Reviewerly/exHarmony huggingface dataset:
C++ Standard Library and Friends

C++ language is accompanied by a library called the C++ Standard Library. It is a collection of containers and useful functions that we access by including the proper header file. The containers and functions inside the C++ standard library are defined in the std namespace. Remember the std::string type mentioned earlier? It is also a part of the standard library. The standard library is implemented through class templates. Long story short: prefer using the standard-library to user-provided libraries for everyday tasks.
Instruments

Chapter 2 contains practical information about models and makers of (copies of) renaissance instruments today. It considers important variables affecting one’s choice of buying a new instrument, such as the most suitable types of wood used and the range of possible pitches. It also provides advice on how to clean and care for the instrument.
A Study on the Utilization of Divergent·Convergent Thinking Techniques to Improve Self-Directed Learning Education - Focused on Visual Design Major -

The role of design and designer is changing as we enter the era of the Fourth Industrial Revolution, which is based on creativity and convergence. New design types of names have been created and the design process, which could be solved by itself, is now essential to cooperate and collaborate with other majors. Therefore, the competence of today's designers wants talent with creative thinking and application skills that reflect the various values demanded by the knowledge society. In this study, based on the integrated thinking of Divergent Thinking·Convergent, which is necessary for the design problem-solving process for self-directed learning, we propose an educational methodology for self-directed learning and seek ways to utilize it. The type of integration of the Divergent·Convergent Thinking Techniques is an educational model that focuses on bringing one's ideas freely through two thoughts within a given format, through topics that can be observed in everyday life. Based on the existing prior research, the research method for the verification of the education model was integrated and applied CPSS types based on the design thinking, and items of Learner Satisfaction, Self-Efficiency, Idea Expression, and Presentation Skill were extracted to verify the effectiveness of the self-directed learning. The extracted items were conducted as experimental studies to verify the relationship of influence between the CPSS. In the future, we hope to cultivate future talents who can naturally solve problems together in collaboration with other major fields, and that the DPS education model will be applied to educators and students in the self-directed learning effect.
ONLINE CONSUMER RETENTION IN SAUDI ARABIADURING COVID 19: THE MODERATINGROLE OF ONLINE TRUST

Online customer retention has become essential for the success of businesses during COVID 19. A shift incustomers toward the online has increased the important of this variable. Nevertheless, few studies examined thepredictors of online customer retention. Based on social exchange theory service quality model, and technologyacceptance model, this study proposes that attitude, customer satisfaction, ease of use and responsiveness willhave a direct effect on online customer retention among customers of retailers in Saudi Arabia. The study alsoproposes that online trust will moderate the relationship. Data was collected from Saudi online customers. Atotal 224 respondents were obtained. The data was analysed using smart partial least square. The findingsshowed that responsiveness, customer satisfaction, ease of use and attitude are important for online customerretention. In addition, the findings indicated that the online trust can moderate the effect of the variables withonline customer retention. Retailers are advised to enhance the delivery time and reward customers for latedelivery to increase their retention.
Prototyping and environments

This chapter will introduce you to different ways of approaching the writing of very simple programs in Python and, in particular, will cover Jupyter notebooks and an introduction to the use of the Python debugger. Although both are relatively well-known tools, many people are proficient in the use of one but not both. It will also cover ways of approaching the writing of command-line interfaces and some useful third-party libraries to support succinct command-line tool development.
Feature Extraction of Basketball Shooting Based on Apriori Algorithm

To enhance the extraction and detection of basketball shooting feature and guide basketball training, an improved intelligent line breakage extraction method based on Apriori algorithm is proposed under computer vision. The template feature matching method is used to find the initial pixel cluster center of the basketball shooting action feature point visual image, and the false action information in the basketball shooting action feature image is eliminated by the gradient information enhancement method. The Apriori algorithm is used for image enhancement to realize the intelligent extraction and location of basketball shooting action feature, and to improve the ability of normative recognition of basketball shooting action. The proposed method realizes intelligent extraction of basketball shooting action features.
Performance Lab Mind Review: The Ultimate Stackable Nootropic

At a Glance This is our review of Performance Lab Mind. Which is, in my opinion, the best nootropic stack you can buy at the moment. Performance ...
FedEmail: Performance Measurement of Privacy-friendly Phishing Detection Enabled by Federated Learning.

