Reviewerly/exHarmony huggingface dataset:
Financial Development and Economic Growth in Kenya: Evidence from the Asymmetric Autoregressive Distributive Lag

Appropriate changes in financial development are largely known to cause growth. Inflation, gross capital formation and government expenditure, believably, succinctly controls the effects and causes long term growth. This paper analyzed this effects for Kenya paying exceptional attention on their asymmetric effects. The most reliable and important results supported that positive asymmetries of financial development increases long run growth unlike the negative with reducing and weak effects. However, in case of financial dynamics and instabilities, economic growth responds negatively with a steep slump to shocks by declining financial development as positive gross capital formation shocks seems to plausibly control such nonlinear dynamics and positively causing growth. Also, sustainable inflation and prudent state expenditure spurs long term growth. Since this growth finance relationship supports the supply-leading hypothesis, there is need for specific financial development policies which would alongside support sustainable inflation and prudent expenditure if they are to spur real growth. Moreover, the financial risk managers are required to robustly prepare against the negative shocks by finance that have greater degenerating effects than by upturn from the positive shock.
국가 R&D 특허성과의 기술융합 네트워크 분석

Purpose The purpose of this study is to analyze the changes in the technology convergence network of national R&D patent performance and the differences in technology convergence research trends between independent R&D and collaborative R&D.Methods Co-occurrence networks have been established in which multiple International Patent Classification (IPC) codes appear per patent in 2014 and 2017. Then, network analysis methods and QAP (Quadratic Assignment Procedure) analysis methods have been used in this study.Results As a result, this study shows that the degree of linkage between technologies related to national R&D projects has increased over time. The main fields of technology convergence research have been changed to ICT fields such as digital and data (G06Q, G06F) and bio fields such as food (A23L) and cosmetics (A61Q). The Ministry of Agriculture, Food and Rural Affairs actively conducts convergence research by introducing new technologies such as ICT. The Ministry of Health and Welfare actively conducts convergence research in the field of bio-health.Conclusion This study showed the changes and characteristics of technology networks of convergence R&D and collaborative R&D. The results of this study are expected to be used as a guideline for decision making in the government''s R&D policies.
Generalized Hamming weights of toric codes over hypersimplices and squarefree affine evaluation codes

Let $ \mathbb{F}_{q} $ be a finite field with $ q $ elements, where $ q $ is a power of a prime $ p $. A polynomial over $ \mathbb{F}_{q} $ is monomially squarefree if all its monomials are squarefree. In this paper, we determine an upper bound on the number of common zeroes of any set of $ r $ linearly independent monomially squarefree polynomials of $ \mathbb{F}_{q}[t_{1}, t_{2}, \dots, t_{s}] $ in the affine torus $ T = (\mathbb{F}_{q}^{*})^{s} $ under certain conditions on $ r $, $ s $ and the degree of these polynomials. Applying the results, we obtain the generalized Hamming weights of toric codes over hypersimplices and squarefree affine evaluation codes, as defined in [14].
Introduction Of Electronic Educational Technologies In The Educational Process Of Russian Universities

The usual educational routine of modern students, who are representatives of the information generation, is closely connected with electronic educational programs and courses, textbooks, tasks, projects.The process of professional training at the University shows a tendency to disappear the line between traditional education and distance education, which is explained by the wide popularity of the internet among students in the process of studying certain disciplines.The rapid development of online technologies has served as a catalyst for the emergence and spread of information educational technologies.The use of modern educational information and communication technologies gives the teacher a wide opportunity to convey educational material simultaneously to different categories of students -with different levels of initial training, with different perception speeds and sometimes with different attitudes to education at the University.This dramatically reduces the number of underperforming students, motivates them to study, makes learning more effective, raises it to the proper level, and, accordingly, increases the rating of the University.The authors emphasize the possibility of attracting foreign students to Russian universities through digitalization of the learning process, which will lead to an increase in the level of efficiency and effectiveness of the training process.In addition, the authors consider an important advantage of digital learning to be the ability to attract highly qualified foreign and nonresident specialists from different fields of knowledge who broadcast their content to students via a media platform.
Covid-19 News Clustering using MCMC-Based Learing of finite EMSD Mixture Models

