development of national education systems. A certain research interest is the process of scientific, methodological and analytical support for the formation of mechanisms for the introduction of strategic models of modernization and concepts of reforming modern domestic education. This research will contribute to the accumulation of knowledge about the current state and development of the complex of sciences of education and their role in the process of modernization and reform of Russian education. It will also make it possible, in the conditions of increasing globalization, to scientifically design promising and futurologically meaningful models of strategic development and management practices in the national education system.
Augmented Reality Integrated Smart Math Solver

The task of smart math solver aims to automatically solve a math problem by reading the text description of the problem and generating the answer. This task requires the machine to have the ability of natural language understanding and reasoning. The model takes math problem questions as input and generates a sequence of equations and the last answer as output. The advantage of the sequence-to-sequence model requires no feature engineering and can generate equations that do not exist in training data. The working of the Veda app is that when we scan a mathematical question or equation through our camera, it uses optical character recognition (OCR) technology to recognise the question and calculates the answers within seconds using computer algorithmic systems. Using AR, we will display the solution in real time of that mathematical problem step-by-step along with the final answer. Veda can solve math problems that range from basic arithmetic to calculus.
History of Science in a Harmonic Style [Review: Smagina G.I. “Learning Science Historically…”: Russian History of Science in the Early Decades of the 20th Century. St. Petersburg, Rostok, 2020. (In Russian)]

This review discusses the structure and key points of G.I. Smagina’s book devoted to the institutional and content development of the Russian history of science as a discipline during the early decades of the 20th century. The major focus falls on the process of institutionalization of the history of science in Russia that took more than 15 years – starting from the establishment of the Commission for the Publication of the Collection of Articles “Russian Science” in December 1916 until the foundation of the Institute of Science and Technology of the USSR Academy of Sciences in February 1932. The monograph consists of five chapters and appendices, which make up almost a third of the entire work. The genre of the reviewed book is defined as a documentary monograph. The institutional and anthropological aspects of the study are emphasized. The researchers who were involved in the shaping of a new discipline are identified. The author believes that over 400 people participated, in one way or another, in the studies within the scope of the history of science. Brief intellectual biographies of both the leaders of the two commissions (A.S. Lappo-Danilevsky, V.I. Vernadsky, N.I. Bukharin) and ordinary participants/creators of the historical and scientific process are presented. Plots related to the practices of popularization of science within the framework of academic structures are distinguished as innovative issues. Based on G.I. Smagina’s reasoning, two levels of popularization are singled out: within the corporation and outside it (in the space of mass culture). A hypothesis about the change in the conceptual settings during the development of the history of science as a discipline in the first third of the 20th century – from a humanitarian interpretation of the history of science to a socially oriented concept – with the subsequent institutionalization of the process is introduced.
THE URGENCY OF GO VIRTUAL AS DIGITAL LITERACY IN LEARNING ENGLISH DURING THE COVID-19 PANDEMIC: THE IMPACT OF THE CONSUMER MEGA SHIFTING

Digital literacy is increasingly being encouraged to support education, especially during the Covid 19 pandemic due to Consumer Mega Shifting, especially Go Virtual. This study aims to analyze and evaluate the implementation of Go Virtual as Digital Literacy for English Learning during the Covid-19 Pandemic at two vocational institutes in Bali, namely the Bali Tourism Polytechnic and the International Business and Tourism Institute. The method used was descriptive qualitative where data collection techniques were in the form of questionnaires (76 students) and interviews (4 English lecturers from both universities). Digital literacy creativity in learning English aims to reduce student boredom in receiving online learning and make English learning more interesting and easy to understand, as well as improve thinking skills andgenerate interest, creativity, and independence of students. English Lecturers from these two vocational institutes can also implement digital literacy competencies in seven digital literacy competency areas proposed by UNESCO. However, there are indicators of digital literacy competence that cannot be applied optimally, namely in the area of security competence, programming indicators and copyrights and licenses caused of the limited knowledge and expertise of English lecturers in the field of digital devices.
LEARNING MEDIA DEVELOPMENT USING COMIC ON THEME 3 SUB-THEME 3 GRADE II OF PRIMARY SCHOOL STUDENTS

This research was started when doing observation and interview with teachers that the use of learning media was still so lack when teachers taught in class so that students were found that they have less interested in learning participating. One of the media that can attract attention and provide entertainment is comics, this is because comics display stories that are closely related to images so that they attract students to read. The purpose of this research is to see the feasibility of the product in the form of comic media with grade II students. The research type is research and development (R&amp;D). This research applied some steps that must be carried out in accordance with the instructions systematically are cinsist of (1) Collection (needs analysis) (2) Comic product design (3) Material and design validation (4) Product revision (5) Feedback /Teacher's Responses (6) Field trials (small groups and large groups (7) Product data analyzer. The instrument used is questionnaire which are validated by a team of material experts and a team of design experts and the product response will be carried out by 2 teachers and 30 students of the 2nd grade. The results on the validation and the response describe the feasibility of the comic product developed. The results obtained (1) Design expert validation got 4.12 scores included as "Eligible" category (2) Material expert validation got 4.17 score included as "Eligible" category (3) The second grade homeroom teacher's response got 4.87 score included as "very appropriate" category (4) The third grade elementary school student's response got 4.46 score included as “Very decent” category. Based on the results of the validation and response results, it was concluded that the material that the researchers developed was the comics media for grade II students at SDS 012 Maitreyawira Karimun. The average score is 4.40 included as "Very feasible" category.
When AI needs to work smarter, not harder [opinion - first person]

