Reviewerly/exHarmony huggingface dataset:
ENT 530 Social Media Portfolio: Bawal Saudia By Hana / Nur Farhana Ruslan

This Social Media Portfolio is a full description and detailed information regarding the small online business which is Saudia by Hana. Bawal Saudia by Hana has been established and developed through social media platform particularly Facebook where Facebook Page play a crucial site for developing and engaging this business. The important effort including the official registration for small businesses has been taken through the GoEcommerce registration online platform. This is considered as the first and necessary step before beginning any activities in the entrepreneurship industry. Through this official registration, a business undoubtedly being legally certified. A brief business background and introduction have been presented in this portfolio where Bawal Saudia by Hana is officially owned by Farhana Ruslan. Bawal Saudia by Hana promoted the bawal scarf with a wellrecognized brand, Saudia, which is originated from Bawal Saudia HQ or Saudia Scarf HQ. All the business activities include promoting, advertising, posting, product launching, teaser, and customer engagement has been done on Bawal Saudia by Hana Facebook page. Bawal Saudia by Hana’s mission is to ensure the satisfying among every customer which assist them in solving the problem they encounter in their everyday life while the vision is focusing on to serve a high-quality product’s material for customers value. They serve and provide a high-quality material of hijab at such an affordable price. This Bawal Saudia is well-known for its great quality of hijab that which has made many customers satisfied and pleasant with it. It is made of high-quality soft cotton material that provided many advantages to hijabis and helps them to overcome their everyday problem concerning their hijab. With this opportunity and benefits provided from Bawal Saudia by Hana, hijabis out there able to look pretty and fashionable as the Saudia scarf comes with a unique design particularly its fringe finishing makes it different and rare from other scarves. The customer also is able to look stylish and beautiful without requiring to spend enough money to purchase such a high branded scarf at the market out there. Every detailed description with respect to the product, promotion, and service information has been created and distributed through the strategized method of copywriting on the Bawal Saudia by Hana Facebook page. This includes the teaser, hard-copywriting, and soft copywriting with the intention to keep a good engagement with the customer, and delivering information and guidance regarding their hijab.
Development of creative competence of future primary school teachers based on art-pedagogical technology

The article examines the problem of developing the creative competence offuture teachers on the basis of an art-pedagogical approach. The relevance of the study is due to the fact that in the context of reforming domestic pedagogical education, risks of ignoring the creative component of pedagogical activity are likely. The subject of the research is art-pedagogical technology and its possibilities in terms of developing the creative competence offuture teachers. The novelty of the research lies in the development and implementation of a model of art-pedagogical technology. The experience of testing art-pedagogical technology in the educational process of the university allows us to conclude that it has a positive effect on the motivation of creativity and readiness to solve complex educational problems.
The Analysis of Students Pronunciation Error

This research is conducted to analysis of students’ pronunciation error of English silent letters. The problems should be answered in this research are: How is the students’ pronunciation ability of silent letters in English words and what are the students’ common errors in pronouncing English silent letters. The subject of the research is 40 students of Economic department at UMN Medan. The objects of this research are the students’ ability in pronouncing English silent letter and the students’ common error in pronouncing English silent letter. To collect the data, the writer applied technique the test. Then, the data is analyzed in descriptive qualitative method.The result of this research shows that mean score of students’ ability in pronouncing English silent letter is 61.05% that means in fair category. There are 20 kinds of silent letter in English and he writer get 14 of the the Students’ common error of silent letter
Λ-Symsym: An Interactive Tool for Playing with Involutions and Types

We present the web portal Λ-symsym, available at http://158.110.146.197:31780/automata/, for experimenting with game semantics of λ^!-calculus, and its normalizing elementary sub-calculus, the λ^{EAL}-calculus. The λ^!-calculus is a generalization of the λ-calculus obtained by introducing a modal operator !, giving rise to a pattern β-reduction. Its sub-calculus corresponds to an applicatively closed class of terms normalizing in an elementary number of steps, in which all elementary functions can be encoded. The game model which we consider is the Geometry of Interaction model I introduced by Abramsky to study reversible computations, consisting of partial involutions over a very simple language of moves.Given a λ^!- or a λ^{EAL}-term, M, Λ-symsym provides: - an abstraction algorithm A^!, for compiling M into a term, A^!(M), of the linear combinatory logic CL^{!}, or the normalizing combinatory logic CL^{EAL}; - an interpretation algorithm [[ ]]^I yielding a specification of the partial involution [[A^!(M)]]^I in the model I; - an algorithm, I2T, for synthesizing from [[A^!(M)]]^I a type, I2T([[A^!(M)]]^I), in a multimodal, intersection type assignment discipline, ⊢_!. - an algorithm, T2I, for synthesizing a specification of a partial involution from a type in ⊢_!, which is an inverse to the former. We conjecture that ⊢_! M : I2T([[A^!(M)]]^I). Λ-symsym permits to investigate experimentally the fine structure of I, and hence the game semantics of the λ^!- and λ^{EAL}-calculi. For instance, we can easily verify that the model I is a λ^!-algebra in the case of strictly linear λ-terms, by checking all the necessary equations, and find counterexamples in the general case.We make this tool available for readers interested to play with games (-semantics). The paper builds on earlier work by the authors, the type system being an improvement.
Personalised exercise recognition towards improved self-management of musculoskeletal disorders.

