Reviewerly/exHarmony huggingface dataset:
Simulation of Tennis Spinning Ball Flight Path Based on Fuzzy Reasoning Algorithm

Topspin is one of the most widely used hitting techniques in a tennis match and it is an effective tool to win over the opponent. Hence, flight path simulation of a spinning ball can be a tremendous analysis tool to help tennis players perfect their game. This article proposes a fuzzy logic model based on the principles of kinematics and mechanics. This study analyzes the physical characteristics of a spinning ball during the flight process, which are divided into two categories: the characteristics of the ball on impact (including the floating and rotating it causes) and the landing rebound characteristics. These two characteristics are considered as the constraints of the flight path simulation and the inputs of the fuzzy logic model. Fuzzy logic is used to fuzzify the impact and landing rebound information of the ball based on the knowledge base, solve the problem, and finally defuzzify the results into crisp outputs, that is, accurate flight trajectory. The simulation results show that the estimation error of the proposed model is lower than 3.7 cm/s and 0.9°, and the success rate of accurate topspin execution is 100%, indicating that the proposed model is effective to train tennis players.
Research on the Trading Strategy Model Between Gold and Bitcoin

In this paper, we build an autoregressive integrated moving average (ARIMA) model and analyze the short-term trends of the gold price (GP) and bitcoin price (BCP) based on historical data. In addition, we use MATLAB to perform statistics and analysis on the data, find that the probability of continuous depreciation or appreciation after day 5 decreases exponentially, and find the maximum and minimum fluctuations. Further, we build a trading strategy model that uses the Apriori algorithm to calculate the number of subsets where prices have risen or fallen for 5 consecutive days. Finally, we perform a sensitivity analysis on the established model.
Innovation and Development of Small and Medium-sized Traditional Banking Industry Based on Service Choreography Technology

In the financial services, under the tide of digital and traditional part of the small and medium-sized commercial Banks due to staff shortages, backward organization management system, such as weak information processing ability problem have to flinch, but transformation is the only way to the bank, so the small and medium-sized Banks is an urgent need to use the appropriate financial technology to complete the core business is the transformation of deposits, bank of distributed systems. The vigorous development of innovative technologies such as agency and service choreography can provide new solutions for traditional small and medium-sized banks.
The Whole and the Parts: The Minimum Description Length Principle and the A-Contrario Framework

This work explores the connections between the minimum description length (MDL) principle as developed by Rissanen, and the a-contrario framework for structure detection proposed by Desolneux, Moisan, and Morel. The MDL principle focuses on the best interpretation for the whole data while the a-contrario approach concentrates on detecting parts of the data with anomalous statistics. Although framed in different theoretical formalisms, we show that both methodologies share many common concepts and tools in their machinery and yield very similar formulations in a number of interesting scenarios ranging from simple toy examples to practical applications such as polygonal approximation of curves and line segment detection in images. We also formulate the conditions under which both approaches are formally equivalent.
Pewarnaan Titik r-Dinamis pada Graf Hasil Operasi Edge Corona

This research is a development of research on $r$-dynamic vertex coloring on simple, connected, and undirected graphs. The $r$dynamic vertex coloring on the graph $G$ is the $r$ point coloring of the $r$ graph so that the vertices of degree two on the $G$ graph have at least two different color neighbors. The $r$-dynamic vertex coloring is satisfied if it meets the conditions for $\forall v \in V(G)$, $|c(N(v))|$ $\geq$ min$\{r,d(v)\}$. The chromatic number for the $r$-dynamic vertex coloring of the graph $G$ is denoted as $\chi_r(G)$. In this study, we discuss the $r$-dynamic vertex coloring on the graph resulting from the \emph{edge corona} operation on a path graph with a complete graph, a star graph, and a sweep graph. It is denoted that the result of the operation of \emph{edge corona} graph $G$ and graph $H$ is $G \diamond H$. In this study, the results of the $r$-dynamic vertex coloring are described in the operation graph $P_n \diamond K_m$, $P_n \diamond S_m$, $P_n \diamond P_m$, and $P_n \diamond B_{(m,k)}
Konstruksi Rak Penataan Gelas Air Minum Menggunakan Hasil Deformasi Benda-Benda Geometri dan Kurva Bezier

Drinking water glass shelves are used as containers that can hold drinking water with a growing model. Drinking water glass shelves is made using thecniques which produced from deformation of geometric objects and Bezier curves. This research aims to made produces procedures for designing buffers, main shelves and more varied reliefs with one axis and three modeling axes. This research method divided into several stages. First, construct some basic objects as constituent components of drinking water glass shelves from deformation of octagonal, tube, beams, and the ball. Second, set some basic objects of the component of drinking water glass shelves two types of modeling axis. Third, arrange program using Maple 13. The results of this research obtained the procedure for designing various forms of constituent components of drinking water glass shelves from the basic object of a octagonal, tube, beams, and the ball. Furthermore, the procedure for assembling the components of drinking water glass from the first procedure result on two types of modeling axis.
THE IMPLEMENTATION OF MOBILE GAMES IN READING COMPREHENSION AT SMPN 1 BANDARLAMPUNG