Artificial intelligence (AI) has been applied in phishing email detection. Typically, it requires rich email data from a collection of sources, and the data usually contains private information that needs to be preserved. So far, AI techniques are solely focusing on centralized data training that eventually accesses sensitive raw email data from the collected data repository. Thus, a privacy-friendly AI technique such as federated learning (FL) is a desideratum. FL enables learning over distributed email datasets to protect their privacy without the requirement of accessing them during the learning in a distributed computing framework. This work, to the best of our knowledge, is the first to investigate the applicability of training email anti-phishing model via FL. Building upon the Recurrent Convolutional Neural Network for phishing email detection, we comprehensively measure and evaluate the FL-entangled learning performance under various settings, including balanced and imbalanced data distribution among clients, scalability, communication overhead, and transfer learning. Our results positively corroborate comparable performance statistics of FL in phishing email detection to centralized learning. As a trade-off to privacy and distributed learning, FL has a communication overhead of 0.179 GB per global epoch per its clients. Our measurement-based results find that FL is suitable for practical scenarios, where data size variation, including the ratio of phishing to legitimate email samples, among the clients, are present. In all these scenarios, FL shows a similar performance of testing accuracy of around 98%. Besides, we demonstrate the integration of the newly joined clients with time in FL via transfer learning to improve the client-level performance. The transfer learning-enabled training results in the improvement of the testing accuracy by up to 2.6% and fast convergence.
A Fuzzy Expert System for Early Diagnosis of Multiple Sclerosis

Background: Artificial intelligence plays an important role in medicine. Specially, expert systems can be designed for diagnosis of disease. Objective: Artificial intelligence can be used for diagnosis of disease. This study proposes an expert system for diagnosis of Multiple Sclerosis based on clinical symptoms and demographic characteristics. Specially, it recommends patients to refer to a specialist for further investigation.Material and Methods: In this empirical study, some symptoms of Multiple Sclerosis are mapped to fuzzy sets. Moreover, several rules are defined for prediction of Multiple Sclerosis. The fuzzy sets and rules form the knowledge base of the expert system. Patients enter their symptoms and demographic information via a user interface and Mamdani method is used in inference engine to produce the appropriate recommendation. Results: The precision, recall, and F-measure are used as criteria to analyze the efficiency of the expert system. The results show that the designed expert system can recommend patients for further investigation as effective as specialists. Specially, while the proposed expert system recommended referring to a doctor for some healthy users, most of the MS patients are diagnosed. Conclusion: The proposed expert system in this study can analyze the symptoms of patients to predict the Multiple Sclerosis disease. Therefore, it can investigate initial status of patients in a rapid and cost-effective manner. Moreover, this system can be applied in situations and places, which human experts are unavailable.
The Application of Improved Genetic Algorithm and Least Square Method in Computer Mathematical Modeling

The basic idea of genetic algorithm is to imitate the genetic process in biological world. In the whole operation process, it is generally composed of three basic operations: mutation, crossover, selection, gene for parameters, chromosome for binary, and finally a population.
Analysis of Leakage Magnetic Field and Winding Loss of Deep-sea Transformer

In this paper, taken the deep-sea transformer as the research goal and based on the numerical model method, the finite two-dimensional numerical model of deep-sea transformer is established by ANSYS and the leakage magnetic field and winding loss of the transformer are calculated. Then based on the two-dimensional numerical model, a three-dimensional model is established to solve the winding losses and verify the accuracy of the two-dimensional loss solution results. The analysis results show that the leakage magnetic field distribution and winding loss of the transformer obtained by the three-dimensional numerical model method are similar to the calculation results of the two-dimensional numerical model, which further verifies the accuracy of the finite element numerical calculation method in the calculation of the electromagnetic characteristics of deep-sea transformers With usability.
Pengaruh Model Pembelajaran Kooperatif Berbantuan Scramble terhadap Hasil Belajar Tema 1 Alat Gerak Hewan dan Manusia Kelas V Gugus 5 Kecamatan Selaparang Tahun Ajaran 2019/2020

This study aims to determine the effect of cooperative learning models assisted scramble toward theme 1 animal and human motion tools study result of 5thgrade at 5th selaparang sub-district school year 2019/2020. This research is experimental research with a type of quasi-experimental and the design is nonequivalent control group design. The data is collected through observation and tests. The data were analyzed with a normality test, homogeneity test and hypothesis test using an independent sample t-test. The analysis showed that the significant level of test = 0.00 was less than 0.05 (0.00 <0.05). Based on testing criteria, if the t-test <0.05, Ha is accepted and H0 is rejected. This means that cooperative learning models assisted scramble influential toward theme 1 animal and human motion tools study result of 5th grade at 5th selaparang sub-district school year 2019/2020.
Assuring Privacy-Preservation in Mining Medical Text Materials for COVID-19 Cases - A Natural Language Processing Perspective

