Reviewerly/exHarmony huggingface dataset:
Does Financial Inclusion Enhance Economic Output? Evidence from North Africa

The aim of this study was to investigate the impact of two dimensions of financial inclusion -namely availability of banking services and usage of banking services- on national economic output in four North African economies; Egypt, Algeria, Tunisia and Morocco. Availability of banking services was proxied by number of commercial bank branches. Usage of banking services was proxied by the sum of outstanding deposits and outstanding loans with commercial banks. National economic output was proxied by real gross domestic product. Using panel data for the years 2004-2020, panel regression analysis results revealed significant positive effects of both, availability and usage of banking services on national economic output when no time-lagging of the predictors was used, and also when the predictors were one and two year lagged. Theoretical contributions, practical implications and study limitations are discussed.&#x0D; &#x0D; Received: 24 December 2022 / Accepted: 10 February 2023 / Published: 5 March 2023
Sarcasm Detection for Hindi English Code Mixed Twitter Data

Abstract: Twitter, Instagram have grown to be the two most popular social media sites for users to voice their opinions on a variety of subjects. The generation of such huge amounts of user data has made NLP activities like sentiment analysis and opinion mining far more important. Sarcastic statements on social media,also referred to as memes, have recently become very popular. Sarcasm challenges many NLP tasks because it flips the meaning and polarity of what the language implies. A lot of resources were developed for the English language, but this does not hold true for Hinglish In this paper we include a tweet corpus for training unique word embeddings as well as a Hinglish dataset labelled forsarcasm detection. Although there have been various attempts to categorise a text’s sentiment, there aren’t many models that can do the same when given non-English data that contains sarcasm or irony . This study compares numerous sarcasm detection methods for Hinglish data in order to determine which approach performs the best on datasets of various sizes and types. We have presented a technique that will enhance the outcomes of sarcasm recognition for Hindi- English code-mixed tweets by examining and researching the prior work.
A Survey on Intelligent Chatbot for Entertainment Recommendation

bstract: Chatbots, also called chatterbots, is a form of artificial intelligence (AI) that simulates text or voice commands and give answers accordingly. It is a computer application uses voice instructions, text dialogues, or both to mimic human communication. In order to reduce the problem of information overload, which has created a possible problem for many Internet users, it is necessary to filter, prioritize, and efficiently distribute essential information on the Internet, where the quantity of options is overwhelming. A chatbot can be employed to communicate with end users, respond to their questions, comprehend their feelings, and make suggestions that are relevant. The objective of our project is to build a chatbot that allows the user to interact with it and get movies or songs recommendation of his liking/choice. Our proposed system is a single page website which can be run on user's desktop as well as mobile and its main focus is to accurately comprehend the user's question in text or voice format and respond to the user with relevant responses. We used Natural Language Processing (NLP) to convert the human conversation in text or voice format into data that is decrypted using recurrent text and patterns and then shaped into automated answers and responses. In recommendation model, Content based filtering is used which works on the data that we take from the user. The system will suggest various movies or songs based on the user's interests, and the result will be shown to the user.
Greedy Heuristics for the Choice of the Radius of Local Concentrations in FOREL-2 Algorithm

The authors examine the problem of choosing the search radius for local concentrations in the FOREL-2 clustering algorithm with an initial number of clusters. Our approach was aimed at improving the accuracy and stability of the result, such as identifying homogeneous batches of industrial products. We examined the k-means and FOREL-2 algorithms by using normalized standard deviation test values and by valid parameter values for the problem of automatic classification of objects in a multi-dimensional space of measured parameters. For such problems, with the use of the FOREL-2 algorithm, we apply greedy heuristic procedures to select the radius of local concentrations. According to the obtained Rand index, the approach which uses the FOREL-2 algorithm demonstrated the best accuracy with a larger value of the objective function in comparison with the k-means algorithm. The accuracy and speed of the software implementation of the algorithm are quite acceptable for solving the problem of clustering electronic radio products based on test data. The use of greedy heuristics for choosing the radius of the search for local concentrations in the FOREL-2 clustering algorithm with a specified number of clusters has an advantage in the speed of exact clustering compared to the k-means algorithm that uses greedy heuristics for choosing centroids.
An Investigation of the Hybridization of DE and BFGS Algorithms

