Reviewerly/exHarmony huggingface dataset:
Pemilihan FinTech Payment untuk Mahasiswa menggunakan Fuzzy Technique For Order Preference by Similarity of Ideal Solution

Abstrak: Pembayaran saat ini beragam macamnya dari pembayaran menggunakan uang tunai,kartu sampai dengan dompet digital. Dompet digital merupakan alat pembayaran yang sahdibawah pengawasan OJK seperti contoh Gopay, OVO, Dana, Link aja, Shopepay dan lain-lain.Pemilihan dompet digital sangat berperan bagi ekonomi mahasiswa, semakin tinggi tingkatekonomi mahasiswa pemilihan dompet digital pun berubah. Penelitian ini untuk pemilihan fintechpayment yaitu Gopay, OVO, Dana, Link Aja dan Shopepay untuk Mahasiswa menggunakanMetode Fuzzy Technique For Order Preference by Similarity of Ideal Solution (TOPSIS). Hasildari penelitian ini Gopay mempunyai nilai tertinggi dengan angka 0,9220, kemudian rangking kedua OVO 0,8435, dan yang ketiga 0,5910 untuk shopepay dari hasil tersebut Gopay dapatdigunakan sebagai rekomendasi mahasiswa untuk bertransaksi.&#x0D; Kata kunci: dompet digital, dana, gopay, OVO, shopepay&#x0D; Abstract: Abstract: Current payments vary from cash, card to digital wallet payments. Digitalwallet is a legal payment instrument under the supervision of OJK, for example Gopay, OVO,Funds, Link only, Shopepay and others. The choice of digital wallet plays an important role forthe student economy, the higher the economic level of students the selection of digital walletchanges. This research is for fintech payment selection namely Gopay, OVO, Funds, Link Ajaand Shopepay for Students using the Fuzzy Technique Method for Order Preference by Similarityof Ideal Solution (TOPSIS). The results of this study Gopay has the highest value with a numberof 0.9220, then ranked second OVO 0.8435, and the third 0.5910 for shopepay from these resultsGopay can be used as a recommendation for students to transact.&#x0D; Keywords: digital wallet, dana, gopay, OVO, shopepay&#x0D;
Mathematical Radiation Models for Sustainable Innovation in Smart and Clean Cities

Sustainable energy has started to attract many researchers due to the ecological imbalance as a result of fossil-based energy sources. The use of renewable energy sources instead of fossil-based resources is a critical choice in preserving the ecological balance when making smart city designs. When all sorts of renewable energy sources are explored, solar energy appears to be the most applicable resource in smart and clean city designs. Solar energy is a source that can be obtained in most of the cities more or less. It is also a clean and relatively low-cost alternative without carbon emission in the production process and it can be stored. Even the intensity of the solar energy in a city is low and it can be transformed into mechanical and electrical (e.g., photovoltaic) energies with appropriate efficiency. Thus, solar energy is the optimum choice for smart and clean city designs.
On the Performance of a Class of Generalized Linear Mixed Model on Some Psychiatric Patients&amp;apos; Data

A generalized linear mixed model (GLMM) is an extension to the generalized linear mixed (GLM) in which the linear predictor contains random effects in addition to the usual fixed effects.They also inherit from GLMs the idea of extending linear mixed models to non-normal data.There are several applications of various types of generalized linear mixed models (GLMMs) to various fields, especially in the areas of health and biological sciences.In this our study Poisson logistic mixed regression model (a class of GLMM) was adopted to investigate the performance of the above mentioned method on some psychiatric patients' data.A clinical trial of ninety (90) mentally disordered patients was examined in this work.Patients suffering from some level of psychiatric disorder were randomized to receive either Amitryphylline or Benzhexol in addition to other therapy.This work is motivated by Thall and Vail, which investigated the performance of the Poisson logistic mixed model on some epileptics' data.The two types of therapy have little effect on the patients, but the interaction (between treatments and visits) has a substantial impact on the patients.The number of seizures is reduced by visits, and a combination of visits and medicines decreases the number of seizures.The fact that the treatments are insignificant suggests that mental disorders are mostly treatable with currently available medications.These drugs only 'manage' them for a short period of time.
Distance Teaching Mode and Practices in College English Course during COVID-19 Pandemic Crisis in China