&#x0D; &#x0D; &#x0D; With the growth of social media information on the Web, performing clustering on different types of data is a challenging task.Statistical approaches are widely used to tackle this task. Among the successful statistical approaches, finite mixture models have received a lot attention thanks to their flexibility. There are already many finite mixture models to cope with this task, but the Exponential Multinomial Scaled Dirichlet Distributions (EMSD) has recently shown to attain higher accuracy compared to other state-of-the-art generative models for count data clustering. Thus, in this paper, we present a Bayesian learning method based on Markov Chain Monte Carlo and Metropolis-Hastings algorithm for learning this model parameters. This proposed method is validated via extensive simulations and comparison with multinomial based mixture models.&#x0D; &#x0D; &#x0D;
Pragmatic Perspectives of Hofstede’s Organizational Dimensions in the Context of ICT-based Culture: Evidence from Public Universities in Pakistan

The present study aimed at analysis of dimensions of organizational culture of universities in Baluchistan. The study was carried out using quantitative research methodology with survey method of research and data collection. A total of n= 126 students, faculty members and administrative staff members (48 students, 48 faculty members and 30 administrative staff members) participated in this study. The sample was drawn through a multi-stage sampling design. Data was collected through close-ended, self-reported five-option Likert scale type questionnaire adopted with minor modifications from Zeqiri and Alija (2016). Analysis of collected data was carried out through SPSS V 24. Samples were contacted through consent letters and emails. Allpossible ways of legal and ethical considerations were part of the study. The analysis of data showed that the organisational culture of universities is a combination of Hofstede’s proposed dimensions of organizational culture.Universities tend to be effective and sustainable in their approaches but this is not so accros the country in the context of higher education teaching and non-teaching faculty members. Organizational culture of universities have inexperience dominance and the culture has openness towards newcomers. Rigidness towards deadlines is also an attribute of universities’ organizational culture, but there are few relaxations and comforts in working enviornments as well. Universities are contributing in a positive way towards society andhave realistice and pragmatic approach towards teaching and reearch. This study recommends a valueable consideration of employees’ personal needs and problems. The study also suggests that middle managers (Deans, Head of Departments) should be trained in human pschychology and human resources management.
Product Promotion Prediction Model Based on Evaluation Information

This paper mainly studies the impact of evaluation information on e-commerce platform on the future of products. Through natural language processing and rating, an evaluation model based on user rating and evaluation is defined to measure product quality. Among them, evaluations are differentiated: review sentiment coefficient (R) and review length (L).The evaluation model is:D=0.3*S+0.7*( 0.3*L+0.7*R). In order to predict the future reputation of products, based on the above evaluation model, time series is used to rank the products studied. Each customer purchases the product through Markov chain model, so as to predict the probability of future word-of-mouth spread of the product. Use TOPSIS method to select monthly sales, stars and comment sentiment coefficient as indicators. The comprehensive measurement method based on text and score is determined to predict whether the product is successfully promoted.
Dual Path Multi-Modal High-Order Features for Textual Content based Visual Question Answering

As a typical cross-modal problem, visual question answering (VQA) has received increasing attention from the communities of computer vision and natural language processing. Reading and reasoning about texts and visual contents in the images is a burgeoning and important research topic in VQA, especially for the visually impaired assistance applications. Given an image, it aims to predict an answer to a provided natural language question closely related to its textual contents. In this paper, we propose a novel end-to-end textual content based VQA model, which grounds question answering both on the visual and textual information. After encoding the image, question and recognized text words, it uses multi-modal factorized high-order modules and the attention mechanism to fuse question-image and question-text features respectively. The complex correlations among different features can be captured efficiently. To ensure the model's extendibility, it embeds candidate answers and recognized texts in a semantic embedding space and adopts semantic embedding based classifier to perform answer prediction. Extensive experiments on the newly proposed benchmark TextVQA demonstrate that the proposed model can achieve promising results.
THE CONTROVERSY OVER THE CREATION OF STATE POLICE IN NIGERIA

This paper examines the controversy over the creation of state police in Nigeria.  The debate is consequent upon the inability of the Nigeria Police to handle the myriad of security challenges facing the country. Such challenges include ethno-religious, farmers-herders clashes, communal conflicts, militancy and Boko Haram terrorism/insurgency to mention but a few.  It interrogates the arguments for and against state police and notes that there are merits and demerits in both arguments.  However, the paper opines that the argument against state police is more compelling in view of not only the vast land area of Nigeria but also its huge demography against the backdrop of the inability of the central government to attain the benchmark of the United Nations on policing.  Arising from this, and using oral and written sources of information, the paper concludes that state police for the country is an imperative which, however, can come about after an appropriate legal instrument has been put in place.  In the interim, a machinery may be initiated for the gradual decentralization of the operations of the Nigeria Police.
The Risks, Threats and Vulnerabilities in Moving to the Cloud