Many real-world global optimization problems are presented by a black-box model, therefore there is no information on properties of the objective function and its derivatives. Differential evolution (DE) is one of search algorithms, which demonstrates the high performance in solving global black-box optimization problems. Usually DE shows good global convergence, but it is slow in the local convergence. A local search can efficiently find a local optimum with high accuracy but cannot identify a basin of the global optimum. In the study we have proposed a hybrid of DE and the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm. In BFGS derivatives are substituted by their approximations using the finite difference method. We have tested 3 different schemes of the cooperation of DE and BFGS. Using a set of benchmark optimization problems, the experimental results have shown that the hybridization can improve the performance of the standard DE algorithm. At the same time the choice of the hybridization scheme affects the results.
Gradient Neural Dynamics Based on Modified Error Function

The present study is devoted to methods for the numerical solution to the system of equations AXB=D. In the case certain conditions are met, the classical gradient neural network (GNN) dynamics obtains fast convergence. However, if those conditions are not satisfied, solution to the equation does not exist and therefore the error function E(t):=AV(t)B-D cannot be equal to zero, which increases the CPU time required for the calculation. In this paper, the solution to the matrix equation AXB = D is studied using the novel Gradient Neural Network (GGNN) model, termed as GGNN(A,B,D). The GGNN model is developed using a gradient of the error matrix used in the development of the GNN model. The proposed method uses a novel objective function that is guaranteed to converge to zero, thus reducing the execution time of the Simulink implementation. The GGNN-based dynamical systems for computing generalized inverses are also discussed. The conducted computational experiments have shown the applicability and advantage of the developed method.
Multi-secret image sharing using the random image and Boolean operations

The sharing of personal information and private data via the Internet has increased exponentially, making it essential to protect data from unauthorized access.Numerous cryptographic techniques are used to provide data security, but these techniques have limitations and require encryption and decryption techniques with a high computation cost.To secure shared information, covert information exchange techniques have been proposed, but these schemes have high computational complexity, making them difficult to share.This paper discusses cryptographic techniques for encrypting and decrypting secrets that provide security for images transmitted over a network.In recent research, n secret images are shared among n or n+1 shared images, which poses a problem because fragmentary secret information can be reconstructed from n-1 or fewer shared images.In this paper, the proposed method employs random image and Boolean arithmetic to circumvent this issue.In this paper, we first generated n random images using the random image and XOR operation.Shared images are generated by applying XOR on random images in a sequence.This method assures that secret images cannot be reconstructed until all shared images are available.
Blockchain Technology for Supply Chain and Logistics

Blockchain technology has the potential to revolutionize the way supply chains and logistics are managed in the manufacturing industry.This technology allows for secure and transparent information sharing across a distributed network of participants, enabling greater visibility and traceability throughout the supply chain.By leveraging blockchain, manufacturers can reduce the risk of counterfeiting, ensure the authenticity of their products, and streamline supply chain operations.With a blockchain-based system, participants can track the movement of goods and materials, verify the origin and quality of products, and ensure compliance with regulations and standards.Additionally, blockchain technology can facilitate faster and more efficient transactions, reducing costs and delays associated with traditional payment and settlement processes.This can help manufacturers to optimize their supply chains, improve inventory management, and enhance customer satisfaction.Despite its potential benefits, implementing blockchain technology in the manufacturing industry can be complex, requiring significant investment in infrastructure, data management, and stakeholder engagement.This paper provides a comprehensive overview of blockchain technology in manufacturing supply chains and logistics and highlights its potential to transform how manufacturing operations are managed and optimized.
Design of Real-time Movement Guidance System Based on Blazepose on Mobile Terminal

People's daily sports and patient rehabilitation movement requires standard movement guidance, this paper puts forward a real-time movement guidance in mobile terminal system, the main function of using the camera to obtain the user movement posture, identify the current posture in the application of the category, and the current posture with the standard movement, in the user movement key body with different color grading tips, in order to prompt the user and correct the user posture.
A Strict Constrained Superposition Calculus for Graphs

Abstract We propose a superposition-based proof procedure to reason on equational first order formulas defined over graphs. First, we introduce the considered graphs that are directed labeled graphs with lists of roots standing for pins or interfaces for replacements. Then the syntax and semantics of the considered logic are defined. The formulas at hand are clause sets built on equations and disequations on graphs. Afterwards, a sound and complete proof procedure is provided, and redundancy criteria are introduced to dismiss useless clauses and improve the efficiency of the procedure. In a first step, a set of inferences rules is provided in the case of uninterpreted labels. In a second step, the proposed rules are lifted to take into account labels defined as terms interpreted in some arbitrary theory. Particular formulas of interest are Horn clauses, for which stronger redundancy criteria can be devised. Essential differences with the usual term superposition calculus are emphasized.
PROBLEM MODELING METHODS IN MATHEMATICS EDUCATION

