Reviewerly/exHarmony huggingface dataset:
Handling big data security and Service through bilinear pairing and parallel computation

A new type of data, Big Data, has emerged as a result of the increased use of online services by a huge number of people. Recent years have seen an explosion in the interest in big data as a concept. Analyzing and properly processing large amounts of data is exceedingly challenging. It becomes a gigantic challenge to maintain the privacy of big data, which has an incredibly high velocity and volume which increases the possibility that mishandling of this data might lead to the theft of secret or sensitive information, which can be extremely troublesome in the case of an incident. Several techniques have been developed to counteract this impact, but they have not proven very effective. Because of this, a methodology has been developed that efficiently divides, classifies, and splits massive data query that are mapped for parallel computing on to the Mongo DB. The technique described in this research paper makes use of the idea of bilinear pairing through the application of hashing and the detection of avalanche effect for the purpose of tamper detection and forensic analysis for effective security report creation. The detailed experimentation has been performed to determine the performance metrics of the presented technique which has reached the desired outcomes.
AZ-SMC Trial - Cross-sectional dataset

Data collected as part of a cross-sectional survey at the end of each rainy season, at which blood samples were taken for determination of malaria infection. Data was collected as part of the AZ-SMC trial (clinicaltrials.gov NCT02211729) in Hounde District, Burkina Faso and Bougouni District, Mali between 2014 and 2016.
A Secure Encryption Mechanism to Manage Your Password with Asymmetric Key

In day to day life internet demand have been increased now for anything we required internet connection which means it is not limited to one person its open for all so to identify each member on the Internet we have been given a User name and password for identifying genuine user, therefore there is the number of user credential has been created to identify our self, but remembering user credential is a big problem for everyone in today's life, so we use to store our credential in the web page for ease of access, but storing the password in the web page it is not secure since Cookies can extract easily or Brute force attack can be performed easily to overcome these problems in this paper we have proposed a password saving mechanism with the help cryptography method where user can use his/her private key to encrypt or decrypt his/her credential.
A Thorough Study on Privacy preserving Crowdsourcing platform On blockchain

The Crowdsourcing approach has been highly useful and extremely popular in the recent years. The reason for this immense popularity is the improvement in the communication capabilities that help coordinate the workers effectively. This is since the platform has aided in the completion of extremely complex tasks. Crowdsourcing is a method of bringing together a big group of individuals or a crowd, to complete the task. This enables the work to be completed successfully, which would have not been feasible if the crowdsourcing approach had not been implemented. However, the majority of crowdsourcing methods have flaws. On the worker's side, there are increasing issues with unfinished or abandoned jobs. In addition, task uploaders have complained about receiving insufficient pay. Both situations result in a loss of confidence among the crowd intelligence system's many players. As a result, this literature survey paper utilizes the previous researches which describe a crowdsourcing system as a viable and safe resolution to these problems. The Reverse Circle Cipher Encryption and Entropy Estimation algorithms, as well as Decision Tree and the distributed Blockchain infrastructure, are helpful in achieving the prescribed goals in this literature survey paper.
Organized Crime, Corruption and the Challenges of Economic Growth in the Economic Community of West African States

This study examined organized crime, corruption, and their challenges to the economic growth of the Economic Community of West African States (ECOWAS). Organized crime and corruption can have a grossly negative impact on the economic growth process of every system, but the extent of damage they have needs to be measured to determine the policy implications to the region. The research is a panel study of 11 countries in the ECOWAS region. The study employs the Fixed Effects Model (FEM) and the Feasible Generalized Least Square (FGLS) known also as the random-effects model with the pooled OLS as a control on the defined objectives. Results show among others that organized crime does not have a significant impact on economic growth, whereas, corruption significantly reduces economic growth. The study concludes that organized crime does not significantly impact economic growth, but that Corruption significantly impacts economic growth in the ECOWAS region. Part of the policy implications and recommendations is that Domestic investment significantly contributes to economic growth. This is encouraging and should be greatly encouraged as it increases production, job creation and reduces dependency ratio and poverty.
Additional Information Delivery to Image Content via Improved Unseen–Visible Watermarking

