Reviewerly/exHarmony huggingface dataset:
EpyNN: Educational python for Neural Networks

Artificial Neural Networks (ANNs) have achieved unequaled performance for numerous problems in many areas of Science, Business, Public Policy, and more. While experts are familiar with performance-oriented software and underlying theory, ANNs are difficult to comprehend for non-experts because it requires skills in programming, background in mathematics and knowledge of terminology and concepts. In this work, we release EpyNN, an educational Python resource meant for a public willing to understand key concepts and practical implementation of scalable ANN architectures from concise, homogeneous and idiomatic source code. EpyNN contains an educational Application Programming Interface (API), educational workflows from data preparation to ANN training and a documentation website setting side-by-side code, mathematics, graphical representation and text to facilitate learning and provide teaching material. Overall, EpyNN provides basics in Python for individuals who wish to learn, teach or develop from scratch.
BITCOIN PRICE PREDICTION WITH COVID-19 SENTIMENT USING LSTM NEURAL NETWORK

Cryptocurrencies are nowadays getting popular for investment due to its various benefits such as low transaction cost, blockchain secured platform, profit, etc. Bitcoin being top of the market capitalization currency, gained more popularity during covid-19 pandemic. This study focuses on bitcoin price prediction with covid-19 sentiment. Here Long Short Term Memory Deep learning model based on machine learning is used for price prediction. At the end both results i.e., with covid-19 sentiment and without it are compared which shows model performs better by adding sentiments.
Resources Consumption Accounting, Cost Reduction For Customers, and Competitive Advantage: An Iraqi Case Study

Accuracy and quality of customer cost information depend on the selection and execution of a contemporary strategy to cost accounting and administration that is responsive to fierce competition between economic units and incorporates resource consumption accounting. RCA, the latest generation of cost accounting and contemporary management software, enables managers to make informed choices and establish effective plans. This research intends to illustrate the influence of resource consumption accounting in rationalizing customer costs in the bags / Hilla facility by lowering product prices, detecting idle energy, and identifying the factory's best customers. In the Al-Hilla / Al-Hilla / Al-Hilla plant, a case-study technique was applied. Through this process, an evaluation of the laboratory's actual expenses and the application of resource consumption accounting are made using the laboratory's existing data for the year 2018. The research concluded that the effectiveness of customer cost analysis is contingent on the technique used and that accounting for resource consumption is one of the most effective and accurate methods for cost rationalization. The resource consumption accounting highlights the economic unit is resources, the entwined relationships between them, and their optimum usage. Furthermore, it finds idle (untapped) energy and eliminates it from goods and services to minimize prices. Thus, the researcher's most significant suggestions affirm that enough attention is given to the application of resource consumption, accounting for their contribution to attaining this aim.
The Functional Regression With Reconstructed Functions From Hybrid Principal Components Analysis: With EEG-fMRI Application

Objective: In this article, we reconstruct the hybrid data with hybrid principal component analysis (HPCA) as a feature extraction step and model them with functional regression as a modeling step, and comparing models and choose the best number of HPCA based on the prediction accuracy as an evaluation step. Method: We decompose the hybrid data to the eigencomponents with HPCA. The reconstructed data from HPCA were divided into the training and testing dataset. The function-on-function signal compression and scalar-on-function regressions were used. Three simulation scenarios and their applications in the neuroimaging datasets (EEG-fMRI) were studied. The number of HPCA was selected with the mean squared prediction error (MSPE). Result: The simulation shows that the raw data, reconstructed from the first and all HPCAs for the training dataset has median MSPE 0.1001, 0.0028, and 0.0174 respectively, and for the testing, the dataset has 0.3207, 0.1118, and 0.2484 respectively. The EEG-fMRI suggests that in both auditory and visual tasks and standard and target stimuli for different regions of the brain the first HPCA has the smallest MSPE. Conclusions: We conclude this method improves the prediction accuracy of the experiments with the EEG datasets. And we recommend that instead of using the functional PCA on the desired dimension, reconstruct the data with HPCA and average it on the other two dimensions for functional regression models.
Working Memory and L2 Grammar Development in Children

