Reviewerly/exHarmony huggingface dataset:
Use of BIM Technology in Construction Design Phase

Building Information Modelling (BIM) is a digital information technology used to transmit information involving architecture, engineering, and construction as a set of interactions in the construction industry. When BIM technology is used as a management system in communication, the delivery of information is more accurate, clear, and detailed. However, problems occur when the construction industry lacks cost in the acquisition of such technology, in addition lack of knowledge and skills to use BIM technology process in project management. Therefore, this study identifies the factors use of BIM technology, the level of absorption, and the measures to increase the users of BIM technology in construction design phase. The method used in the data collection process is the questionnaire method. The population involved in this study includes architects and engineers, with a total of 80 distinguished populations. However, only 55 sets of questionnaire forms were recovered. The respondents involved in this study were architects and engineers. The result of the data analysis obtained shows that knowledge and skills need to be improved in the process of operating BIM technology. However, small-scale organisations cannot afford to own this technology because of the high cost and the need to undergo training in managing the technology. In an effort to coordinate the policy on the use of BIM technology, CIDB provides a centre as a reference for all parties involved in the industry to know the true concept of BIM technology and to undergo courses offered related to the use of BIM technology. These findings benefit those involved in achieving a more systematic use of BIM technology in organisational management involving the construction design phase.
Grieg and Violins

Violin was Edvard Grieg’s favourite orchestral instrument. This affinity expanded to other string family instruments and a string orchestra. The article aims to characterise Grieg’s two-movement cycles of miniatures for string orchestra, emphasizing the features of their orchestration. The analysis revealed that these cycles should be considered as original and creative orchestral compositions where the composer efficiently employs the possibilities of string instruments.
Deep Learning Approach of Product Evaluation Using Comment Analysis

Abstract: Digital reviews now play a critical role in strengthening global consumer communications and influencing consumer purchasing patterns. Consumers can use e-commerce giants like Amazon, Flipchart, Snap deal, Jio and others to share their experiences and provide real insights about the performance of a product to future buyers. The classification of reviews into positive and negative sentiment is required in order to derive relevant insights from a big set of reviews. Comment Analysis is a computer programme that extracts subjective data from text. Out of Various Classification models Deep Learning Approach of Product Evaluation Using Comment Analysis is to develop a model that uses AI technologies like Deep Learning to process thousands and millions of online reviews on a product in a split second of time and rate the products on a scale of 1-5 based on the user comments We have worked on two deep learning models based on Recurrent Neural Networks (RNN) and Graph Convolution Network (GCN). Keywords: LSTN, GCN, NLTK
New Tests for High-Dimensional Linear Regression Based on Random Projection

We consider the problem of detecting the significance in high-dimensional linear models, allowing the dimension of the regression coefficient to be greater than the sample size.We propose novel test statistics for the hypothesis testing of testing the global significance of the linear model as well as the significance of part of the regression coefficients.The new tests are based on randomly projecting high-dimensional data into a space of low dimensions and then working with the classical F-test using the projected data.An appealing feature of the proposed tests is that they have a simple form and are computationally easy to implement.We derive the asymptotic local power functions of the proposed tests and compare with the existing methods for hypothesis testing in high-dimensional linear models.We also provide a sufficient condition under which our proposed tests have higher asymptotic relative efficiency.Through simulation studies, we evaluate the finite-sample performances of the proposed tests and demonstrate that it performs better than the existing tests in the models we considered.Applications to real high-dimensional gene expression data are also provided for illustration.
CURRENT ISSUES OF INCREASING EF-FICIENCY OF SAINT-PETERSBURG STATE TECHNOLOGICAL INSTITUTE (TECHNICAL UNIVERSITY) STUDENTS’ INVOLVEMENT IN THE INDEPENDENT ASSESSMENT OF QUALIFICATIONS

Currently, the government pays more atten-tion to the standards and guidelines for all education systems to ensure that vocational and higher education programmes are coor-dinated with the evolving needs of the labour market. This policy includes development of the National qualifications system and of the independent assessment of qualifications, which could be served for external evalua-tion of the quality of higher education. The paper represents indicators of SPbGTI(TU) students' involvement in the procedures of independent qualifications assessment, re-sults of students' awareness about the Na-tional Qualifications System and about the infrastructure, which carries out this as-sessment, as well as results of the study of students' motives for voluntary participation in the procedures of the independent qualifi-cations assessment. The paper also offers suggestions about improving students’ in-volvement in the independent assessment of qualifications.
LBS as Vectors of Influence

