Reviewerly/exHarmony huggingface dataset:
Same or Different? Diff-Vectors for Authorship Analysis

In this article, we investigate the effects on authorship identification tasks (including authorship verification, closed-set authorship attribution, and closed-set and open-set same-author verification) of a fundamental shift in how to conceive the vectorial representations of documents that are given as input to a supervised learner. In “classic” authorship analysis, a feature vector represents a document, the value of a feature represents (an increasing function of) the relative frequency of the feature in the document, and the class label represents the author of the document. We instead investigate the situation in which a feature vector represents an unordered pair of documents, the value of a feature represents the absolute difference in the relative frequencies (or increasing functions thereof) of the feature in the two documents, and the class label indicates whether the two documents are from the same author or not. This latter (learner-independent) type of representation has been occasionally used before, but has never been studied systematically. We argue that it is advantageous, and that, in some cases (e.g., authorship verification), it provides a much larger quantity of information to the training process than the standard representation. The experiments that we carry out on several publicly available datasets (among which one that we here make available for the first time) show that feature vectors representing pairs of documents (that we here call Diff-Vectors ) bring about systematic improvements in the effectiveness of authorship identification tasks, and especially so when training data are scarce (as it is often the case in real-life authorship identification scenarios). Our experiments tackle same-author verification, authorship verification, and closed-set authorship attribution; while DVs are naturally geared for solving the 1st, we also provide two novel methods for solving the 2nd and 3rd that use a solver for the 1st as a building block. The code to reproduce our experiments is open-source and available online. 1
Construction cost prediction system based on Random Forest optimized by the Bird Swarm Algorithm

&lt;abstract&gt; &lt;p&gt;Predicting construction costs often involves disadvantages, such as low prediction accuracy, poor promotion value and unfavorable efficiency, owing to the complex composition of construction projects, a large number of personnel, long working periods and high levels of uncertainty. To address these concerns, a prediction index system and a prediction model were developed. First, the factors influencing construction cost were first identified, a prediction index system including 14 secondary indexes was constructed and the methods of obtaining data were presented elaborately. A prediction model based on the Random Forest (RF) algorithm was then constructed. Bird Swarm Algorithm (BSA) was used to optimize RF parameters and thereby avoid the effect of the random selection of RF parameters on prediction accuracy. Finally, the engineering data of a construction company in Xinyu, China were selected as a case study. The case study showed that the maximum relative error of the proposed model was only 1.24%, which met the requirements of engineering practice. For the selected cases, the minimum prediction index system that met the requirement of prediction accuracy included 11 secondary indexes. Compared with classical metaheuristic optimization algorithms (Particle Swarm Optimization, Genetic Algorithms, Tabu Search, Simulated Annealing, Ant Colony Optimization, Differential Evolution and Artificial Fish School), BSA could more quickly determine the optimal combination of calculation parameters, on average. Compared with the classical and latest forecasting methods (Back Propagation Neural Network, Support Vector Machines, Stacked Auto-Encoders and Extreme Learning Machine), the proposed model exhibited higher forecasting accuracy and efficiency. The prediction model proposed in this study could better support the prediction of construction cost, and the prediction results provided a basis for optimizing the cost management of construction projects.&lt;/p&gt; &lt;/abstract&gt;
The Use of A Collaborative Learning Strategy of Think-Pair-Share by Listening to An English Dialogues to Improve Learning Outcomes