Musculoskeletal Disorders (MSD) have been the primary contributor to the global disease burden, with increased years lived with disability. Such chronic conditions require self-management, typically in the form of maintaining an active lifestyle while adhering to prescribed exercises. Today, exercise monitoring in fitness applications wholly relies on user input. Effective digital intervention for self-managing MSD should be capable of monitoring, recognising and assessing performance quality of exercises in real-time. Exercise Recognition (ExRec) is the machine learning problem that investigates the automation of exercise monitoring. Multiple challenges arise when implementing high performing ExRec algorithms for a wide range of exercises performed by people from different demographics. In this thesis, we explore three personalisation challenges. Different sensor combinations can be used to capture exercises, to improve usability and deployability in restricted settings. Accordingly, a recognition algorithm should be adaptable to different sensor combinations. To address this challenge, we investigate the best feature learners for individual sensors, and effective fusion methods that minimise the need for data and very deep architectures. We implement a modular hybrid attention fusion architecture that emphasises significant features and understates noisy features from multiple sensors for each exercise. Persons perform exercises differently when not supervised; they incorporate personal rhythms and nuances. Accordingly, a recognition algorithm should be able to adapt to different persons. To address the personalised recognition challenge, we investigate how to adapt learned models to new, unseen persons. Key to achieving effective personalisation is the ability to personalise with few data instances. Accordingly, we bring together personalisation methods and advances in meta-learning to introduce personalised meta-learning methodology. The resulting personalised meta-learners are learning to adapt to new end-users with only few data instances. It is infeasible to design algorithms to recognise all expected exercises a physiotherapist would prescribe. Accordingly, the ability to integrate new exercises after deployment is another challenge in ExRec. The challenge of adapting to unseen exercises is known as open-ended recognition. We extend the personalised meta-learning methodology to the open-ended domain, such that an end-user can introduce a new exercise to the model with only a few data instances. Finally, we address the lack of publicly available data and collaborate with health science researchers to curate a heterogeneous multi-modal physiotherapy exercise dataset, MEx. We conduct comprehensive evaluations of the proposed methods using MEx to demonstrate that our methods successfully address the three ExRec challenges. We also show that our contributions are not restricted to the domain of ExRec, but are applicable in a wide range of activity recognition tasks by extending the evaluation to other human activity recognition domains.
Nowcasting Indonesia’s GDP Growth Using Machine Learning Algorithms

GDP is very important to be monitored in real time because of its usefulness for policy making. We built and compared the ML models to forecast real-time Indonesia's GDP growth. We used 18 variables that consist a number of quarterly macroeconomic and financial market statistics. We have evaluated the performance of six popular ML algorithms, such as Random Forest, LASSO, Ridge, Elastic Net, Neural Networks, and Support Vector Machines, in doing real-time forecast on GDP growth from 2013:Q3 to 2019:Q4 period. We used the RMSE, MAD, and Pearson correlation coefficient as measurements of forecast accuracy. The results showed that the performance of all these models outperformed AR (1) benchmark. The individual model that showed the best performance is random forest. To gain more accurate forecast result, we run forecast combination using equal weighting and lasso regression. The best model was obtained from forecast combination using lasso regression with selected ML models, which are Random Forest, Ridge, Support Vector Machine, and Neural Network.
초등 영재 학생 과학 독서록에서의 질문유형 분석

The purpose of this study was to explore the question types of reading process in science reading instruction, and find effective education direction. For this purpose, elementary school gifted students’ science book reports were analyzed in focusing questions. 60 students in Seoul National University of Education Gifted Education Center submitted the book reports after reading science books. Researchers selected 2 books and 120 book reports which were the most read. In the format of book report, students make questions about the book, and the questions were categorized in 3 types (convergent question, productive question, evaluative question). Also the book reports were evaluated in 4 criteria (contents understanding, depth of thinking, logicality, creativity), and divided in good, average, poor. As a result, productive questions were the most and it was the same result in the group of good, average, poor. Moreover, the higher score group in evaluating the book reports, the more ratio of productive question. In contrast, the lower score group in evaluating the book reports, the less ratio of productive question. It shows that the question types are related to students’ science abilities, and will be base to improve making better questions and develop effective reading education.
Individual Factors of Employee Engagement in Organizational Performance