This research is quantitative research. The objectives of study were to investigate the process of using mobile games in reading comprehension and to analyze how the effects of mobile games on reading comprehension of the IX grade students at SMP N 1 Bandar Lampung in ESL context. Besides, it was to find out whether students are motivated to learn ESL by using mobile phone. The subject of research was 25 students at SMPN 1 Bandar Lampung. The instrument of research was reading comprehension test. The results showed that the students enjoyed the process as they played mobile games since it could take their interest in learning English and the mobile games could give positive effect on students’ reading comprehension. In addition, students are motivated to understand the storyline of the game which then
THE EFFECT OF ANIMATION VIDEOS ON YOUNG LEARNERS’ VOCABULARY AT GRADE 4 IN SDN 2 PALAPA BANDAR LAMPUNG

A purpose of this research to determine the effect of animation video on young learners vocabulary grade 4 in SDN 2 Palapa Bandar Lampung. It was quantitative research to aime two classe were experiment and control class in using treatment five meetings. The research design used pretest to determine ability of young learners to learn English vocabulary. The population was grade IVA and IVB. The researcher chose two classes on test instrument, there were twenty five multiple choice questions to use pretest-posttest. The result before giving treatmen mean value was 69.2000 obtained by experiment class and mean value was 69.600 obtained by control class so two class had same ability level. Researcher gave posttest after it finished to give treatment and analyze of SPSS showed t-test was 0.05 English vocabulary. Mean score was 84.8000 experiment class and mean score was 77.2000 control class. There was an effect on treatment that it had been given by researcher, (.000) was lower than (&lt;0.05), and it was mean the treatment to animation videos was significant of calculation procedure, so it was calculation animation videos could improve English vocabulary of young learners and it could be recommendation as teaching media.
AN ANALYSIS OF USING INDONESIAN LANGUAGE WITH AND WITHOUT CODE-SWITCHING IN ENGLISH DEPARTMENT OF UNIVERSITAS BANDAR LAMPUNG

This study is qualitative research aiming to analyze the phenomenon of code switching in English Department Universitas Bandar Lampung. There are two questions in analyzing the phenomenon of code switching used by the students and teachers. The first question talks about how the use of Indonesian language with code switching is and the second question talks about how the use of Indonesian language without code switching is. The data of this study is gathered by using observation, questionnaires, and interview. As a result, I conclude that code switching occurs in switching the word, phrase, and sentence level. Switching the code is from Indonesian to English and vice versa. The switching also indicates that the speaker wants to emphasis the point, do not know word in a language, and they are nervous when talking in front of their classmates. In addition, without code switching there will be many hesitation and confusion of what is said. Code switching is one way to help the interlocutor to get into the communication.
Influence of Binomial Crossover on Approximation Error of Evolutionary Algorithms

Although differential evolution (DE) algorithms perform well on a large variety of complicated optimization problems, only a few theoretical studies are focused on the working principle of DE algorithms. To make the first attempt to reveal the function of binomial crossover, this paper aims to answer whether it can reduce the approximation error of evolutionary algorithms. By investigating the expected approximation error and the probability of not finding the optimum, we conduct a case study comparing two evolutionary algorithms with and without binomial crossover on two classical benchmark problems: OneMax and Deceptive. It is proven that using binomial crossover leads to the dominance of transition matrices. As a result, the algorithm with binomial crossover asymptotically outperforms that without crossover on both OneMax and Deceptive, and outperforms on OneMax, however, not on Deceptive. Furthermore, an adaptive parameter strategy is proposed which can strengthen the superiority of binomial crossover on Deceptive.
Deontic-doxastic belief revision and linear system model

OPINION article Front. Psychol., 11 August 2022Sec. Theoretical and Philosophical Psychology https://doi.org/10.3389/fpsyg.2022.948330
A Personalized Recommendation Technique for Travel Route Based on Fuzzy Consistent Matrix