Cloud computing is the availability of computer system resources on-demand, like data storage, and computing power, which does not require any direct user interaction. Cloud computing has various benefits, starting with potentially lower cost (more capabilities in the public cloud which helps in productivity and more limited capabilities in the private cloud) and faster time. To revolutionize the digital transformations companies are rapidly using the cloud. Organizations expose themselves to a myriad of commercial, financial, technical, legal, and compliance risks, that adopt cloud technologies or chooses the cloud service providers (CSP) and services or applications without becoming fully informed of the risks involved. Cloud infrastructure can be complex, and everyone knows that complexity is the enemy of security. Organizations can also make grave errors and expose critical data and systems, while most cloud security experts agree that companies can benefit from the security solutions built into the cloud. Data security is amongst the key concerns holding back enterprises from adopting cloud solutions, with the array of benefits that the cloud offers. As a supportive statement, a survey found that 93% of companies are moderate to extremely concerned about cloud computing security risks.
Local Scaling Analysis with Continuous DFA in High Frequency Financial Time Series

The crucial question every investor has to answer before buying stock is: what is the risk associated with it?In this work, we applied the Continuous Detrended Fluctuation Analysis (CDFA) to uncover the point-wise Hölder exponent of the time series at various time scales.The Hölder exponent is a time-dependent measure of the autocorrelation of the variability in data, and it can be used to measure the market risk.CDFA is an extension of the popular Detrended Fluctuation Analysis (DFA) method, but -contrary to DFA -it allows for estimating the Hölder exponent locally.We used this method to study the two-minute frequency data of the U.S. S&P 500 index from 1984 to 1995.We found that the value of the exponent increases as lower resolution data was used, which means the financial time series appear more predictable at higher scales than at lower scales.Moreover, we found that correlations between the Hölder exponent and the log returns and absolute log returns are scale-dependent.That means that the CDFA method could potentially be used in the future to identify time scales at which the series are the most predictable which can have practical applications.
Into the Secrets of Jazz Arranging: Chromatic Scale in Different Harmonic Contexts

Herein we introduce a reliable and effective method, allowing any musician, regardless of the theoretical background, to carry out a 4-way jazz harmonization of whatever melodic progression almost instantly, with few exceptions. Many jazz students experience a deep frustration in dealing with the harmonization of non-diatonic notes. Sometimes, moreover, a coherent harmonization of the aforementioned notes can turn out to be a very challenging task even for extremely skilled professionals. In this paper, the harmonization of the chromatic scale in different harmonic contexts is accurately discussed, by resorting to the well-known concepts of harmonic functions, tonicization, chromatic and diatonic parallelism, and auxiliary chords. All the chords are labelled so as to allow the reader to immediately understand their role in the particular harmonic context. Consequently, the procedure essentially translates into an optimization of the "harmonic flow".
Real Time Data Pipeline for Twitter Trends Analysis

In social media, Information is present in enormous amount. Extracting data from processed information from social media gives us diverse usages in various fields. In the field of Business Analytics, HealthCare, Technologies and Trending Topics in Social Media posted by the user. Extracting information from social media is providing number of benefits such as knowledge about the latest Technology, Medical field, Business Decisions, etc. Twitter is solitary of the social media which allows the user post tweets of limited number of characters and share the tweet to their followers. Twitter allows application developer to access the tweets for their motive. In the implemented methodology, Tweets are collected, and sentiment analysis is performed on them. Based on the results of sentimental analysis of Trending Topics in Twitter, suggestions can be provided to the user. In this way, the implemented system can help in improving the growth of business, healthcare, technologies and alsoNegative or Positive mentions of a product or service can be determined.
Robot rights: Where science ends and fiction starts

Artificial intelligence (AI), thanks to pop culture, is widely identified with robots or humanoid machines that take control over humans. Even though we might be feared of the new technology or the questionable social and ethical issues that arise from it, AI is developing rapidly which makes it a priority in the cognitive economy. Consequently, processes or services performed without any help from humans can no longer be considered as a part of the distant future. According to public opinion research from last year, conducted for IBM by NMS Market Research, 92% of Poles have heard of AI and 8 out of 10 expect it to be used more broadly. Efficient legislation can ensure the correct and regulated development of new technologies whilst inefficient legislation or the complete lack thereof can halt and even completely cease further research, or make the usage of AI significantly difficult in both social life and the economy. This paper is an attempt at placing national legislation concerning AI in the context of the legislation of the EU and other countries. I will attempt to answer the question of whether it is possible to introduce into legislation a technology whose usage and full potential are yet unknown. Is AI, in terms of the law, a scientific fantasy or can it be regulated? I have analysed soft law on which some general regulations and future law recommendations are based. Currently, AI is only restricted by single provisions as there are no regulations that can be used in a complex manner in the area of new technology.
THE IMPLEMENTATION OF GROUP INVESTIGATION IN TEACHING READING (A Quasi-Experimental Research at SMAN 24 Bandung)

