Reviewerly/exHarmony huggingface dataset:
CERITA RAKYAT SEBAGAI UPAYA PENGENALAN BAHASA DAN BUDAYA INDONESIA DALAM PEMBELAJARAN BIPA

Indonesian is the official language and the unity of the Indonesian nation. Currently, Indonesian is increasingly in demand by foreign speakers with various backgrounds. Foreign speakers learn not only Indonesian but also Indonesian culture. This study aims to describe folklore as an effort to introduce the Indonesian language and culture to foreign speakers. The method used in this research is library research. The results showed that folklore could be used as teaching material to introduce the Indonesian language and culture to foreign speakers. The use of folklore can also be integrated into the four language competencies: listening, reading, speaking, and writing.
Analysis of the Impact of Education Management on Academic Performance and Competitiveness of Universities in Terms of Faculty Turnover in China

The purpose of the article is to demonstrate the role of education management in order to enhance the academic performance and competitiveness of Chinese universities. After the COVID-19 pandemic, technology-based education has resulted in faculty burnout and turnover due to a lack of motivation of delivering quality education. In order to accomplish the article, a secondary source of information has been used based on which thematic analysis has been performed. With the inevitable tendency of teaching through technology, teachers can be adopted with the rapid-changing teaching context in China. Each teacher must be active in understanding the need to learn specific software and hardware skills in order to deliver quality education to students. It has been found from the research that China has adopted MOOCs to help teachers for upgrading their skills and knowledge. Teachers in university, besides experience a lack of psychological empowerment which lower engagement n education. It is therefore effective to provide training opportunities to the teachers by the management to improve the overall performance of the university. Therefore, it is recommended to incorporate teachers in designing pedagogical frameworks and design thinking technology.
The Impact of Competition and Market Structure on The Financial Performance and Integrity of The Nigerian Commercial Banks

This research examines the effects of banking competition and market structure on the financial health and integrity of the Nigerian commercial banks from 2010 to 2020. The measures of concentration k-bank concentration ratio (CRk) and Herfindahl-Hirschman Index (HHI), respectively, are used in this study to analyses competition and market structure. This research employs a panel static model that combines panel ordinary least squares, a fixed effect model, a random effect model, and a dynamic GMM model to evaluate the empirical model. The results show that the Nigerian banking market is moderately concentrated as measured by the Concentration Ratio-CR5 and the Herfindahl-Hirschman indexes-HHI, with significant disparities in market power among market competitors. The Nigerian commercial banks operate in a monopolistically competitive environment (monopolistic competition), based on conventional qualities that exist between various market structures. The findings also revealed a strong inverse relationship between Nigerian commercial banks' profitability and banking competition. To protect competition between commercial banks in Nigeria there is the need for the regulatory authorities to be cautious of efforts that may increase market concentration of commercial banks in Nigeria.
Ecolodge sebagai Implementasi Pendidikan Sains (IPA) yang Multidimensi

Science Education (IPA) is a science related to systematic natural and material symptoms that are arranged regularly, generally in the form of a collection of observations and experiments. Science learning is expected to be a vehicle for students to learn about themselves and the surrounding nature, as well as the prospect of further development in applying it in everyday life. In the world of education, environmentally sound education has begun to be integrated, for example education with the vision of SETS (Science Environment Technology and Society) is defined as science, environment, technology, and society, is a unit that in the concept of education has implementation so that students have the ability to think higher (higher order thinking) Science, Technology and Society (STS) approach or the Science, Technology and Society (STM) approach. is a combination of concept approaches, process skills, CBSA, Inquiry and disambiguation as well as environmental approaches. One example of the implementation of the learning model with the environment is lodging in an open environment with an environmentally sound concept called ecolodge. Ecolodge is a small hotel or guesthouse that combines local architecture, culture and natural characteristics, supports environmental conservation by reducing waste and energy use and provides social and economic benefits to local communities.
THE EFFECT OF INTERNAL CONTROL SYSTEM ON THE PROFITABILITY OF SMALL MEDIUM ENTERPRISES IN RWANDA. A CASE OF CETRAF LTD (2016-2019)