During the COVID-19 pandemic in early 2020, many Chinese colleges and universities actively carry out distance online teaching, responding to the call of the Ministry of Education to "suspend classes without suspension of teaching and learning."However, the integration of the Internet and education has changed the traditional education ecology and has also posed a huge challenge to the traditional teaching model.The research focuses on the teaching practices of on-line teaching of College English course and offers a detailed analysis of the changed teaching model adopted by China Jiliang University.The paper employs both quantitative and qualitative approaches to study the perceptions of teachers and students during the lockdown period, trying to construct a new online teaching mode by taking both of the feedback of students and the teaching reflection of teachers into consideration.It is hoped that the research results can provide some enlightenments for colleges and universities to deal with emergencies and expand online higher education in the future.
Multimodal Neural Machine Translation System for English to Bengali

Multimodal Machine Translation (MMT) systems utilize additional information from other modalities beyond text to improve the quality of machine translation (MT).The additional modality is typically in the form of images.Despite proven advantages, it is indeed difficult to develop an MMT system for various languages primarily due to the lack of a suitable multimodal dataset.In this work, we develop an MMT for English→Bengali using a recently published Bengali Visual Genome (BVG) dataset that contains images with associated bilingual textual description.Through a comparative study of the developed MMT system vis-a-vis a Text-totext translation, we demonstrate that the use of multimodal data not only improves the translation performance improvement in BLEU score of +1.3 on the development set, +3.9 on the evaluation test, and +0.9 on the challenge test set but also helps to resolve ambiguities in the pure text description.As per best of our knowledge, our English-Bengali MMT system is the first attempt in this direction, and thus, can act as a baseline for the subsequent research in MMT for low resource languages.
Cultural and artistic education strategies

The relevance of this study is conditioned by the dual standards of institutionalisation of artistic and educational practices, must meet the principles of creating cultural objects as material products of high culture and aesthetic level, but, at the same time, must meet the requirements of the time, standards and educational tendencies of its time. Thus, a conflict of artistic vision and the standards of accumulated artistic experience is formed, which must be resolved in a process of dialogue and permanent collaboration of the two practices: educational and artistic. The purpose of this article is to investigate the basic vectors of the institutionalisation of educational and artistic practices, identifying priority ways of institutionalising both practices and the space for their interaction in scientific research. The main scientific methods for researching the topic are the basic general scientific theoretical methods of analysis, synthesis, induction, deduction, comparative to deduce the main regularities and characteristic features in the processes of institutionalisation of artistic practices, as well as systematisation and classification methods to form the structure of the main educational artistic strategies based on common and unique features.
Cryptocurrencies: Concept and Current Market Structure

Since the creation of Bitcoin in 2009, hundreds of cryptocurrencies have emerged, thus becoming a common fixture of financial news bulletins. With a market capitalization of the five highest-valued cryptocurrencies exceeding $140 billion at the time of writing, these alternative currencies have caught the attention of both financial institutions and central banks with their innovative technological foundations and their potential to disrupt current financial institutional structures. We provide a non-technical overview of the concept and current market structure of cryptocurrencies for researchers in economics, finance, mathematics and computer science.
ON THE REFORM OF TEACHING MODE IN VOCATIONAL AND TECHNICAL EDUCATION

Abstract. Around the development of modern science and technology, combined with different education modes, this paper discusses the reform of education mode, in order to improve the quality and efficiency of teaching and promote the modernization of education. At the same time, this paper puts forward some suggestions on the curriculum based on the learning experience.
Research on Speech Processing Strategies for English Speakers During Learning of Chinese Quantifier Complements

This study explored the speech processing strategies for English speakers of three Chinese proficiency levels to learn five types of Chinese quantifier complement sentences through the compiled examination.English speakers experience four speech processing strategies from the low level to the high level when they are processing word order of quantifier complements: sequential combination strategy of verb-quantifiers < verbobject phrase adding strategy < verb-object phrase separation and insertion strategy < separable word separation and insertion strategy.This process reflects the development from external processing to internal processing, that is, from the external adding of components to internal separation and insertion of components.The internal separation of phrases is also manifested by development features from separation among different components to separation of single component.
Analysing Photovoltaic Carport Canopies Power Generation using Artificial Neural Network and Graphical User Interface