Using artificial intelligence to help make the best decisions doesn&apos;t always depend on having huge amounts of data. Taking a &apos;problem first&apos; approach to the task can be just as effective. The article explains an approach involving the development of a deep understanding of the problem from the outset and encoding that information into the AI. In other words, having less but more relevant and better data is the AI equivalent of the old adage &apos;work smart, not harder&apos;. This is also where collaboration between humans and AI is crucial. Keeping a human - or domain expert - involved in an AI&apos;s decision-making process provides a lot more control and minimises the bias being introduced into the system.
ANALYSIS USE OF ELEMENTS, STRUCTURE, AND TEXT LANGUAGE RULES IN 2013 CURRICULUM

This research is motivated by the competencies that students must have in Indonesian language subjects, especially class VIII, namely understanding news texts, exposition texts, and poetry texts. In the 2013 curriculum, the material aims to enable students to convey their ideas and ideas logically and systematically in written form. This type of research is qualitative using descriptive method. The data in this study are excerpts of sentences or words contained in the students' texts, while the data sources used are the writings of these texts, students of class VIII SMP Pertiwi 2 Padang. The research instrument is the researcher himself and the data inventory format. The results of this study are summarized as follows.First, specifically for news texts, which use elements of only thirty-one student texts, and only twenty-five student texts use the language rules of news texts. Second, for the exposition text, which uses the structure of the exposition text, there are only twenty-six student texts, and fifteen student texts that use linguistic rules. Third, for poetry texts, there are only twenty-two student texts that use language rules.
Notebooks Now! Elevating Computational Notebooks

AGU is launching a community-driven effort, funded by the Alfred P. Sloan Foundation, to support computational notebooks as primary research objects in scholarly publications.
The Acceptance of E-Learning during Covid-19 Pandemic amongst Dental Students of Islamabad

Background: The worldwide COVID 19 pandemic coerced all organizations including educational facilities to embrace online teaching methodologies. The present study was done to assess the acceptance of e-learning during COVID 19 among dental students in the metropolitan city of Islamabad using the Technology Acceptance Model (TAM)&#x0D; Methods: This was a cross sectional study involving all dental colleges of Islamabad, was conducted between August 2020 – October 2020. The complete enumeration technique was employed for sampling. A structured self-reported questionnaire of the Technology acceptance model (TAM) was used for data collection. It consisted of four constructs, perceived usefulness (PU), perceived ease of use (PEOU), attitude towards use (ATT) and intention to use (INT). The questionnaire was shared online with 600 dental undergraduate students in Islamabad. To analyze the data SPSS (version 22) was used.&#x0D; Results: The total number of complete responses received were 274 (RR 45%).The overall mean scores for PEOU, INT, PU and ATT were 3.38, 3.21, 3.1 and 2.92 respectively. Lower mean value showed that the respondents disagreed/strongly disagreed, whereas higher mean value showed that they were inclined to agree/strongly agree with the idea of e-learning. Based on TAM model, six hypotheses were formulated and tested for significance based on the regression statistics. Larger beta and t values and P value of 0.05 using regression analysis showed existence of significant relationship between all the factors.&#x0D; Conclusion: The present study explored the acceptance of e-learning by dental students and concluded that in order to motivate students to use technology for educational purposes it is necessary for them to perceive technology to be useful and easy to use. This in turn would help them develop a positive attitude towards using it and consequently motivate greater participation.&#x0D;
How to Generate and Import Functional Test Cases into a Project Management Software System using Natural Language Processing

The main purpose of software testing is to identify what the software does and whether it matches its functional expectations. Applying a test plana allows one to prevent problems in early stages, identifying and addressing solutions before a project goes into production. Test cases play an important role during the software testing phase. A test case is a document with comprehensive details and sequences of actions to guide the software tester through the steps that need to be taken and the outputs that are expected. _x005F_x000D_ _x005F_x000D_ The proposed system generates test cases based on scraped data that are used to interact with Natural Language Processing (NLP) approaches to generate functional test cases. A project management software (e.g., JIRA) is integrated with the JIRA python library to manage the test cases by the software tester.
THE EFFECT OF BLENDED LEARNING MODEL ON STUDENTS’ ACHIEVEMENT IN READING CLASS

Reading is a skill that is not easy for the student to understand in learning English. However, English teacher at that school still used the monotonous learning model in teaching reading. Hence, this study aimed to find empirical evidence whether teaching using a blended learning model was effective or not on students' reading comprehension of narrative text. This study used a quantitative method and quasiexperiment design. The experimental class and control class were the sample of this study. X DPIB 1 as experimental class consisted of 30 students and X DPIB 2 as controlled class consisted. To take the sample, the researchers used purposive sampling. Students in the experimental class were taught using the blended learning model. In contrast, the controlled class did not use the blended learning model. Theinstrument was a test, and it was divided into pre-test and post-test. The data among pre-test, post-test and gained score were analyzed by using t-test. The pre-test result showed that there were no significant differences between both classes. Then post-test showed that p=0,101 and was greater than α=0.05, and it meant no significant differences in both classes. Furthermore, gained score result showed that p= 0,466 and it also greater than α=0.05. Moreover, based on manual calculation the t0 (tvalue) = 0,762 and tt (ttable) = 1,672, it meant that t0 (tvalue) &lt; tt (ttable) (0,762 &lt; 1,672). Based on the calculation of the t-test, it was proved that the null hypothesis (H0) was accepted. It means that there was a significant effect onstudents reading comprehension who were taught with the blended learning model.