The aim of this study was to evaluate the effects of internal control systems on profitability of SME’s in Rwanda . A descriptive research design was adopted in this study while the population of this study was 445 employees of CETRAF Ltd. A sample of 82 employees of CETRAF Ltd was selected . Purposive sampling technique was used both primary data and secondary data were used; where primary data were collected using questionnaire and interview while the secondary data were collected using documentation. After the data collected were organized, edited and coded, quantitative data were entered into SPSS 20 and MS-Excel. The significance of the findings was tested using the p-value, to determine whether the null hypothesis should be accepted or rejected. If the p-value &gt;0.05 then alternative hypothesis is accepted while null hypothesis is rejected. The results examined and established a significant relationship between internal control system and profitability of CETRAF Ltd through the dimensions of internal control systems (the control environment, control activities, risk assessment, information and communication, and monitoring activities) and that of the profitability (ROE) selected for this particular study. Details showed that control environment is linked to ROE (r = 1.000, p ≤0.05), control activities is also linked to ROE (r = 0.762, p ≤ 0.05), risk assessment is linked to ROE (r = 0.836, p ≤ 0.01), information and communication is also linked to ROE (r = 0.762, p ≤ 0.05), and monitoring activities is linked to ROE (r = 0.836, p ≤ 0.01). It implied that there a strong positive relationship between internal control system and profitability of CETRAF Ltd . The study concluded that there was a positive relationship between the control environment, control activities, risk assessment, information and communication, and monitoring activities and the profitability of CETRAF Ltd. The study recommended that SME’s should ensure that they have effective control environment, control activities, proper risk assessment policies, efficient information and communication methods and proper monitoring activities strategies to ensure that their internal controls systems are effective and to enhance their profitability. Key Words: Internal Control Systems, Profitability of Small Medium Enterprise CITATION: Uwineza, F., Maringa, E. K., &amp; Mbanzamahoro, H. F. (2022). The effect of internal control system on the profitability of small medium enterprises in Rwanda. A case of Cetraf Ltd (2016-2019). The Strategic Journal of Business &amp; Change Management, 9 (2), 1 –23.
EFFECT OF ESSENTIAL BUSINESS COMMUNICATION PRACTICES ON CONSUMER CHOICES IN THE OIL AND GAS INDUSTRY: A CASE STUDY OF NATIONAL OIL CORPORATION OF KENYA

The purpose of this paper was to examined the role of essential business communication practices on the consumer choices in the oil and gas industry. Business communication entails the sharing of information, both internally and externally in regard to the execution of company obligations towards the realization of mission and vision. Traditional mediums of business communication notably print media and visual audio communication have remained reliable and useful over many decades. However, with the advancement in technology in this information age, digital communication has really gained traction in business communication. Companies in the oil and gas industry have also embraced best practices in essential business communication in effort to appeal the ever growing consumer base in the oil and gas industry. This posits the importance of understanding the effect of essential business communication on consumer choices. This study adopted case study approach with National Oil Corporation being the organization of focus. Top managers from the company drawn from marketing, human resource and corporate communication department participated in the study. An interview schedule (Appendix 1), was used as the tool for data collection. The study established that essential business communication was a critical factor in selling reputation in the eyes of petroleum consumers. Digital communication was found out to be useful in regard to faster transmission of important information both internally and externally. The study concluded that most modern petroleum consumers were digital connected thus well confirmed on all trends within the oil and gas industry which informed their petroleum brand preferences. The study recommended for investment in digital communication, through modernization of communication systems and technologies into cutting edge high-tech systems. The study also recommended for capacity building in boosting digital communication and human resource pool for petroleum companies which is necessary for modernized communication with informed consumers. Key Words: Business Communication, Consumer Choices CITATION: Maundu, J. (2020). Effect of essential business communication practices on consumer choices in the oil and gas industry: A case study of National Oil Corporation of Kenya. The Strategic Journal of Business &amp; Change Management, 7 (4), 1534 – 1546.
Nexus among Crypto Trading, Environmental Degradation, Economic Growth and Energy Usage: Analysis of Top 10 Cryptofriendly Asian Economies

The higher discharge of carbon emissions in environment is endangering human life as well as eco system. With the emergence of digital technology, crypto trading and blockchain technologies are also causing the paradigm shift in technological needs, however, in parallel, creating unresolved environmental problems especially in the top 10 crypto-friendly Asian economies due to the higher percentage of poisonous emissions. Thereby, the study attempts to scrutinize the nexus among crypto-trading, environmental degradation, economic growth and energy usage. CO2 emissions are taken as a proxy of environmental degradation in the context of crypto friendly Asian economies. The data extracted from WDI and coin market cap covering the period from 2012-2020. The article applied CS-ARDL technique in order to find the association between variables in short and long run. Granger Causality test is also applied to find out the causality among constructs. Findings expose that bi-directional causality exists between crypto trading and carbon emission and crypto trading and energy usage, hence, disturbing environmental sustainability due to high emissions. The paper suggests policy makers and other institutional officers to de-socialize those block chain technologies which consumes high energy and use green technology as their substitute. This helps in the reduction of environmental damages.
Mapping Corporate Social Responsibility: Unveiling Compliance and Expenditure Trends in Public and Private Sector Banks (2013-2020)