Currently, there is a very large volume of Covid-19 related medical data that have been stored in cloud based systems and made available for studing the disease dynamics. without any privacy-preservation. In order to reduce possible privacy leakage and also accommodate massive medical reports with high efficiencies, we proposed a privacypreserving word embody-based text classification method for mining COVID-19 medical documents. It uses the recurrent neural network deep learning algorithm according to the identified internal hiding centralization pattern. In addition, a new model-fusion method is proposed for the continuous improvement of the system performance.The extensive numerical studies have demonstrated that the classifier of the proposed system has superior performance via integrating with the keywords extraction approach. Moreover, the advanced new model does not only accurately capture the keyword patterns but also effectively capture the analogical hierarchy structure of the pathology related datasets with lower computational complexity.
PROFESIONALISME GURU SD MENGGUNAKAN TEKNOLOGI INFORMASI DAN KOMUNIKASI (TIK) DALAM PROSES PEMBELAJARAN SEKOLAH DASAR DI KEC. KOTO TANGAH PADANG

This study aimed to determine the knowledge, attitudes and skills of teachers of information and communication technology (ICT) in the learning process. Assess the contribution of knowledge, attitudes and skills of teachers of information and communication technology (ICT) on the use of ICT in the learning process. Research methods approach using surveys of 40 teachers drawn proportionally  sampling zone based,instrument as the main data collection tool. Data analysis used descriptive analysis, multiple regression statistical test. The results showed ICT attitudes of primary school teachers in the early stages and is being followed by the knowledge and skills that are at a low stage.Teachers who have knowledge of ICT to contribute higher, followed by teachers' ICT skills and attitudes about ICT. There is a significant contribution to knowledge, attitudes and skills of teachers to use ICT in the learning process. The implications of this research are necessary increase in the use of ICT in the learning process at the elementary school is to provide ICT training to primary teachers who have the skills shortage in the ICT Key Words : Professionalism of teachers, the use of information and communication technology (ICT), the process of learning elementary school.
The historical experience of the “Soviet Primorye” almanac (1945–1958).

The article covers the historical experience of the “Soviet Primorye” almanac (which now is called «Literary Vladivostok»). There are very few special works in historiography devoted to almanac's analysis. The author investigates the post-war period of almanac's activity (1945–1958), paying special attention to the role of AUCP(b). Every aspect of almanac's publicistic activity – from the issue's content to its distribution – was under the full control of Primorye party committee. The communist party took actions to improve the work of Primorye writer's organization, obligated the almanac to mentor young writers and help them publish. On the other hand, ideological control demanded that works be written on particular topics (e.g. labor, kolkhoz villages, the revolution history). The socialist realism method was to be applied in the works as well. The article also reviews the critical materials addressing the almanac's contents and its lack of artistic level. The findings of the almanac's fiction and publicistic works quantitative analyses are also presented in the article.
When the Drone Flies! Rethinking Communication Models in the Context of Innovations

As the use of technology in development continues to rise, Communication for Development (C4D) has been interrogated to guarantee that the communication demanded by innovation conceptually fits into existing models. Communication in innovation suggests more than what is offered by the traditional theory and practice. This paper studies the UNICEF work that launched an innovation to use drones to transport laboratory samples from a peri-urban health facility to a central laboratory. The C4D team recognised the need for a non-traditional C4D approach that included steps to Introduce, Name and Interrogate the innovation. The paper argues that while innovations proliferate, C4D models must mutate to better respond; and particularly to leap-frog new technologies. This requires rethinking communication models and approaches.
말하기 평가 등급기술을 위한 학습자 담화 능력별 특징 연구 - 부탁에 대한 거절하기 과제 수행을 중심으로 -

The purpose of this study is to develop an empirically verified grading scale description using the ‘performance data-driven approach’ suggested by Fulcher(1987). This study focuses on creating a standardized category of the discourse features for Korean language learners depending on their discourse competence. The data used in the study were collected from 50 Korean language learners by conducting a CBT speaking test using the ‘REFUSAL’ task. The speech data were graded by five raters, and the speech samples were categorized into five different groups according to their grading results. Additionally, the speech data were transcribed and analyzed using discourse analysis. According to the analysis, five groups of different discourse competence level demonstrated distinct discourse features. The group with the highest level of discourse competence showed a complete four or three level discourse structure and a coherent discourse equivalent to the native Korean speakers. Furthermore, the group with a higher level discourse competence expressed its willingness to help and apologized more. Meanwhile, the groups with a lower level discourse competence displayed incomplete discourse structures and numerous negative factors such as repetitions and direct refusal expressions. The results of this study can be utilized not only as objective data for developing a speaking scale description for the Korean language speaking test, but also for the development of effective teaching discourse method, rater training courses and instrumental textbooks.
Milenial, Pemimpin Politik, dan Debat Capres Indonesia 2019