Abstract. Due to their technical capabilities and use-cases, LBS can impose autonomy constraints on individuals, both through direct interaction and via indirect means. This essay outlines four main interaction characteristics that constitute LBS as a vector of influence and contextualizes them by mapping them onto a pragmatic framework of autonomy.
THEORETICAL ASPECTS OF DIGITAL TRANSFORMATION OF PROFESSIONAL TRAINING OF FUTURE SPECIALISTS

Of particular importance in the system of higher professional education is the provision of the educational process with appropriate information tools, methods and curricula, so that the educational institution, teacher and teacher training system meets modern global and national challenges and provides modern support in digital technologies, develops and forms digital competence. The purpose of the study is to reveal the theoretical aspects of digitalization of professional training of future specialists. Research methods applied: theoretical: analysis, systematization and generalization of pedagogical and psychological research. The professional responsibilities of teachers in the spread of digital technologies are expressed not only in the willingness to use them in the educational process, but also in the manifestation of competencies such as willingness to cooperate in the professional field, communication skills and the desire for continuous development in the digital environment. Digital resources include the ability of teachers to make their competent choice, creation and modification, as well as their exchange in accordance with the objectives of learning. Teaching involves the teacherʼs ability to create, plan and implement digital technologies at different stages of learning, it is important that the center of the educational process was directly the student, and the teacher himself acted mainly as a tutor. Student assessment involves the use of digital tools to implement existing methods of student assessment and provide them with feedback and analysis of their activity in the digital environment. Expanding the rights, opportunities and independence of students in the educational process involves the use of digital technologies by teachers to build an individual trajectory of students, as well as eliminating differentiation in studentsʼ access to appropriate technical devices.
Features of positioning of German university libraries on official websites

The problem of space music as a special cultural phenomenon requires scientific understanding. The purpose of the article is to study the features of the emergence and development of space rock as a specific trend in modern popular culture using the history of the “HAWKWIND” group as an example. The chronology of sound recordings of the “HAWKWIND” group as one of the founders of the “Space Rock Music” is established. The role of Dave Broсk, Bob Kalvert and other group participants in the creation of creative music programs is noted. It is proved that these musicians are the principles of the historical phenomenon, which received popularity as “Space Rock”. For the first time, the analysis of “HAWKWIND” sound documents through the prism of the history of space music development has been proposed.
Model of adaptive management of formation of digital competence basics of primary school students

The study is devoted to the issues of modeling the processes of adaptive management of the formation of digital competence of students in the process of obtaining primary education. The key aspects of the theoretical foundations of management of socio-pedagogical systems are revealed. Especially, the principles and approaches to management in general and adaptive in particular are described. It is described, that the essence of management of social and pedagogical systems consists in purposeful influences on the managed subsystem for its ordering. It is determined, that the main task of such management is to ensure the purposefulness, consistency of operation and development of the managed subsystem. The essence of adaptive management is specified, which, taking into account the main characteristics of classical management, is based on the processes of dialogic adaptation of managed and managing subsystems. The characteristics of the key definitions of the research are described, and the structure of the model of adaptive management of the process of formation of digital competence of students in the process of obtaining primary education is presented. The model consists of interconnected structural components, which together give an idea of the process of forming digital competence of students to ensure the success of their lives. The model was built on the basis of system and activity approaches using certain stages of the modeling process. The essence of four blocks of the model is described: target, theoretical, content-technological; and final-reflexive. It is noted, that the pedagogy of partnership is a key component of the formula of the New Ukrainian School and a component of the built model of adaptive management of the formation of digital competence of students in the process of obtaining primary education
Teaching Design of English Picture Book for Primary Schools Based on Performance Culture Teaching Method-Taking the Story Time in Unit 1 of the Third Grade of the PEP Version as an Example

&lt;p&gt;The performance culture teaching method was first proposed by the American Sinologist Wu Weike. It is a teaching method to learn a second language through the comprehension and practice of the target language. It focuses on culture and practice. The learner presents the story in a rehearsal manner in the context of the target language culture. Picture book teaching is a popular teaching method for primary school English teachers at this stage. Its novel feature of moving from outside class to classroom makes it an indispensable teaching method in primary school English teaching. This article takes the PEP version of the third grade English textbook as an example for teaching design and integrates the performance culture teaching method with the picture book teaching in the primary school English classroom teaching. The focus of research in teaching design is teaching implementation, that is, the application of performance methods in primary school English classrooms. This teaching design combines picture book teaching and performance culture teaching methods to promote primary school English teaching.&lt;/p&gt;
Sterility Test of Syringes As A Pharmaceutical Preparation That Obtained From Pasar Pramuka