This research report thoroughly and minutely examines the compliance of Corporate Social Responsibility activities through item-wise aggregate analysis of nominated public sector banks and private sector banks from 2013-20. Furthermore, the amount spent on different CSR activities in accord with the provisions of the Companies Act 2013 has been investigated. The study is vivid in nature and is based on secondary data. The researchers presented the results using tables and graphs.
Linguistic Profile of a Text and Human Ratings of Writing Quality: a Case Study on Italian L1 Learner Essays

This paper presents a study based on the linguistic profiling methodology to explore the relationship between the linguistic structure of a text and how it is perceived in terms of writing quality by humans. The approach is tested on a selection of Italian L1 learners essays, which were taken from a larger longitudinal corpus of essays written by Italian L1 students enrolled in the first and second year of lower secondary school. Human ratings of writing quality by Italian native speakers were collected through a crowdsourcing task, in which annotators were asked to read pairs of essays and rated which one they believed to be better written. By analyzing these ratings, the study identifies a variety of linguistic phenomena spanning across distinct levels of linguistic description that distinguish the essays considered as ‘winners’ and evaluates the impact of students’ errors on the human perception of writing quality.
Semidirect product key exchange: The state of play

Of the many families of cryptographic schemes proposed to be post-quantum, a relatively unexplored set of examples comes from group-based cryptography. One of the more central schemes from this area is the so-called Semidirect Product Key Exchange (SDPKE), a generalization of Diffie–Hellman Key Exchange that is plausibly post-quantum. In this report we survey the state of the literature relating to SDPKE, providing a high-level discussion of security, as well as a comprehensive overview of the proposed platforms and the main cryptanalytic ideas relevant to each.
The Problems Of Pre-Reading Instruction In Thematic Learning At Grade 2 SDN 09 Bandar Buat, Kecamatan Lubuk Kilangan, Padang

This study aims to analyze the problems of early reading in thematic learning in class II at SDN 09 Bandar Create, Lubuk Kilangan District, Padang. This study uses a qualitative approach with a descriptive type. The subjects of this research are class II teachers and students. This research was conducted at SDN 09 Bandar Create, Lubuk Kilangan District, Padang in June 2022. The data collection techniques used were observation, interviews and documentation. The results showed that in applying good reading learning outcomes to students, the teacher could apply thematic learning in students' reading problems, doing a preparation and planning. In the planning, among others, the first to look at the students' reading ability and determine the learning objectives to be implemented. Second, the teacher uses thematic reading teaching materials to guide students in learning to read. The three teachers use the media to guide students in reading activities
PhaPaM: In Vitro Panoramic Map Using Phase Correlation

Studying cells of brain slices under microscopes reveals subtle changes in neuron networks. But the field of view of microscopes is compromised by high-resolution imaging. A post hoc computer vision-aid process can address the problem. Commonly, feature-based stitching methods can be used to obtain large-scale images. They detect and match salient features within an image. However, the success rate of stitching is highly related to the scale of overlapping of two images and feature-rich properties. Unlike the feature-based methods, this paper reports on a method using a Fourier-based domain, PhaPaM, which infers relative motion from a pair of microscopy images by phase correlation. Specifically, we first apply the Fourier transform for microscope images to sequentially estimate the relative movement of an image pair. Then, we use a minimal spanning tree algorithm to minimize the stitching error and obtain the best stitching path. Finally, we apply the liner-blending method to smoothing the panoramic image. This method is evaluated using large-scale images obtained from the visual cortex of rodent animals, which shows great fidelity and satisfying results.
A PSO-Based Cooperative Search Method for Multi-UAVs with Collision Avoidance

Since Unmanned Aerial Vehicle (UAV) swarm emerged with the merit of high efficiency, flexibility and robustness in search tasks, related research has been in the spotlight in recent years. In this paper, an adaptive cooperative search method with the ability of collision avoidance for multi-UAVs is presented on the basis of the well-known Particle Swarm Optimization (PSO) algorithm and the efficient topological planning method EGO-Swarm. Remarkably, apart from the introduction of adaptive strategy to compensate for the easy tendency to local optimum of classic PSO, a mechanism of autonomous path planning is innovatively incorporated into PSO algorithm to eliminate possible collisions. This, while inheriting the intrinsic advantages of PSO like few parameters, simple implications and low computational complexity, facilitates the practical application of UAVs in nonideal search environments. Simulation shows that our method proposed is well suited for rapid target localization in scenes dense with obstacles, while confliction among UAVs can also be avoided swiftly.
Path Planning and Tracking Control for Quadrotor Helicopters Based on Artificial Potential Field