In a practical watermark scenario, watermarks are used to provide auxiliary information; in this way, an analogous digital approach called unseen–visible watermark has been introduced to deliver auxiliary information. In this algorithm, the embedding stage takes advantage of the visible and invisible watermarking to embed an owner logotype or barcodes as watermarks; in the exhibition stage, the equipped functions of the display devices are used to reveal the watermark to the naked eyes, eliminating any watermark exhibition algorithm. In this paper, a watermark complement strategy for unseen–visible watermarking is proposed to improve the embedding stage, reducing the histogram distortion and the visual degradation of the watermarked image. The presented algorithm exhibits the following contributions: first, the algorithm can be applied to any class of images with large smooth regions of low or high intensity; second, a watermark complement strategy is introduced to reduce the visual degradation and histogram distortion of the watermarked image; and third, an embedding error measurement is proposed. Evaluation results show that the proposed strategy has high performance in comparison with other algorithms, providing a high visual quality of the exhibited watermark and preserving its robustness in terms of readability and imperceptibility against geometric and processing attacks.
The Effect of Various Learning Approaches on Mathematical Learning Outcomes based on the Multiple Intelligences of Students

The aim of this paper is to describe the research results on multiple intelligences in mathematics learning, using a descriptive approach. It also ascertains the influence of various learning models on mathematics learning outcomes based on students’ multiple intelligences. Student Teams-Achievement Divisions (STAD) and Team Games Tournament (TGT) learning models improved learning outcomes for students possessing logical-mathematical, kinesthetic, and interpersonal intelligences. Furthermore, Group Investigation (GI) and Numbered Head Together (NHT) learning models improved student learning outcomes with logical-mathematical intelligence. Two Stay Two Stray (TSTS) learning model with peer tutors improved student learning outcomes with linguistic, logical-mathematical, and interpersonal intelligences. Team Assisted Individualization (TAI) and Jigsaw learning improved student learning outcomes with linguistic intelligence. Also, TSTS and NHT learning models improved student learning outcomes with logical-mathematical, and interpersonal intelligences. Keywords: compound intelligence, learning model, mathematics
Discussions on the Teaching of Piano Accompaniment in Normal University

Piano playing is an important form of performance.It mainly consists of 3 performances, including piano solo, duet and accompaniment.The piano accompaniment is also known as the piano art instruction, and it is a widely-used form of music art performance.After years of practice, piano accompaniment has gradually formed its unique artistic charm and plays a leading role in the piano solo, playing an irreplaceable role in music performance.Piano accompaniment, because of its unique means of expression and artistic form, and its wide coverage and strong practicality, requires players to have many aspects of music knowledge and high playing skills.Therefore, it is necessary to explore the current situation of piano accompaniment teaching and the cultivation of students' piano accompaniment ability, so as to make piano graduates more suitable for the needs of social development.
Evolving visual representations from noise

Seeing involves not only the light that reaches our retinae, but also visual memories and expectations. When searching for our favourite mug, we hold its appearance in mind. When talking to a friend over the phone, we picture their facial expressions. Talented artists can even paint detailed visual scenes from memory. The content of such mental representations is of great interest in perceptual and cognitive neuroscience, yet is challenging to measure experimentally (alas, too few of our participants are talented artists!). One previously-proposed approach is reverse correlation. Participants are asked to report whether they see a signal—e.g., the letter “s”—in pure noise. Over enough trials, some random noise samples will happen to resemble the signal the participant has in mind. Averaging over all trials in which a participant spuriously detected a signal provides a “classification image” — a visualisation of their representation of the letter. One major drawback of reverse correlation is that it requires tens of thousands of trials to obtain even coarse impressions of mental images. Perhaps more importantly, reverse correlation cannot recover multiple concurrent templates. If a participant imagined both print and cursive instances of the letter “s”, the recovered classification image would be a jumble of both. We address these issues using an evolutionary algorithm approach. We generate image populations by crossbreeding noise. On each trial, participants are shown multiple alternative images drawn from these populations. Across generations, only those images in which participants detect a signal are kept for further breeding. In both simulation and experiments with human participants, we demonstrate that this method converges faster than standard reverse correlation, can recover multiple internal representations of a signal, and can even provide access to the mental representation of illusory visual percepts. Our approach thus provides an efficient, data-driven way to access complex mental representations.
Impacto del aislamiento obligatorio en los diferentes entornos educativos: Estudio de caso Institución Educativa Edukids y Maximiliano Neira Lamus

As we already know, the world has been transformed due to the health contingency derived from covid-19. We could affirm that all our daily life has had to adapt to these changes; An important aspect in this transformation has been education and this has generated challenges for each and every one of the actors involved in the educational field: students, parents and school, and it was consolidated under this emergency, when the situation forced the parents to be a fundamental part of their children's learning and teaching by having to adapt the “I learn at home” strategy.
La natura della memoria autobiografica e l’autobiografia linguistica. Il metodo autobiografico nella linguistica educativa per gli anziani