An organization’s success and profitability depend upon the performance of its employees. Business leaders know that a high-performing workforce is essential for the achievement of strategic business goals. The objective of this study is to identify the individual factors of employee engagement in Organization performance. In this study, “Employee Communication, Employee Development, Reward & Recognition, and Leadership” are used as the independent variables and “Employee Engagement in Organizational Performance” is used as a dependent variable. The target population consists of workers in SMEs relating to the Colombo district (This is the commercial capital and largest city of Sri Lanka by population) in 2019 year. The current study has used Stratified sampling method for selecting 249 employees to collect the data from the survey by representing all management levels. This study has used Pearson correlation analysis to identify the relationships between independent and dependent variable. According to the analysis results, the study concludes the findings as follows; there is a significant positive relationship between employee communication and employee engagement in organization performance, there is a significant positive relationship between employee development and employee engagement in organization performance, there is a significant positive relationship between reward/recognition and employee engagement in organization performance and there is a significant positive relationship between leadership and employee engagement in organization performance.
Network Feature Extraction for Regional Economic Development and Financial Agglomeration Analysis

The feature components extracted by the ISA neural network have good mutual independence and good translation invariance, scale invariance and rotation invariance. It can better acquire hidden internal feature information and is successfully applied in the field of human behavior recognition. Through the optimization process, the ISA neural network can complete the learning phase to train the weight parameters. This paper analyzes regional economic development and financial agglomeration using machine learning algorithms and deep learning, and uses a spatial econometric model to empirically study the differences between financial industry agglomeration and regional economic development. This paper measures the degree offinancial agglomeration and analyzes the degree of financial agglomeration of China’s regional economy and integrates the empirical results. The paper provides a certain reference value for the development of the regional economy.Keywords: Deep Learning; Feature Extraction; Deep Network; Financial agglomerationCite AsY. Zhang, Q. Qiang, W. Zhu, Network Feature Extraction for Regional Economic Development and Financial Agglomeration Analysis, Engineering Intelligent Systems, vol. 27 no. 2, pp. 71-78, 2019.
POSTPHENOMENOLOGY OF FRP MATERIAL ON GRAND BANKS YACHTS PRODUCTION SHIP DESIGN

The use of Fiberglass Reinforcement Plastic (FRP) as the basic material for forming ships does not necessarily change the appearance of the fishing yacht design produced by Grand Banks Yachts (GBY), which has been famous for a long time with its classic style. The phenomenon of GBY product models with classic characteristics is interpreted as beautiful by special users with all their interpretations of beauty, thus attracting a lot of interest. The research problem in disclosing the concept of design sustainability through GBY's FRP technology is interesting to examine with the structuralist functionalism paradigm, where FRP elements have characteristics and properties that can facilitate and even replace the role of humans in their use. The case study method used in this study explains that the FRP material on the GBY vessel can be interpreted as a social phenomenon in a posthumanist context, assisted by Don Ihde's post-phenomenological theory, which dissects the relationship between humans versus this technology. Explain the research results in the form of individual and collective interpretations as an aesthetic expression of a GBY product concept which is a posthumanist phenomenon. The research objective as the end result is to find a posthumanist concept in FRP material technology in aesthetic interpretations of GBY products.
TECHNOLOGY OF MIXED TRAINING OF FUTURE MECHANICAL ENGINEERS IN THE CONDITIONS OF UNPC «ALL-UKRAINIAN SCIENTIFIC AND EDUCATIONAL CONSORTIUM»

The article discusses the need to transform the traditional professional training of a future mechanical engineer, which is associated with a number of contradictions due to new requirements for a graduate of an agricultural university. The issues of improving the quality of the fundamental and practical component are actualized, which the professional activity of a specialist in modern high-tech production needs - the development, operation, maintenance and management of new equipment, technologies and technical systems. It is proved that a powerful means of eliminating these contradictions is the development of a strategy of agricultural educational institutions for the integration of science, education and production, focused on the current state of the agro-industrial complex. The scientific and educational industrial complex is considered as a concept of the mechanism for the transition of agro-industrial production to an innovative development model. Substantiated is the author's student-centered technology of blended learning of future mechanical engineers in the conditions of the Educational-scientific industrial complex USEC «Ukrainian scientific-educational consortium». It has been proven that in the process of training mechanical engineers in the conditions of scientific and educational industrial complexes, the technology of blended learning with elements of dual education, based on the integration of traditional classroom and distance forms, using the best capabilities of each, will be effective. The analysis of the existing practice of using distance and blended learning technologies in the process of training specialists is carried out, the psychological and pedagogical conditions for the design of student-centered education based on the blended learning technology are theoretically substantiated, a model for the design of blended learning technology is developed, the principles of selection of subject-specific information in the mathematical training of specialists are determined, student-centered technology of blended learning of future mechanical engineers (on the example of the course "Higher Mathematics"), prepared information resources and teaching materials are described.
Horn Pack [1.37]