This paper presents a path planning method that satisfies both environmental constraints and dynamics constraints of the quadrotor helicopters. An improved artificial potential field (APF) method is employed in path planning for the quadrotor to get a series of path points that meet environmental constraints. Using the differential flatness property of the system, a smooth reference trajectory connecting these path points satisfying the dynamics characteristics of the quadrotor is obtained. A cascaded control strategy is proposed for autonomous flight control of the quadrotor. The outer loop adopts high-order differential feedback control (HODFC) method, and the inner loop employs proportional-integral-derivative (PID) controller. Numerical simulations and experimental results show that the proposed control strategy has superior tracking performance compared with the cascaded PID controller.
Healthcare Chatbot Using Artificial Intelligence

In today's busy life, people often do not take proper care of their health. People try to avoid going to the doctor for a diagnosis, either because they don't like it or because they don't have time. Health care is very important if you want to lead a good life. However, it is very difficult to get a consultation with a doctor in case of any health problems. The proposed idea is to create a medical chatbot using artificial intelligence to diagnose the disease and provide basic details before consulting a doctor. The user can only get the real benefit of the chatbot if it can diagnose all kinds of diseases and provide the necessary information. To solve this problem, this project provides a platform where a human can interact with a highly trained chatbot on datasets using machine learning algorithms. Machine learning algorithms take a more natural approach to computation than a logical approach. The output depends on the dataset they are trained on. We can implement a real-time medical system and convert text results into voice format. The proposed system also supports the drug purchase process and payment process through this application.
A Study on Error Feature Analysis and Error Correction in English Translation Through Machine Translatio

English translation is the most frequently encountered problem in English learning, and fast, efficient and correct English translation has become the demand of many people. This paper studied the most frequently encountered English grammatical error problem in English translation by the Transformer grammatical error correction model in machine translation and explored whether machine translation could analyze the features of the errors that may occur in English translation and correct them. The results of the study showed that the precision of the Transformer model reached 93.64%, the recall rate reached 94.01%, the value was 2.35, and the value of Bilingual Evaluation Understudy was 0.94, which were better than those of the other three models. The Transformer model also showed stronger error correction performance than Seq2seq, convolutional neural network, and recurrent neural network models in analyzing error correction instances of English translation. This paper proves that it is feasible and practical to identify and correct English translation errors by machine translation based on the Transformer model.
META-ANALYSIS REVIEW OF THE USE OF VIRTUAL REALITY IN SAFETY TRAINING

This study aims to review the use of virtual reality in safety training through a meta-analysis approach. The choice of topics in this study was motivated by the lack of studies related to correlations that discuss Virtual Reality" and "safety amid the high use of Virtual Reality in various aspects. The method in this study follows the Preferred Reporting for Systematic Reviews and Meta-Analysis (PRISMA). PRISMA was created with the aim of helping to ensure clarity and transparency of reporting, systematic reviews, and meta-analyses. The meta-analysis conducted resulted in the discovery of a large-size effect on the relationship between Virtual Reality and Safety. Based on the analysis with Jamovi, the results of the heterogeneity study obtained a value of Q = 170.487, a value of I2 = 96.25%, and Tau2 = 0.3825 (with SE = 0.1937). In addition, the effect size value is 0.67 (RE Model), the Eggers Regression value is -2.104, and in the forest plot image, it is known that the data represented by black dots are located inside the white triangle and are around the triangle.&#x0D;
Anomaly Detection in Time Series Flight Parameter Data Using Machine Learning Approach

Abstract: Infrastructure monitoring is more crucial than ever, especially in the aviation industry. To attempt to overcome the difficulties brought on by the problems given by the exponential growth of connected devices and data volume, this study analyzes the application of machine learning approaches for anomaly identification in time series flight parameter data. The introduction of network telemetry, which automates data collecting, is presented as a remedy, however processing enormous data quantities in real-time still poses a challenge. With a focus on time-series data, the paper explores the role of machine learning in network telemetry anomaly detection. Statistical, proximity-based, deviation-based, and supervised classifiers are used to identify anomalies, or departures from predicted patterns, in flight parameter data. For a few examples of anomalous data, long short-term memory networks (LSTMs) are used. The objective is to provide an effective anomaly detection system that can process complex time series flight data and includes data purification, anomaly discovery, temporal reference, and value prediction. The methodology describes the univariate anomaly detection strategy, in which distinct models record particular patterns for each flight parameter. The findings offer new understanding of thresholds, repeated anomaly correction, and prediction errors. The results show that the method is accurate in separating instances of normal data from those containing anomalies, making it a useful tool for practical applications needing accurate anomaly identification.