Recommending travel routes for tourists has become a research hotspot in the present tourism industry. Various machine learning methods have been well studied for recommendation systems. However, the accuracy of these systems is not up to the expected levels. In order to increase the ranking accuracy, as well as, the recall rate of the recommended routes by the personalized travel recommendation algorithm, in this paper, a fuzzy consistent matrix technique is introduced for personalized travel recommendation systems. First of all, the user’s travel interest data are obtained through the fuzzy consistency matrix. Next, the user’s travel interest data are de-noised to determine the user’s preferred interest points and the coverage of the user’s interest points. Besides this, the constraints of the route recommendation systems have also become a research topic. Therefore, the proposed method also uses the fuzzy consistent matrix technology to determine the users’ similarity and classifies the personalized recommendation algorithm. Finally, a personalized travel recommendation model is constructed to comprehend the personalized travel route recommendation. The investigational outcomes, using real datasets, illustrate that when the number of routes is 5000, then the accuracy rate of the proposed method is approximately 97.21%, and the accuracy rate of the recommendation ranking is 97.54%. We also observed that when using 60 GB of data, the recall rate of the proposed method, for personalized travel recommendation routes, can reach as high as 97.59%.
Towards unified management of software capstone projects in Saudi universities: a survey-based study

Purpose Saudi universities have incorporated capstone projects in the final year of an undergraduate study. Although universities are following recommendations of the National Commission for National Commission for Academic Accreditation and Assessment (NCAAA) and Accreditation Board for Engineering and Technology (ABET), no detailed guidelines for management and assessment of capstone projects are provided by these accreditation bodies. Variation in the management and assessment practices of capstone project courses and analysis of the students' capabilities to align with industry demands, to realize Vision 2030, is challenging. This study investigates the current practices for structure definition, management and assessment criteria used for capstone project courses at undergraduate level for information technology (IT) programs at Saudi universities. Design/methodology/approach A web-based questionnaire is administered using a web service commonly used for questionnaires and polls to investigate the structure, management and assessment of capstone projects at the undergraduate level offering software engineering, computer science and information technology (SECSIT) programs. In total, 42 faculty members (with range of experience of managing/advising capstone projects from 1 to more than 10 years) from 22 Saudi universities (out of more than 30 universities offering SECSIT undergraduate programs) participated in the study. Findings The authors have identified that Saudi universities are facing challenges in the utilized process model, the distribution of work and marks, the knowledge sharing approach and the assessment scheme. To cope with these challenges, the authors recommend the use of an incremental development process, the utilization of a project-driven approach, the development of a national level digital archive and the implementation of homogeneous assessment scheme. Social implications To contribute to the national growth and to fulfill the market demand, universities are recommended to align the capstone project courses with latest technology trends. Universities must collaborate with the industry and update the structure and requirements of capstone project courses accordingly. This will further facilitate to bridge the gap between industry and academia and will develop a win–win scenario for all the stakeholders. Originality/value Although universities are committed to increase innovative capacities of their students for enabling them to contribute to economic and social growth, it is still hard to know the knowledge creation and sharing at national level. Variations in the management and assessment practices for capstone projects further intensify this challenge. Hence, there is a need of smart assessment and management of software capstone projects being developed in Saudi universities. Incorporating latest technologies, such unified management can facilitate discovering the trends and patterns related to the domain and complexity.
Cellular Automata Enhanced Machine Learning Model for Toxic Text Classification

As we know internet and social media usages are increasing day by day. Sometimes users take social media as a medium to use hateful and abusive comments that may rude and dis-respectful for others. So it is important to detect the toxicity and remove it from the social media. As social media users are in millions so it is impossible for filtering out the toxic comments manually, and hence there is a need for a method to filter out the toxic comments and make social media cleaner and safer to use. This paper aims to detect toxic comments in social media using cellular automata based LSTM (Long Short-Term Memory) model. Our approach produces 97.43% of F1_score without using any kind of pre-trained word embeddings or language models.
Recommendation in Offline Stores

With the current advancements in mobile and sensing technologies used to collect real-time data in offline stores, retailers and wholesalers have attempted to develop recommender systems to enhance sales and customer experience. However, existing studies on recommender systems have primarily focused on e-commerce platforms and other online services. They did not consider the unique features of indoor shopping in real stores such as the physical environments and objects, which significantly affect the movement and purchase behaviors of customers, thereby representing the "spatiotemporal contexts" that are critical to identifying recommendable items. In this study, we propose a gamification approach wherein a real store is emulated in a pixel world and a recurrent convolutional network is trained to learn the spatiotemporal representation of offline shopping. The superiority and advantages of our method over existing sequential recommender systems are demonstrated through a real-world application in a hypermarket. We believe that our work can significantly contribute to promoting the practice of providing recommendations in offline stores and services.
Topic-Driven Detection and Analysis of Scholarly Data