This study discusses Analyzing Photovoltaic Carport Canopies Power Generation Using Artificial Neural Network. Carports are free-standing buildings having a roof and solar canopies are an increasingly popular way to take benefits of parking and invest in solar power. Many factors could influence the power output of carport canopies such as depends on peak sun hours, temperature, and shading. Therefore, it is important to predict the PV system's optimal power output. This study will analyze the potential of Artificial Neural Network (ANN) with Graphical User Interface (GUI) which will be applied in the system of prediction of power output from photovoltaic (PV) panel system. To be verified efficiency and reliability, the proposed ANN model and GUI experimental output are in comparison with proposed mathematical equations. The novelty of this project is Renewable energy (RE) friendly, predicting solar panel power output and prediction of solar radiation for solar systems by ANN. Therefore, the prediction of solar power generation involving the calculations of parameters such as the weather, sun hours and temperature plays an important role as the solar panel output will not produce according to its rating. The results stated that the total number of PV panels for carport canopies is 1332. A large proportion of the designated car parking areas have been installed with carport canopies are currently about 11 rows of car parking areas. Also, total energy production for one year, which is 438370030.4 kWh. The total assured power output, maximum power output and net array for one year, values are 149178672 kW, 105096892.9 kW and 94587203.3 kW. The design of a GUI and an ANN which can predict solar power output on a daily, monthly, and annually has been successfully designed and developed.
Dynamic Obstacle Avoidance for AUV based on the Randomized Sampling-based Algorithm

Real-time dynamic obstacles avoidance in the pre-unknown environment is a state-of-the-art in the autonomous underwater vehicle path planning. In this paper, the Local Real-time Reactive Randomized Sampling-Based Tree (LR3SBT) is proposed. The LR3SBT considers various obstacles and applied the RRT algorithm to generate the collision-free path in the time varying environment. The LR3SBT consists of four components: 1- Sampling-Based Tree path planner (SBT-PP), 2- Local path planner (L-PP), 3- Reactive path planner (R-PP), and 4- Critical path planner (C-PP). The initial path is designed by offspring random nodes through the SBT-PP. If unknown obstacles are detected in the initially planned path, the L-PP is called by LR3SBT. The R-PP module is called if the desired path does not generate through the L-PP. If unknown dynamic obstacles are detected, the C-PP module is called. The planed path is optimized eliminating further nodes using the concept of triangular inequality. Simulation results demonstrate the path planning and dynamic obstacle avoidance in the pre-unknown environment through the LR3SBT. The real-time response and certain obstacles avoidance are two characteristic of the LR3SBT method.
LibGuides: Gardening and Horticulture Open Access Resources: General Gardening Resources

This guide provides many open access (free to use) resources regarding agriculture, horticulture, and other topics usually covered within the University Extension programs.
Social Media Networking: As Facilitator of Acculturation

Globalization has made the whole world a single market for the consumer as well as for employees in terms of employment opportunities. This phenomenon, resulted in acculturation problems for global enterprises. The tension/stress of cultural adjustment at a new workplace with their own culture results in adverse effects the employee’s mental and physical health. Organizations are trying to utilize social media networking as a solution to this challenge and even employees it using as a mean to learn the culture of the organization. With the objective to explore the impact of social media networking on the acculturation of employees, the sample of 735 employees of various IT companies using the social networking platform of their organization taken, and data collected through a standardized questionnaire of 22 items, and analyzed using EFA and OLS techniques. The study resulted in a positive significant impact of social media on the acculturation of employees, however, there is a difference in employee behavior towards social media on the geographical basis.
A Platform for Keyword Search and its Application for COVID-19 Pandemic Data

Keyword search is typically associated with information retrieval systems. However, recently, keyword search has been expanded to relational databases and RDF datasets, as an attractive alternative to traditional database access. This paper introduces DANKE, a platform for keyword search over databases, and discusses how third-party applications can be equipped with DANKE to take advantage of a data retrieval mechanism that does not require users to have specific technical skills for searching, retrieving and exploring data. The paper ends with the description of an application, called CovidKeyS, which uses DANKE to implement keyword search over three COVID-19 data scenarios.
Impact of Psychological, mental, and Socioeconomic Factors on Corruption in South Asia

The study empirically examines the effects of socio-economic factor (per capita GDP, level of education and Inflation) on crime (corruption) in South Asia. For empirical analysis panel Co-integration technique is used by using data for four South Asian countries for the period 1997 to 2017. First, it is found that the variables have unit roots at levels but are stationary at first differences, which indicates the possibility of co-integration. Co-integration test results show that long-run co-integrating relationship holds among variables. Fully Modified OLS (FMOLS) and Dynamic OLS (DOLS) methods are applied to find the parameter estimates. The results of long run estimates show that level of education, per capita income reduces the corruption, while inflation increases the corruption in the region. It is also found that growth also increase the corruption. Corruption enhances economic growth by allowing investors to escape bureaucratic interval by the use of “speed money”.
A Study on the criteria for judging the responsibilities of the parties involved in Back to Back L/C fraud trade transactions