The role of working memory in language learning has received considerable attention, but several pertinent issues remain. One of these concerns the directionality of the relationships between working memory and language learning. Another issue relates to different types of processing and working memory components involved in learning different aspects of a second language (vocabulary, grammatical sub-skills, e.g., subject-verb agreement, verb placement, word order, auxiliaries). In this chapter we review and integrate findings of previous studies, following the extraction and integration model (Thiessen et al., 2013), and apply these to second language learning. In so doing, we distinguish between statistical learning based on conditional relations of adjacencies (extraction) and statistical learning based on distributional patterns of non-adjacencies (integration). We propose how L2 children's gradual increase in knowledge of the second language increases the sensitivity of working memory to cues in ambient speech that, in turn, fosters further second language learning.
Empowering Students’ Reading Comprehension Through Cornell Note-Taking Method

The purpose of this research was to determine whether or not using the Cornell note-taking method improves students' reading comprehension while they are enrolled in the first grade at MA-Al Hidayah. In this study, a pre-experimental research design was used, and participants in one group had a pre-test, treatment, and post-test. The overall sample size was thirty students, and the approach utilized was called purposive sampling. This study made use of a multiple-choice questionnaire as its tool. The findings of this study indicate that the pre-test mean score for students was 54.38, but that it increased to 79.06 after the intervention. It is possible to draw the conclusion that the students' reading comprehension increased, and this indicates that using the Cornel Note Taking approach led to an increase in the students' reading comprehension.
Economic Development and Institutional Economic Mechanisms In Emerging Countries: A Case of Iraq

The institutional economy is concerned with the role of enterprises in economic activity, access to efficiency, and shaping economic behavior. Because institutional procedures are critical in various productive activities, a state suffering from decline and a lack of institutional practices will not advance economically. It also emphasizes the importance of Conducting extensive research on institutions and market views and the many interactions between persons and institutions in society to improve the position of society's members and the state as a whole on both the local and local international level. This study aims to illustrate the historical context of the institutional economy and its contemporary advancements. It seeks to show the dynamics behind current institutional economies. Finally, it tries to provide light on Iraq's institutional architecture through several indicators. The findings reveal that Iraq's institutional economy is deteriorating across several economic sectors, which has resulted in rampant corruption. In addition, restricted limits on productive activity have harmed the country's economic progress.
Pemanfaatan IoT untuk Mendeteksi Dini Kelembaban Kamar Hotel

The pandemic period has greatly affected various business sectors which also resulted in the decreasing income of most people. This is coupled with the implementation of PPKM (Enforcement of Restrictions on Community Activities) in several areas, so that community activities are very limited. One of the impacts of this pandemic is being felt in the hotel business, where many hotels and inns are not selling well and this business has to go out of business. Hotels and inns that can still survive are forced to reduce the number of employees and reduce operational costs, one of which is the cost of room maintenance. Along with the number of vacant rooms due to lack of customers and reduced number of employees, resulting in vacant rooms are rarely opened which will become damp and stuffy. If this is left for a long time will result in the growth of mold in the hotel room, so a process of monitoring temperature and humidity is needed. These problems can be solved by utilizing the Internet of Things (IoT). From the results of testing the temperature and humidity sensor readings using DHT11, the results are quite accurate with an error rate of 1.30% for measuring temperature and 3.79% for measuring humidity. Making an IoT system using Blynk can be done very easily because it does not require programming skills in its manufacture.
Design Of Class Vii Informatics Learning Media Using Adobe Animate In MTSN 6 AGAM

This research aims to develop and produce computer based learning media using adobe animate application in informatics subjects. Learning media has a very important role in learning. This research uses the 4D version of the Research and Development (R&amp;D) method, namely Define, Design, Development, and Disseminate. The multimedia development model use is the luther sutupo version model which has six stage, namely concept, design, material collection, assembly, testing, and distribution. The result of this study showed (1) validation test by three lecturers in computer informatics engineering expeerts showed a value of 0, 94 with a very valid category, (2) practicality tests from three informatics subject teachers showed a score of 0,95 showed very practical, (3) the effectiveness test of 25 students showed a score of 0,90 showed very effective
Learning Pinball TWSVM efficiently using Privileged Information and its Applications