Solving problems using different methods has always been a topical issue in the teaching of mathematics.Depending on the structure of the problem, mathematical models are widely used for students to visually master the relationships between given and sought quantities.The concept of the model in solving mathematical problems, its applications and forms have always been of interest to researchers in this field.This article considers the theoretical and practical bases of problem modeling, the requirements for them, the conditions under which the model is given, the possibility of using several models in solving a problem.Here, examples of solving specific problems related to content lines are considered, similarities and differences of these content lines in the modeling are analyzed.
Listening Comprehension Problems Faced By The Third Semester Students Of The English Language Education Study Program

The purpose of this research was to investigate students’ listening comprehension problems. The researchers used a mixed-method design. The participants were third-semester students of the English Language Education Program at Universitas Katolik Indonesia Santu Paulus Ruteng. In collecting the data, the researchers used two instruments namely survey questionnaires, and semi-structured interviews. The findings of this study revealed that the third-semester students of the English Language Education Study Program perceived some degree of listening comprehension problems. Parsing problems took 50%, utilization problems took 30%, and perception problems took 20% of listening comprehension problems faced by the third-semester students. In addition, the results of the interview revealed that mostly the students experienced listening comprehension problems due to the fast speech rate of the speakers in the recording. Another cause of their listening comprehension was the lack of vocabulary and unfamiliar topics which made them unable to comprehend the spoken texts. In conclusion, the listening difficulties encountered by the third-semester students were to due the semantics and lexical meaning of the spoken text
Educational Game as An Effort to Accelerate Learning After The Covid-19 Pandemic

The Covid-19 pandemic that occurred forced us to carry out the learning process through the internet network (online or online). Learning carried out online creates many problems, so it is considered ineffective and causes learning loss. Various methods have been taken to overcome this learning loss, including collaborating with various parties and issuing various regulations. In addition, teachers are also required to provide a new spirit in creating and innovating to provide effective, efficient, and competitive learning media. One way is to do educational game-based learning. Educational games are considered adequate for overcoming learning losses because learning media with educational games require players to participate in determining outcomes, have an entertainment side, and can increase creativity and problem-solving skills. The planned research method stages for collecting the required data are observation, interviews, and literature study. As for the development of educational games in this study, the prototype development method will be used. This study's result is that the Educational Game design has produced output that meets the needs. In future research, when this design is implemented, it is hoped that it will be an alternative medium for accelerating post-pandemic learning.
Convolutional Neural Network – Long Short Term Memory Untuk Prediksi Harga Emas Indonesia

In the economic field, gold generally has three main functions, namely the monetary function, investment and industrial functions. In the financial world, prediction of the trend of gold price fluctuations is an important issue. Convolutional neural network algorithm is one of the popular algorithms in the image classification domain. But this algorithm can also be applied to 1-dimensional problems, such as predicting the next value in a sequence, be it a time series or the next word in a sentence. In this study, the Convolutional Neural Network algorithm was optimized with long shot time memory to predict the price of Indonesian gold from 1979 to 2021 with a total of 511 records. The test was carried out with three different epoch values, namely 50, 100 and 150 with a validity test using RMSE. From the test results, the smallest RMSE train value and RMSE validation are generated at epoch 150, which is 0.0138 for RMSE train and 0.0402 for RMSE validation.
Crime Rates in the Philippines: A Comparative Analysis of Bulan and Irosin Municipalities from Sorsogon Province