Hello Mod Lovers First You Love The Horn Select From Our Video And Go To Mod Folder And When You Enter The Game When You Want To Change It Works ...
Identification and Characterization of the Corticotropin‐releasing Factor (CRF) System in Atlantic Salmon (<i>Salmo salar</i>)

In contrast to most other teleosts studied to date, salmonids has undergone four whole genome duplications (WGD), commonly referred to as the Ss4R (salmonids‐specific 4 th vertebrate WGD) event. Large genomic rearrangements and the restoring of the disomic chromosome inheritance in the ancient polyploidy have been crucial for the post Ss4R re‐diplodization process, leading to possible divergent functions of duplicated genes. This evolutionary genome duplication, together with the available genome sequence information for Atlantic salmon ( Salmo salar ), provide a unique opportunity to investigate the pivotal roles of gene diversity and functionality. When facing variable external or internal adverse effects beyond their homeostatic state, teleosts engage a stress response through the Hypothalamic‐Pituitary–Interrenal gland (HPI) axis to restore the compromised physiological steady state and enable the animal to overcome the threat. Corticotropin‐releasing factor (CRF), CRF‐binding proteins (CRFBPs) and CRF receptors (CRFRs) are commonly used as markers for stress responsiveness. This system has been poorly explored in Atlantic salmon, thus, in this study, we aim to investigate all the CRF system players. As for other salmonids, the Ss4R event induced the tetradiploidization in the Atlantic salmon genome leading to the several duplicated genes (paralogues) in these species. We currently investigate the crf , crfbp and crfr genes to explore the roles of the different paralogues. In silico analysis show that the Atlantic salmon genome has four crf paralogue genes distributed among chromosome ( Chr)Ssa03 , ChrSsa14, ChrSsa19 and ChrSsa 29, two crfbp genes located in the ChrSsa01 and ChrSs11 , two crf r1 paralogue genes placed in the ChrSsa03 and ChrSsa06 and two crfr2 paralogue genes in ChrSsa03 and ChrSsa14 . To evaluate their function in the HPI stress response axis, we have analysed the mRNA expression of the different transcripts in different brain regions of Atlantic salmon post‐smolts. Our initial data shows that all crf transcripts are present in the hypothalamus and pituitary. However, further analysis are needed and particularly the characterization of these several transcripts under control and stressed conditions. Support or Funding Information Funded by the Research Council of Norway (NFR 267626 LeuSENSE). This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
The Use of Kahoot Application in English Language Teaching During Covid-19 Pandemic Era at SMP IT Al Huda Wonogiri

The purpose of this research is to show a better understanding of the use of Kahoot application for learning during the pandemic based on the opinion of IT Junior High School teacher Al-Huda Wonogiri. This research is a qualitative descriptive research using phenomenology approach. Data from this research was obtained from the interview method with two English teachers of SMP IT Al-Huda Wonogiri as a data source. Data analysis techniques from this research use interactive data analysis techniques aimed at producing research data that is accurate, simple, and easy to understand and can focus with research objectives and answer research questions. The results of this study showed that the use of Kahoot application during the pandemic makes students enthusiastic to learn because the display of Kahoot application is interesting to use, in addition students become easier to learn lessons because the use of Kahoot application is easy to access during learning and outside learning, and make it easier for students to understand the lessons delivered because the material contained in the Kahoot application is simple and easy to learn.
Artificial neural networks in the problem of determining the position and size of the solar disk in wide-angle photographs of the sky

&amp;lt;p&amp;gt;Total cloud score is a characteristic of weather conditions. At the moment, there are algorithms that automatically calculate cloudiness based on a photograph of the sky These algorithms do not know how to find the solar disk, so their work is not absolutely accurate.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;To create an algorithm that solves this data, the data used, obtained as a result of sea research voyages, is used, which is marked up for training the neural network.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;As a result of the work, an algorithm was obtained based on neural networks, based on a photograph of the sky, in order to determine the size and position of the solar disk, other algorithms can be used to work with images of the visible hemisphere of the sky.&amp;lt;/p&amp;gt;
LibGuides: Professional Development for Organizational Effectiveness: Working From Home

This guide was developed by the Organizational Effectiveness Committee to provide ongoing access to professional development opportunities for the Foley Library's staff and faculty members. Resource for distance work.