Autobiographical memory is an essential part of long-term memory. It intersects cognitive processes, current emotions related to the memory of oneself past, and thought about oneself and one’s goals and purposes. Autobiographical memory joins past with future of an individual. By it everyone forms an idea about himself/herself. Starting from the features of autobiographical memory it is possible to elaborate an autobiographical method. This paper aims to analyse the main features of the autobiographical memory within the perspective of the language education of the elderly. It will especially focus on the model of language autobiography as an educational and training tool for the language education of the adults and elderly.
PEMANFAATAN BUKU SEKOLAH ELEKTRONIK (BSE) MELALUI SMARTPHONE PADA MATA PELAJARAN IPS TERPADU DI SMP NEGERI 1 EREMERASA: Irpan Ansyari

Abstract: This class action research has the aim of studying the application of the use of electronic school books as a source of learning as well as efforts to improve student achievement. As for the background of this research because e-books or electronic school books are one of the interactive media along with other advantages such as easy, practical and anti-damaged. This research data collection technique by providing formative tests on each cycle and observation sheet. The data analysis method is quantitative descriptive. Learning achievement is analyzed by comparing tests between cycles. Indicators of learning achievement success in the form of mastery learning classically ≥ 85%. The results showed an increase in mastery learning from 75% or 15 people who finished in cycle I, to 90% or 18 people who completed in cycle II. This proves that the use of BSE on smartphones as a source of learning can improve mastery and learning achievement. The conclusion of this study is the effective use of BSE through smartphones can improve student achievement in class IX B in SMP Negeri 1 Eremerasa. Research recommendations to teachers to make maximum use of learning resources in schools such as BSE. And to students to better utilize the use of smartphones to increase knowledge and knowledge.
NeurIPS 2020 NLC2CMD Competition: Translating Natural Language to Bash Commands

The NLC2CMD Competition hosted at NeurIPS 2020 aimed to bring the power of natural language processing to the command line. Participants were tasked with building models that can transform descriptions of command line tasks in English to their Bash syntax. This is a report on the competition with details of the task, metrics, data, attempted solutions, and lessons learned.
Random Variables in Machine Learning

This chapter aims at a detailed discussion on the concepts of random variables (single and multiple) and their role/applications in the specified areas of machine learning. Discussion of each concept of the random variable will immediately be followed by its application with reference to machine learning.
AN ANALYSIS OF STUDENTS’ READING COMPREHENSION IN NARRATIVE TEXT AT THE NINTH GRADE OF SMPN 3 MERANGIN ACADEMIC YEAR 2020/2021

Teaching reading material to students in school is based on syllabus. According to this syllabus. Understanding text is determined by the purposes for reading, the context, the nature of the text, and the readers’ strategies and knowledge. On the other hand, the students at the ninth grade of SMPN 3Merangin academic year 2020/2021 have difficulty to comprehend the text and it is influence to their achievement on reading comprehension. Students have less involvement if the teacher asks them to read the text. Therefore, this research purposed to find out the students’ reading comprehension in narrative text at the ninth grade of SMPN 3 Merangin academic year 2020/2021. This research designed with descriptive quantitative research. The population of this research were the students of ninth grade of SMPN 3 Merangin which is consisted of 26 students. It was consisted of 12 students are male, and 14 students are female. Through this purpose, in collecting the data the researcher used reading comprehension test with essay form. The test consisted of 20 questions in essay form in which the sudents should answer the question based on the text. Based on the analyzing data, the researcher concluded that the students’ reading comprehension in narrative text at the ninth grade of SMPN 3 Merangin academic year 2020/2021 was good with students’ average was 73,46. Based on the conclusion, the researcher proposes the students have to increase their ability in reading comprehension especially in narrative text by enrich their knowledge about reading comprehension.
FUNDAMENTALS OF EXPANSION OF EDUCATIONAL SUBJECTS IN THE CREDIT-MODULE SYSTEM OF TEACHING

The article analyses the basics of teaching the expansion of subjects in the credit-modular system of education.
Figure 3.1.8

Axial divergence aberration profiles shown for several levels of axial divergence. Case 1 (of Table 3.1.1) is computed for a source length of 12 mm and a sample and receiving-slit length of 15 mm. The remaining three simulations include are of case 2, where Soller slits limit the axial divergence (R = 217.5 mm).
Students Perception on the Use of Speech Texter Application in Teaching Pronunciation Skills