The low crime rate has been identified as a predictor of a calm, orderly, and secure neighborhood. Furthermore, a safe and secure environment is essential in encouraging investment and economic progress in a country. Crime statistics can help criminal justice professionals predict increased crime risk. This study, therefore, aims to compare the crime rate of two municipalities in the province of Sorsogon: Bulan Sorsogon and Irosin Sorsogon from the calendar year 2018 to 2020. This study used document analysis to analyze and compare the crime data in the Municipality of Bulan and Irosin Sorsogon. Data reflected that in the comparison of the two municipalities in the province, the Municipality of Bulan has the highest crime rate (61%) compared to the Municipality of Irosin which has a (39%) total crime rate. Data also revealed that the crime under special law was the most numbered crime committed with (253) total in the five parameters of crime in both municipalities. Interestingly crime against property was (32) total crimes committed in both municipalities, showing a low number of crimes based on the record. Hence, the police may continue to collaborate closely with many community sectors to guarantee the seamless implementation of its programs and projects to protect public safety and security Information awareness campaigns in any form like in any platform of social media in all their programs and projects may be made available in the community to increase awareness and support of stakeholders, especially in the far-flung areas in the municipality.
The Use of Rumah Belajar as Learning Media for Elementary Teachers in Ata Dei Subdistrict, Lembata Regency, East Nusa Tenggara Province

The demands of the 4.0 industrial revolution and the implementation of blended learning as the result of the COVID-19 pandemi are very solid in educational field. Teachers are required to be able to carry out distance learning activities by utilizing various learning media which are mostly technological-based. This Community Service aims at improving the ability and or skill of elementary school teachers in Ata Dei District, Lembata Regency in utilizing technological-based media in learning activities. 25 elementary school teachers in Ata Dei District involved in this PkM. The PkM was designed in two activities namely, seminar and workshop. The seminar was carried out for 3 hours while the workshop was carried out for 3 days. In this activity, a portal launched by KEMDIKBUD namely portal Rumah Belajar was introduced. It consists of 4 features, namely the sumber belajar feature, the laboratorium maya feature, the wahana jelajah angkasa feature and the edugame feature. The impact of this activity is increasing the knowledge and skills of elementary school teachers in Ata Dei District, Lembata Regency in using the portal rumah belajar as a digital technology-based learning media whic is effective and efficient in learning activities, especially daring learning.
Game-Assisted Mathematics Learning for Kids in KBG Santa Ursula

The prolonged Covid-19 pandemic has an impact on the learning process in schools which must be abolished and replaced by learning from home. Learning from home, especially mathematics, reduces students' enthusiasm for learning and grows a sense of laziness in learning among students because they prefer to play rather than study. This also happened to students in the Santa Ursula KBG environment. With such conditions, the author uses the media of math games to help children at KBG Santa Ursula in learning mathematics. The results of the activities that have been carried out show that the use of math games increases the enthusiasm for learning and reduces the laziness of the children at the Santa Ursula KBG in learning mathematics
Medan City Tourism Geographical Information System Using Dijkstra Algorithm Method

Medan City Tourism Office in providing tourism location information is currently still using the official website that only displays explanations about tourism and mapping of tourist location points only, the current system is less efficient and makes tourists or the public not know much about the location or route to be passed and search for tourist attractions in the city of Medan. Researchers try to solve the problem by implementing a geographic information system implemented with OSM (Open Street Map). In this study, data collection using qualitative methods and applications was developed using waterfall methods. The results of the analysis will be described using UML (Unified modelling language). The results of this study show that the geographical information system of tourism to find out the location point and the nearest route can provide benefits to tourists and local people to travel in the city of Medan.
Sistem Pendukung Keputusan Menentukan Mitra Berprestasi di Halal Mart Menggunakan Metode AHP – WASPAS

PT Herbal Penawar Alwahida Indonesia, known as HNI-HPAI, is one of several companies in Indonesia as a Halal Network business that focuses on providing various quality and halal consumer goods products. With the number of partners spread throughout Indonesia, human resource management is important for the development and progress of the company. Along with its development, the selection of outstanding partners has so far been done manually, which is directly selected by the mentor from the partner and does not pay attention to the criteria. Therefore, we need a decision support system (DSS) in determining partners who excel by taking into account the weight of the criteria. That way it produces a clear and time-consuming calculation where the calculation begins to determine the variables used to calculate the value of errors or optimize the estimation or selection of the highest and lowest values.
Implementasi Metode MOORA Penentuan Pusat Perbelanjaan Terbaik Di Riau

This research has motivated by an increasing number of shopping centers that appear in the community with various offers and products. The quality of mall services and facilities determines the target audience in measuring the quality of shopping centers. The purpose of this research is to help developers improve the quality of services and more. Therefore, a Decision Support System is needed to assist the assessment process using five alternatives and seven criteria. The method used is Multi-Objective Optimization on the Ratio Analysis (MOORA) basis. The results showed that the Living World mall was chosen as the best mall in the city of Pekanbaru with a final point of 3.17.