Purpose : To investigate the legal problems regarding the relationship between parties in Back to Back L/C fraud trade transactions, to present the criteria for judging trade fraud based on the relationship between the Master L/C and Back to Back L/C, and to prevent Back to Back L/C trade fraud by deducting the implications for the issuing bank and shipping carrier of the Master L/C. Research design, data, methodology : Literature review and analyzed Supreme Court Decision 2017Da21776 decided on November. 14, 2017 Results : First, the Supreme Court's legal interpretations of the negotiating bank, Fraud Rule, and the forgery of shipping documents were introduced as problems. Second, the limitations of the payment methods used in trade fraud between the Master L/C and Back to Back L/C were investigated. Third, the criteria for judging whether the parties of the Master L/C were involved was presented. Finally, through the analysis of the Supreme Court, the implications for the issuing bank, negotiating bank, and shipping carrier of the Master L/C were deducted. Conclusions : The Master L/C and Back to Back L/C payment method has loopholes where the issuing bank and the negotiating bank of Master L/C can be subjected to trade fraud. Given that the L/C trade fraud starts and ends with a bill of lading, the shipper who issues this bill of lading must be held accountable.
Innovative Methods of Teaching Russian Language and Literature

The traditional education system lags somewhat behind the needs of society. The concept of modern education has determined the goal of the teacher's professional activity - to form students' ability to successfully socialize in society, actively adapt to the labor market. The consequence of this is the development of innovative technologies in teaching. Innovative methods are characterized by a new style of organizing educational and cognitive activities of students. Modern teachers admit that the technology of problem-based learning presents the maximum opportunities in the development of creative abilities, intellectual activity
Efficient Detection and Early Diagnosis of Breast Cancer Using Deep Learning

AComputer-aided diagnosis system based on mammograms enables early breast cancer detection, diagnosis and treatment. However, the accuracy of the existing CAD system remains unsatisfactory. In the proposed system, design of critical and early breast cancer detection is done using machine learning approach to make the system detect the tumor cells automatically using advanced image processing techniques. Images pre-processed by studying various parameter extraction such as  color conversion, resizing and filtering. Fuzzy c-means clustering segmentation is carried out by segmentation algorithms. This helps to identify the amount of lesions scattered over the body. Feature extraction is by GLCM and finally, Approximate reasoning method to recognize the tumor shape and position in MRI image using LDA algorithm classification method. Finally the message box will be displayed whether it is benign or malignant.
Temporal Video Segmentation Using Optical Flow Estimation

Shot boundary detection is the process of segmenting a video into basic units known as shots by discovering transition frames between shots. Researches have been conducted to accurately detect the shot boundaries. However, the acceleration of the shot detection process with higher accuracy needs improvement. A new method was introduced in this paper to find out the boundaries of abrupt shots in the video with high accuracy and lower computational cost. The proposed method consists of two stages. First, projection features were used to distinguish non boundary transitions and candidate transitions that may contain abrupt boundary. Only candidate transitions were conserved for next stage. Thus, the speed of shot detection was improved by reducing the detection scope. In the second stage, the candidate segments were refined using motion feature derived from the optical flow to remove non boundary frames. The results manifest that the proposed method achieved excellent detection accuracy (0.98 according to F-Score) and effectively speeded up detection process. In addition, the comparative analysis results confirmed the superior performance of the proposed method versus other methods.
Object Oriented Software Visualization Tool and its comparison

Software Visualization is the visualization of computer programs or algorithms, which is very crucial and costly process. The visualization method can be derived into six categories as Scope, Content, Form, Method, Interaction and Effectiveness. To maintain visualized software used for industry or research, are required visualization tools for enhancement of the functionality of software. Here, I am here going to discuss the way of analyzing of the available software and its documentation as new Visualization program. The effectiveness of visualization tool upon the effectiveness of other relevant tools.
Design and Development of Modern Educational Technology and High-quality Online Courses Based on Fuzzy Clustering Algorithm

With the continuous deepening of the process of education informatization, modern educational technology skills have become an important part of the professional quality of teachers, and they are the necessary qualities that every teacher should master in order to adapt to the modern education reform. As a major branch of online courses, the challenge lies in the reusability and standardization of learning resources, as well as development efficiency and other issues. In order to make the calculation simple and fast, a direct fuzzy clustering algorithm of web users and pages is given, which can classify, summarize and predict the trend of page content according to the access rules of students, guide the construction of college websites, and improve online education. Has very good practical value. The development of online distance education is one of the important means to build a lifelong learning system in the knowledge age. Based on the development principles of online courses, this paper introduces the design and development methods of modern educational technology public courses online courses combined with fuzzy clustering algorithms, and puts forward some issues that should be paid attention to in the development of the online courses.