Expert knowledge plays a vital role in any learning framework. However, in the field of machine learning, an expert's knowledge is rarely utilised. Furthermore, most machine learning methods (support vector machine, SVM-based) use a hinge loss function that is sensitive to noise. Thus, in order to benefit from expert knowledge while reducing noise sensitivity, we propose in this paper a fast and novel Twin Support Vector Machine classifier based on privileged information with a pinball loss function, dubbed Pin-TWSVMPI, where expert knowledge is in the form of privileged information. The proposed Pin-TWSVMPI incorporates privileged information into two nonparallel decision hyperplanes by employing a correction function. Furthermore, we employ the Sequential Minimal Optimization (SMO) technique to get the classifier in order to make computations more efficient and faster, and we have demonstrated its applicability for pedestrian detection and handwritten digit recognition. Furthermore, for UCI datasets, we first construct a process that retrieves privileged information from the dataset's features, which is then used by Pin-TWSVMPI, resulting in improved classification accuracy with a reduced computing time.
A Substantiation and Key Agreement Based on Unidentified Identity for Peer-to-Peer Cloud

Abstract: Real-time data collected by smart sensors deployed in factories is shared over open channels as the Industrial Internet of Things (IIoT) expands, posing a risk of unauthorised access to transmitted messages by adversaries, resulting in a privacy leakage problem. However, users frequently find it difficult to backup all data from the original cloud servers to their mobile phones in order to upload the downloaded data to the new cloud provider due to insufficient local storage and computational capabilities. To address this issue, it is proposed to gather information on the available solutions for the application of security issues in peer-to-peer networks, with a focus on authentication mechanisms.
International University Rankings and The Accessibility of University Websites: An Analysis of Arabic and Iraqi Universities

Prioritizing educational achievements, notably higher education, is critical for economic and social growth in developing or developed countries. Educational institutions in general, whether universities, institutes, or others, seek to apply their academic programs to their inputs through the most advanced scientific methods to produce program-digesting outputs prepared for entry into the labor market. As a result, educational institutions are often classified according to many worldwide classifications, ranked sequentially according to the type in charge of this process and the criteria and indicators used. One of the most well-known classifications in this field is that of China's Shanghai Jiao Tong University. The Times THES-QS ranking of world universities THES QS World University Rankings, and a third classification, no less significant than the previous two, is that of the Spanish Webometrics website. Arab institutions have typically been excluded from higher ranks in these three rankings, save one of Saudi Arabia's universities. Nevertheless, it was listed among the top 200 institutions in the online metrics webometrics ranking when King Saud University was placed 99th after being ranked 100 in the second edition of 2010.
Facial Recognition Technology Code of Ethics

Facial recognition technology (FRT) is a tool used to identify individuals by scanning their face and comparing it to a database of facial images. In the last decade, the use of FRT has rapidly increased and is now used all around the world. This has resulted in many ethical issues caused by taking an individual’s images without consent to train FRT programs, FRT misidentifying individuals, and using FRT to classify individuals as part of specific groups based on appearance alone. Because of these issues, a new code of ethics is proposed to provide a guideline for the creation and use of FRT. The code of ethics will prevent images of individuals from being taken and used without their consent and prevent FRT from being used unethically.
Code of Ethics for Facial Recognition Systems: A Case Study

The integration of Facial Recognition Systems (FRS) in society is increasing. A key factor in adequate performance for FRS is the reliance on user data. Hence it is important not only to understand the ethical issues surrounding FRS but also to ensure that a proper code of ethics is established. This paper analyses and discusses the ethical issues with existing FRS as well as ethical conducts that are already put in place. Additionally, a new code of ethics will be created for FRS. Furthermore, a case study of a specific project involving FRS is conducted. Each principle listed in the newly created code of ethics is applied to the selected project.
Adding Context to Industry 4.0 Analytics: A New Document Driven Knowledge Graph Construction and Contextualization Approach

Throughout the ripples of digitization, companies and organizations are becoming smarter and equally dependent on information. Information is integrated along the value chain of organizations, while through industrial analytics and smart algorithms, information can be harnessed for manufacturing and business decisions. Together this shapes the idea of industry 4.0 – the organization as an interconnected world. However, analytical support is generated in the context of its recording and creation. So, to harness outcomes from different sources, it not only needs an information integration but furthermore an integration of context, into a representation strict enough for utilization and flexible enough to bridge the understanding across the organization. This work in progress introduces knowledge graphs as tools for contextualization and how to extract graphs from repositories of documents, as a representation of organizational knowledge. The graph will be harness in an industrial example to contextualize analytical solutions throughout teams and departments.
Teaching Mode in the Management of Higher Vocational Colleges in the Era of Big Data