&lt;p&gt;This study tries to explain and the reception of millenial generation in Universitas Padjadjaran towards the representation of leaders in the nonverbal message and the substance of the message of Indonesian Presidential candidates in 2019 presidential debate. Data was collected by in-depth interviews and FGDs of eight informants. The results of this study indicate that the reading of informants on the representation of the leaders of the candidates for the substance and nonverbal candidates in the 2019 Indonesian Presidential Debate shows candidate 01 superior to candidate 02. Candidate 01 excels in five variables: nonverbal kinesik, nonverbal artifactual, substance alignment topics, substance selection and alternative solution arguments, and the substance of the stimulation of alternative solutions. Whereas candidate 02 is only one variable superior namely nonverbal paralinguistic.&lt;/p&gt;
The privileging of representation and the marginalising of the interpersonal: a metaphor (and more) for contemporary gender relations

The contemporary marginalising of interpersonal features is hardly surprising given the negative value assigned to the emotions, the realm of feeling, in contemporary Western culture and the primacy of the referential within linguistics itself. The effects have been unfortunate, most significantly in imposing arbitrary limits on notions of ‘language’ as a human phenomenon and of ‘linguistics’ as the study of that phenomenon. Infants develop repertoires of signs for expressing interest, pleasure, displeasure and a desire for interaction itself, as well as for getting people to do things for them, well before they start using language more referentially by learning ‘words’ as ‘labels’. The primary groups whose linguistic practices have been systematically devalued by attitudes which assume the validity of such a dichotomy, between talk ‘for talk’s sake’ and talk for ‘getting things done’, have been so-called ‘primitive’ peoples, those in whose societies a central role of language lies in its interactive role and its role in ritual and myth.
Identification Word Spacing of Erroneous Sentences on Indonesian Scientific

Scientific writings in Indonesian language must the rules of the General Guide to the Reformed Indonesian Spelling especially in terms of word spacing. good word spacing is proportional to the width of the typeface. generally use the align right facility in order to have article look neat in typing, but causes space from word to word over space. Additionally, according to the General Guide book for the updated Indonesian spelling, there are rules that use the distance of words with punctuation after and before punctuation. This research is intended to make for detecting applications using word spacing of the Regular Expression String algorithm and to comment on articles based on principles that are in accordance with the General Guidelines for Indonesian Reformed Spelling.
Blockchain in Healthcare

Healthcare is a key factor in deciding people's physical and mental well-being, which is why it is often widely recognized as a major contributor to the economy of a country. The quality of society's healthcare system and facilities is considered one of the most important factors in the development of a country. Today almost all medical records are stored in an Electronic Healthcare Record (EHR) system which improves access to clinical data intended to streamline costs. However, EHRs are essentially non-portable and kept on the networks where they were created mainly for purposes of interoperability, security, and liability. This results in a loss of medical quality for the patient and a rise in healthcare costs as the sharing of information between multiple healthcare facilities, spread around different places, is highly dependent on the patient who is not known as the data owner and might not be aware of such treatments obtained.The objective of this article was to investigate is Blockchain relevant to the healthcare system and benefits when it was applied to the medical sector. Considering if Blockchain can help patient be the owner and have the control of their medical records. With its functions and effectiveness, Blockchain could be the key to change the current health system. While it is not yet a 100% perfect technology, what Blockchain offers can help the healthcare system develop or at least alleviate problems that are occurring.
EnDASH - A Mobility Adapted Energy Efficient ABR Video Streaming for Cellular Networks

User experience of watching videos in smartphones while travelling is often limited by fast battery drainage. Existing client video players use adaptive bitrate (ABR) streaming through Dynamic Adaptive Streaming over HTTP (DASH) to improve user’s Quality of Experience (QoE) while ignoring the energy savings aspect, which has been addressed in our work. In this paper, we propose EnDASH- an energy aware wrapper over DASH which minimizes energy consumption without compromising on QoE of users, under mobility. First, we undertake an extensive measurement study using two phones and three service providers to understand the dynamics between energy consumption of smartphones and radio related network parameters. Equipped with this study, the proposed system predicts cellular network throughput from the radio parameters within a finite future time window. The prediction engine captures the effect of associated technology and vertical handovers on throughput, unlike existing works. EnDASH then uses deep reinforcement learning based neural networks to first tune the playback butter length to the average predicted cellular network throughput and then to select an optimal video chunk bitrate. It achieves a near 30% decrease in the maximum energy consumption than state-of-the-art ABR Pensieve algorithm while performing almost at par in QoE.