Syringes are one of the pharmaceutical preparations that are in high demand. In healthcare institutions, syringes are used to aid in patient care and examination. Pharmaceutical preparations, such as various syringes, are widely available in the Pasar Pramuka. Syringes must be free from microbes and used syringes should not be reused. Microbiological sterility tests can be performed on a syringe to determine whether it is sterile or not. The purpose of the study is to test the sterility of syringes obtained from the Pasar Pramuka. A random sample of a syringe is being used in the study as an experimental method. The syringes were isolated and incubated for 14 days in Fluid Thioglycollate Medium (FTM) and Trypticase Soy Broth (TSB) at 30-35 oC and 20-25 oC, respectively, with frequent observations. If FTM and TSB media were turbid, then isolated into selective media based on their microbe as controls, namely Clostridium sporogenes ATCC 19404, Pseudomonas aeruginosa ATCC 9027, Staphylococcus aureus ATCC 6538, Escherichia coli ATCC 25922, Escherichia coli ATCC 8739, Bacillus subtilis ATCC 6633, Salmonella typhi. The results showed that the B syringe was turbid on FTM media and did not contain pathogenic microbes after being identified on selective media, as in controls. The A and C syringes on TSB media were turbid, and after identification on selective media, Candida albicans and Aspergillus brasiliensis were found. In conclusion, the A, B, and C syringes are not steril.
PERBANDINGAN METODE SEASONAL ARIMA DAN EXTREME LEARNING MACHINE PADA PERAMALAN JUMLAH WISATAWAN MANCANEGARA KE BALI

Bali Island of the Gods is one of the wealth of very popular tourist destinations and has the highest number of foreign tourists in Indonesia. It is very necessary to do more in-depth learning related to the projections or forecasting of foreign tourist visits to Bali at a certain period of time. Forecasting analysis used is to compare two methods, namely the Seasonal ARIMA method (SARIMA) and Extreme Learning Machine (ELM). The SARIMA method is a statistical method commonly used in forecasting time series data that contains seasonality and has good accuracy. While the ELM method is a new learning method of artificial neural networks that has fast learning speed and good accuracy. The results obtained indicate that the Seasonal ARIMA method is a better method used to predict the number of tourists to Bali in this case, because it has a smaller forecasting MAPE value of 4.97%. While the ELM method has a forecasting MAPE value of 7.62%.
WhatsApp Emoji in Business Interactions: The Case of Malaysian and Iranian Interactions

WhatsApp emoji has been widely used by users all over the world especially entrepreneurs during their business interactions. In these interactions, WhatsApp emoji has been discovered to be intriguing. Emoji, among other things, were used to replace non-verbal expressions in face-to-face interactions especially during business communications. However, studies related to the usage of WhatsApp emoji in business interactions were found to be limited, particularly in the Malaysian setting. Thus, the purpose of this research was to examine the use of WhatsApp emoji in business communications between a Malaysian entrepreneur and three Iranian counterparts. Content Analysis was used to interpret the messages in the business conversations, and the data was analysed using De Vito's Five-Stage Model of Conversation. The findings revealed that WhatsApp emoji performed a range of functions in business interactions in a BELF setting. In short, WhatsApp has clearly added some useful and valuable features for a variety of uses, including business communications.
Daily Cryptocurrency Returns Forecasting and Trading via Machine Learning

We execute a comparative analysis of machine learning models for the time-series forecasting of the sign of next-day cryptocurrency returns. We begin by compiling a proprietary dataset that encompasses a wide array of potential cryptocurrency valuation factors (price trends, liquidity, volatility, network, production, investor attention), subsequently identifying and evaluating the most significant factors. We apply eight machine learning models to the dataset, utilizing them as classifiers to predict the sign of next day price returns for the three largest cryptocurrencies by market capitalization: bitcoin, ethereum, and ripple. We show that the most significant valuation factors for cryptocurrency returns are price trend variables, seven and thirty-day reversal, to be specific. We conclude that support vector machines result in the most accurate classifications for all three cryptocurrencies. Additionally, we find that boosted models like AdaBoost and XGBoost have the poorest classification accuracy. At length, we construct a probability-based trading strategy that secures either a daily long or short position on one of the three examined cryptocurrencies. Ultimately, the strategy yields a Sharpe of 2.8 and a cumulative log return of 3.72. On average, the strategy’s log returns outperformed standalone investments in all three cryptocurrencies by a factor of 5.64, and Sharpe ratios more than threefold.
Strengthening Human Resources as Lecturers Through the E-Learning Learning Method