In the current information society, colleges and universities have produced a wealth of data on educational learning, research, personnel training, and student management. Changes in data formats and quantity lead to changes in quality. If university administrators can summarize these massive data, conduct effective mining and analysis, and finally present the analysis results in university management decision-making, then this should be the creative research of university administrators. In the construction of digital campuses, informatization promotes multiple innovations in teaching and management in vocational colleges, resulting in teaching big data, teaching big data, and data management needs. After analyzing the reading data of students’ on-campus learning system through big data, it can be concluded that the learning data of Blue Nebula from 2017.09.20 to 2017.10.10 is 8.5 more than that of Chaoxing on average. During the period of 10.01–10.10, the learning data of the two platforms increased by 15 and 7, respectively, compared with the period of 09.20–09.30.
Application Of The User Experience Lifecycle Method On Thesis Data Processing Information System And Stmik Field Work Practice Report YMI Tegal

Educational institutions really need a data processing information system in carrying out their work activities because they are seen to be more organized and directed with the support of adequate computer equipment. STMIK YMI Tegal is a computer-based high school, but at the UPT bureau of the library as the inventory and management of PKL and Thesis reports, there is no information system facility for processing data on PKL and Thesis report titles. In its management, it still uses the manual method, which is recorded in a ledger, so it feels slow and not well organized. So in this study, the author tries to create a Data Processing Information System for PKL Reports and Thesis, which is specifically to provide information on title data for PKL reports and Thesis to the academic community of STMIK YMI Tegal. The method used in this study is the User Experience Lifecycle method, which is the method proposed by Hartson and Pyla to develop user experience by focusing on usability and user experience aspects. This method is divided into four stages, namely analysis, design, prototype, and evaluation. With this PKL and Thesis Report Data Processing Information System, it is expected to be able to help the UPT Library bureau in processing PKL and Thesis report title data and make it easier for students to search for PKL or Thesis report titles online
The influence of first and second language on the acquisition of pragmatic markers in Spanish

This paper reports on an experimental study of the use of two Spanish markers of epistemic modality and evidentiality, creo que ‘I believe that’ and pienso que ‘I think that’, by native speakers, and by Dutch and German learners of Spanish. We found a clear preference for creo que among the native speakers of Spanish, but with differences between the main varieties of the language. For Dutch and German learners the preference for creo que was significantly weaker, and for beginning learners of Spanish it was significantly weaker than for advanced learners. While for the Dutch learners of Spanish this pattern reflects the preference for I think over I believe in their L1, the preference that the German-speaking learners have for creo que can be seen as evidence for a general tendency noticed in the literature, namely the interference of an L2 (in this case English) instead of the L1 (in this case German) in L3 performance (in this case Spanish).
The Role of Fiscal Policies In Financing Human Development In Iraq

Economic and social movements and changes in people's lives are linked to the development process and the consequence of the interaction. As a result of worldwide changes, the idea of development has been broadened to include more than just economic progress, making it part of the continuing process of sustainable development. Therefore, this research will study fiscal policies and their prominent role in financing human development in Iraq and the calendar effect. Their relationship is quantitative and identifies the various concepts and variables related. The findings indicate that there is a positive impact of the general budget on human development in Iraq as evidence the value of the coefficient of determination of 78%, which shows the significant role played by the budget in effect on the value of human development in Iraq guide during the period 2007-2019. On the other hand, findings from this study show that budgets' social role is heavily influenced by factors such as salaries and unemployment rates and mandatory social contributions, and the human development index. It suggests a need to continue developing the workforce's professional and personal skills.
Rectification note to “Scientific models and metalinguistic negotiation” (Theoria. An International Journal for Theory, History and Foundations of Science, 34(2), 277-295)

Rectification note to “Scientific models and metalinguistic negotiation” (Theoria. An International Journal for Theory, History and Foundations of Science, 34(2), 277-295).
Opportunities for Transforming Fundamental Physics Researchinto an Innovative Product

Currently, humanity, our entire civilization needs long–term forecasts of emergencies and systems of individualized control of the actions of people and robots (AI systems) in the event of an emergency in order to radically reduce human and material losses. This was shown by the events of this year – catastrophic in scale fires, floods, earthquakes, apparently associated with global space phenomena, and man–made disasters, including epidemics associated with the pace of economic activity – the concentration of the world's population in megacities, globalization of the economy, population mobility, etc. The article shows that only the introduction of a mass service of individualized subscriber rescue management (IUSA) of an infocommunication network with sensors developed as a result of fundamental physical studies, and its full–fledged industrial operation can be accelerated by creating the Association of Researchers of Applied Physics Problems (ARAPP).