&lt;p align="center"&gt;&lt;strong&gt;ABSTRACT&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt; &lt;/em&gt;&lt;/strong&gt;&lt;/p&gt;&lt;p&gt; This study aims to find out the effectiveness of Group Investigation method in improving students’ reading ability. This quasi-experimental research design was involved 64 students of SMAN 24 Bandung as the participants. This study used a type of data collection technique including pre test and post test. The conceptual framework for the study included the independent variable of teaching method, and dependent variable of students’ ability in reading. The experimental study was conducted within this framework by using non parametric test. The results of data analysis show that Group Investigation could facilitate the students in improving their reading ability. It can be seen from the result of mean rank and Mann-Whitney U. Furthermore, the results of the pre test and post test indicate that students’ reading ability improved in four indicators, encompassing identifying the explicit information, identifying the main idea of the text, identifying the purpose of the text, and identifying the implicit information of the text. Meanwhile, the results of test in control group indicate that the students’ reading ability improved in two indicators, encompassing identifying the purpose of the text and identifying the synonym of the words. Due to the limitations of the study, it is recommended for other researchers to introduce Group Investigation gradually into the classroom and practice it before the class undertakes a full-scale investigation project and to observe the students’ social interaction skill in the classroom. It is also recommended for every teacher who wants to use this method to fully competent at implementing this method. Despite the need for the further research, this method can be used as a method in teaching reading to EFL learners.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords:&lt;/strong&gt;&lt;em&gt; reading ability, Group Investigation. &lt;/em&gt;&lt;/p&gt;
Digital Transformations and the Challenges of Higher Education Institutions

This work aims to identify the challenges of Higher Education Institutions against the increasing digitalization. The first part of the work reviews Industry 4.0, analyses recent scientific works to demonstrate how the technological changes and especially the development of Information and Communication Technologies causes the future of jobs. Fourth Industrial Revolution creates the general foundation for the activities of nowadays; the platform economy is gaining strength; digital transformation with the advent of big data, digital literacy, and data literacy is becoming increasingly essential. To prepare students for their future work is the direct responsibility of Higher Education Institutions. The second part of this work is devoted to the challenges of the education system, focusing on the Higher Education Institutions. Desk research is conducted to analyze what changes will bring the ongoing process and how these institutions should respond to the challenges of digitalization. The contribution of this paper is to develop the conceptual design of responding measures to the digitalization taken by Higher Education Institutions.
Blood Group Determination through Medical Image Processing

The determination of blood types is crucial during any emergency situation before blood transfusion. At present, these tests are performed manually by lab technicians in clinical laboratories, which can lead to slip-ups. In emergency situations, timely determination of the blood types is crucial for the treatment of the patient. A method based on image processing is developed. Image processing techniques, such as colour plane extraction, thresholding, morphological operations, and quantification, are used. The images of the slide test obtained from the pathological laboratory are processed, and the occurrence of agglutination is evaluated. The slide test used for processing consists of the mixture of one drop of blood with one drop of reagent, the results are interpreted according to the occurrence of agglutination. The combination of the occurrence and non-occurrence of the agglutination will determine the blood type of the patient.
Using Natural Language Processing to Translate Plain Text into Pythonic Syntax in Kannada

Digital evolution has made various services and products available at everyone's fingertips and made human lives easier.It has become necessary for individuals with a passion to be a part of this digital evolution to learn how to write code, which is the basic literacy of the digital age.But writing code has become a privilege for students with prior knowledge of English.In the context of the evolving field of Agri-tech, individuals and companies are making large strides towards digitising various different aspects of Agriculture.AI is being used actively to solve various problems in the agricultural space.The basic expected literacy here as well, is the ability to write code with the default understanding of English.Rural areas where one of the mainstream occupation for a large part of the population is Agriculture, English language may not be their primary language of choice for written and verbal communications.With our work, we wish to provide a learning interface that users can employ to first learn the basics of writing code in their native language (Kannada will be in focus in our paper) and in future, the farmers can themselves build and consume tools that help them in their day to day needs with the skill of writing code that they can now acquire without the pre-requisites of knowing English.The current model can successfully identify and convert conditional statements in the Kannada language into python code.The next effort will be aimed at extending this to recognise loop statements and create a framework for a wide variety of languages.