Introduction: The concept of e-learning is an alternative for students who are unable to attend faceto-face lectures. The use of e-learning as an alternative learning is increasing in line with technologicaldevelopments. Aim: This study applies e-learning learning methods to strengthen educational humanresources as lecturers using Computer-based Multimedia Communication (CMC). Method: Thisresearch is a pre-experimental study. The research was conducted in STIKes Yarsi Mataram, Indonesiain 2020. The measuring instrument used a questionnaire. The study population was all students, witha total sample of 81 students. The independent variables include a method of learning. The dependentvariable in this study was knowledge. The analysis used was univariate and bivariate using paired t-test.Result and Discussion: frequency of e-learning based on CMC in the experimental group, namely 63%in the evaluation and 80% in the implementation process. While in the control group using conventionalmethods, 50% of the intervention and 23% of the implementation. Conclusion: Improving studentlearning outcomes in the community nursing process by using the CMC learning method is moreeffective than using conventional methods.
Review of Machine Learning Applications and Datasets in Classification of Acute Leukemia

Cancer is an extremely heterogenous disease. Leukemia is a cancer of the white blood cells and some other cell types. Diagnosing leukemia is laborious in a multitude of areas including heamatology. Machine Learning (ML) is the branch of Artificial Intelligence. There is an emerging trend in ML models for data classification. This review aimed to describe the literature of ML in the classification of datasets for acute leukemia. In addition to describing the existing literature, this work aims to identify different sources of publicly available data that could be utilised for research and development of intelligent machine learning applications for classification. To best of the knowledge there is no such work that contributes such information to the research community.
The Dynamics between External Public Debt and Foreign Exchange Reserve of Ethiopia Economy: 1981 to 2019

This paper empirically examined the short-run and long-run dynamics among external public debt and foreign exchange reserve of Ethiopia. The two variables are playing a pivotal role in the growth and development of nations economy. To achieve the objective the study took 39 years data from the year 1981 to 2019 from National bank of Ethiopia and World Bank data sets. The study used descriptive analysis and empirical methods of analysis. The Autoregressive Distributed Lag model with error correction models were employed after checking the possible assumptions of our economic series. The results of ADF test statistics confirms our economic series are stationary at level and first difference forms. Bounds co-integration test suggests one co-integrating relationship between the variables taking foreign exchange reserve as the outcome variable. According to the descriptive method of analysis, on average, in Ethiopia the trend for service sector indicated that an ever improvement of the sector throughout the periods and supplementing the notion of change from agriculture base to service sector. In addition, the trade tariff rate of Ethiopian economy is indicating a downward movement and this in turn justifies the relative openness of the economy to the globe. In the same manner the financial development indicator of the nation is rising, which assures relative improvement in the financial sector. On the other hand, according to the Autoregressive Distributed Lag model in the short -run average trade tariff rate, share of manufacturing sector from the GDP, and lagged value of EPD itself predicts the external public debt significant at least at less than 10 percent level of significance. Moreover, the error correction model revealed that in the long-run, financial development indicator, debt service payment, and average trade tariff rate were predicting the stock of foreign exchange reserve for Ethiopian economy. The result also indicates that in the short-run, only the share of agriculture and service sectors are significantly predicting the variations of the stock of foreign exchange reserve, ceteris paribus. Finally, the concerned body specially the government of Ethiopia should limit or reduce the amount of external debt inflows that has an adverse effect on debt service payment, and recheck the budget sources for financing different projects especially manufacturing industries rather than highly basing on external sources in the form of external public debt . More importantly, the government should enhance the value of export potential, among others.
Reducing the need for bounding box annotations in Object Detection using Image Classification data

We address the problem of training Object Detection models using significantly less bounding box annotated images. For that, we take advantage of cheaper and more abundant image classification data. Our proposal consists in automatically generating artificial detection samples, with no need of expensive detection level supervision, using images with classification labels only. We also detail a pretraining initialization strategy for detection architectures using these artificially synthesized samples, before finetuning on real detection data, and experimentally show how this consistently leads to more data efficient models. With the proposed approach, we were able to effectively use only classification data to improve results on the harder and more supervision hungry object detection problem. We achieve results equivalent to those of the full data scenario using only a small fraction of the original detection data for Face, Bird, and Car detection.