Abstract The chapter presents a topic mining approach that can used for a scholarly data analysis. The idea here is that research topics can emerge through an analysis of epistemological aspects of scholar publications that are extracted from conventional publication metadata, such as the title, the author-assigned keywords, and the abstract. As a first contribution, we provide a conceptual analysis of research topic profiling according to the peculiar behaviours/trends of a given topic along a considered time interval. As a further contribution, we define a disciplined approach and the related techniques for topic mining based on the use of publication metadata and natural language processing (NLP) tools. The approach can be employed within a variety of topic analysis issues, such as country-oriented and/or field-oriented research analysis tasks that are based on scholarly publications. In this direction, to assess the applicability of the proposed techniques for use in a real scenario, a case study analysis based on two publication datasets (one national and one worldwide) is presented.
Study on Quantum Finance Algorithm: Quantum Monte Carlo Algorithm based on European Option Pricing

As one of the major methods for the simulation of option pricing, Monte Carlo method assumes random fluctuations in the distribution of asset prices.Under certain uncertainties process, different evolution paths could be simulated so as to finally yield the expectation value of the asset price, which requires a lot of simulations to ensure the accuracy based on huge and expensive calculations.In order to solve the above computational problem, quantum Monte Carlo (QMC) has been established and applied in the relevant systems such as European call options.In this work, both MC and QM methods are adopted to simulate European call options.Based on the preparation of quantum states in QMC algorithm and the construction of quantum circuits by simulating a quantum hardware environment on a traditional computer, the amplitude estimation (AE) algorithm is found to play a secondary role in accelerating the pricing of European options.More importantly, the payoff function and the time required for the simulation in QMC method show some improvements than those in MC method.
A Top-down Method of Extraction Entity Relationship Triples and Obtaining Annotated Data

The extraction of entity relationship triples is very important to build a knowledge graph (KG), meanwhile, various entity relationship extraction algorithms are mostly based on data-driven, especially for the current popular deep learning algorithms.Therefore, obtaining a large number of accurate triples is the key to build a good KG as well as train a good entity relationship extraction algorithm.Because of business requirements, this KG's application field is determined and the experts' opinions also must be satisfied.Considering these factors we adopt the top-down method which refers to determining the data schema firstly, then filling the specific data according to the schema.The design of data schema is the top-level design of KG, and determining the data schema according to the characteristics of KG is equivalent to determining the scope of data's collection and the mode of data's organization.This method is generally suitable for the construction of domain KG.This article proposes a fast and efficient method to extract the topdown type KG's triples in social media with the help of structured data in the information box on the right side of the related encyclopedia webpage.At the same time, based on the obtained triples, a data labeling method is proposed to obtain sufficiently high-quality training data, using in various Natural Language Processing (NLP) information extraction algorithms' training.
Artificial Skylight A Novel Photovoltaic Approach For Daylight Harvesting

Daylight harvesting is an apparent way of utilizing green energy in modern buildings which leads to sustainable development. In modern days, a huge amount of energy is consumed for lighting applications. So, in this article, we approached a novel photovoltaicbased daylighting system that can replicate the sunlight into an electric light inside a room. In general, this task is dependent on a photovoltaic cell and its maximum power point tracking for maximum energy conversion/extraction (daylight to electricity). So, we have developed a unique algorithm for this task which will lead to a maximum extraction of current based on the daylight condition outside. The MPPT algorithm is controlled by a microcontroller and the output light from the system is proportionate replication of the daylight available outside the room. The microcontroller controls the boost converter duty cycle for maximum power extraction. This article consists of detailed circuit diagrams and algorithm used for this whole system. This system is capable of lighting up a series of LED luminaires from a single photovoltaic cell.
FORMATION OF CREATIVE COMPETENCE OF FUTURE DOCTORS OF PHILOSOPHY AS A PRECONDITION FOR INNOVATIVE ACTIVITIES

The article substantiates the relevance of the formation of creative competence as a prerequisite for the innovative activity of future doctors of philosophy in the context of reforming the domestic system of higher education. Various scientific approaches to the definition of the concept of «creative competence» are shown. The theoretical analysis of the essence of the creative activity of teachers is carried out. It has been proved that professional creative competence is a qualitative characteristic of the level of a specialist’s preparedness for pedagogical activity, an indicator of his professionalism as a special integrative quality of a person. The features of the functioning of the mechanism for the formation of knowledge, skills and abilities necessary for the formation of a creative personality have been determined. Models of the formation of creative dimensions of the professional development of future scientific and pedagogical workers have been substantiated. The features of the formation of creative competence among future doctors of philosophy in the study of various academic disciplines are shown. The system of indicators of achievement of creative competence is highlighted. The article describes the understanding of the readiness of teachers for innovative creative activity through a specific definition of the qualities, features, forms of creative competence. The factors influencing the effectiveness of the innovative activity of teachers have been investigated. The results of the activity on the formation of the creative competence of doctors of philosophy as areadiness for future professional pedagogical activity on the principles of innovativeness have been determined.