Teaching pronunciation for EFL, students ideally need to learn how to produce sound like a native speaker. Students should be assisted to practice and drill the correct pronunciation. However, teaching pronunciation in pandemic covid-19 situation became problematic not only for the lecturers but also for students. This research aimed to find out the students’ perception on the use of speech texter application in teaching pronunciation skill. The method of the research was descriptive qualitative. The subject of the research was the first semester students of 2020/2021 academic year which consist of 18 students. The instrument used to collect the data was in the form of semi-structured interview. There were 4 semi-structured interview gave to the students. The data were analyzed by using threeanalysiscomponents: datareduction,datadisplay,and conclusiondrawing. After analyzing the data, the result showed that the use of speech texter application was interesting and motivated them to drill the pronunciation until they produced the correct words. Then, they were also sure to be able to speak with the correct pronunciation after using the application. Thus, it can be concluded that students have a positive perception on the use of speech texter application in teaching pronunciation skill.
Examining the Effectiveness of Teamwork in Work Engagement among Gen Y-A Conceptual Framework

As the older generation is retiring from the workforce, it became a concern for many organizations on ways to manage the new generation who is flowing into the current workforce. This new generation is known as Gen Y. This generation workforce often linked to job hopping and their loyalty towards the organization is being questioned by researchers as many organizations are experiencing a high level of attrition among them. This study investigated teamwork as a critical success factor of work engagement among Gen Y. The methodology adopted in this study includes an extensive review of the literature on teamwork that contributes to working engagement, followed by questionnaire distribution and then the answers were processed and statistically measured and analyzed. The results of this study conclude that there is a significant positive relationship between teamwork, work engagement and IR 4.0. The practical implications of the study will be useful for the organization to address and examine the effect of teamwork that influences work engagement to reduce high turnover among Gen Y employees.
Social Media: A Platform for Effective Instructional Delivery of Technical and Vocational Education and Training (TVET) Programmes

Social media is significantly paving its way in the classroom and it could be useful for effective instructional delivery of Technical and vocational education and training (TVET) programmes. This study was carried out in Enugu State , Nigeria to determine Social media as a platform for effective instructional delivery of TVET programmes in Public Universities in Enugu State. Survey research design was employed for the study. The population consisted of 97 TVET lecturers teaching in the two public universities offering TVET programmes in Enugu State. The entire population was used. Therefore, no sample was drawn because of the manageable size of the population. Two research questions were answered by the study and two null hypotheses tested at .05 level of significance. The result of the study revealed that social media is a useful platform for effective TVET delivery but TVET lecturers utilize social media to a low extent. From the findings of the study, the researchers recommended among others that TVET lecturers should update their skills in the use of social media and also, TVET institutions should upgrade social media facilities in their various institutions for effective utilization in TVET delivery.
IMPLEMENTASI SISTEM PAKAR DALAM PENANGANAN PENYAKIT KANKER

The use of information technology in patient health services in hospitals will never be separated to achieve efficiency and time effectiveness. In the health sector, the use of technology is still very much needed, let alone its use. In the treatment of cancer, many efforts have been made by patients from prevention, screening (early detection), diagnosis, and treatment. With expert methods are expected to help in providing recommendations in the treatment of cancer. The expert system will read the inputted symptoms to be able to make recommendations in dealing with cancer. The OMT method is an object-based approach methodology that uses use case tools in building software.
URL Hoaxing Detection using Machine Learning

The paper is on our project that is all about detecting Phishing website. This project plays a cardinal role in detection of a phishing website and keeping user safe from fraudsters. Phishing is the most dangerous cyber-crime of the world with about 241,324 reported cases in 2020 and 96% of these attacks arrive by emails in form of some masked URL. These attacks end up costing in billions yearly. In this paper we have discussed a Machine Learning model working on Random Forest algorithm to predict whether a website is phishing or not by using URL of the website and analyzing its HTML.
Empirical Findings on the Role of Structured Data, Unstructured Data, and their Combination for Automatic Clinical Phenotyping

The objective of this study is to explore the role of structured and unstructured data for clinical phenotyping by determining which types of clinical phenotypes are best identified using unstructured data (e.g., clinical notes), structured data (e.g., laboratory values, vital signs), or their combination across 172 clinical phenotypes. Specifically, we used laboratory and chart measurements as well as clinical notes from the MIMIC-III critical care database and trained an LSTM using features extracted from each type of data to determine which categories of phenotypes were best identified by structured data, unstructured data, or both. We observed that textual features on their own outperformed structured features for 145 (84%) of phenotypes, and that Doc2Vec was the most effective representation of unstructured data for all phenotypes. When evaluating the impact of adding textual features to systems previously relying only on structured features, we found a statistically significant (p < 0.05) increase in phenotyping performance for 51 phenotypes (primarily involving the circulatory system, injury, and poisoning), one phenotype for which textual features degraded performance (diabetes without complications), and no statistically significant change in performance with the remaining 120 phenotypes. We provide analysis on which phenotypes are best identified by each type of data and guidance on which data sources to consider for future research on phenotype identification.