This study aims to improve cadet learning outcomes through the application of cooperative learning model. The subject of this study is a cadet of the TPS study program batch 58 of the Jakarta Technical University of Fisheries for the 2022/2023 academic year. This class consists of 39 cadets with a cadet composition, namely 10 female cadets and 19 male cadets. This cadet was chosen as a research subject because this cadet has a low ability to understand listening before. The object of this study is the result of learning to listen to short English dialogues. The location of this research is in the class of cadets of the TPS study program batch 58 of the Jakarta Fisheries Polytechnic. The study was based on preliminary observations that indicated cadets had problems listening. In accordance with the purpose of this study, which is to improve learning outcomes in listening, this research was carried out in the form of classroom action research. This class action research is described in a cyclical or spiral process consisting of several steps, namely planning, action, observation, and reflection. This class action research is carried out in 2 cycles. Each cycle consists of three sessions of which two sessions are for action and one session for testing. The results of this study showed that the learning outcomes of listening to cadets increased by applying the Think Pair Share (TPS) type or cooperative learning model. This can be seen from the average score of cadets in the test. The average score of cadets in the pre-test was 48.27. Then it increased to 72.75 in cycle I (one). This result is not satisfactory because it has not met the completeness criteria that have been targeted by researchers. The results of cadet scores increased after researchers modified teaching and learning activities in cycle II. As a result, the average score of cadets has increased to 86.20 and 93% of cadets have achieved learning completion, which means that it has exceeded the target of 75%. It can be concluded that the application of the cooperative learning model can improve the listening ability of cadets from the results of the study.
Research on the Curriculum Reform of Exploration on "Water Conservancy Engineering Construction" under the Guidance of Industry-University-Research

The essence of industry-university-research is close cooperation between schools and enterprises, promoting learning through industry and nurturing industry through research.How to cultivate composite talents that meet the employment standards of enterprises in the new era has become the problem.This article starts with the current situation of industry-university-research in various universities, and analyzes the ways and methods of integrating industry-university-research.By analyzing the teaching process of the compulsory course "Water Conservancy Engineering Construction" for the major of water conservancy and hydropower engineering, the existing problems of the course are analyzed from three aspects: curriculum system and teaching content, training mechanism and faculty, teaching ideology and performance evaluation.The purpose of industryuniversity-research is further clarified, and a curriculum reform method that is consistent with the needs of the times and deepens the integration of industry-university-research is proposed, in order to implement the plan to promote professional talent cultivation as soon as possible, Building a distinctive path with water conservancy characteristics.
Strategies for the Curriculum Reform of Psychological Well-being Education for University Students

Due to the rapid growth of society and the increasing pressure of study and competition, the frequency of university students' psychological problems has gradually increased.In recent years, university students' psychological well-being education courses have gradually attracted social attention.How to scientifically construct the teaching of university students' psychological well-being education, improve the efficiency of university students' psychological well-being education, do a good job in university students' psychological well-being education and improve their psychological quality has become one of the problems that universities need to focus on.In order to encourage students to correctly identify information and obtain healthy psychological development, universities should pay more attention to students' psychological well-being, establish a new curriculum model of psychological well-being education with the cooperation of many parties, innovate instructional methods and promote the reform of curriculum teaching.This paper analyzes the problems existing in the course of university students' psychological well-being education, discusses the psychological development characteristics of contemporary university students from the perspective of positive psychology, and tries to construct a long-term mechanism to adapt to contemporary university students' psychological well-being education.
Method of generating roughening paths for shoe soles based on monocular encoded structured light

Abstract In this paper, we propose a monocular encoded structured light-based path generation method for sole roughening, and the obtained paths are used to guide a six-degree-of-freedom (DOF) robot for automatic roughening, which greatly improves the quality and efficiency of roughening. First, we selected monocular structured light as the vision system. To improve the calibration and reconstruction accuracy of the projector, we used an improved Three-Wavelength Phase-Shift Profilometry technique (TWPSP) to calibrate the projector, and the accuracy was improved by 26.29% compared with the conventional method. Then, we proposed a Three Coordinate Scanning Weighted-Principal Component Analysis (TCSW-PCA) algorithm as the path planning system. The experimental results show that the six-DOF-robot can automatically roughen different types of soles according to the generated roughening paths, and the processing efficiency and finished product quality of our proposed method of automatic roughening are better than other roughening methods, with an average improvement of 42% in roughening effect and an average improvement of 30.52% in roughness.
The Relation of Methodology and Methods in Social Research

The academic community has varying perspectives on the definition of methodology.Many scholars consider methodology encompassing the systematic and theoretical analysis of methods and principles within a specific field of study.It serves as a guide for researchers in scientifically validating the information used in their research.There has been a noticeable shift in the understanding of methodology in recent years, particularly in publications since 2000.Scholars argue that research should not be confined to a strict dichotomy between qualitative and quantitative approaches.The dichotomy needs to be deemed sufficient to meet the demands of modern research and calls for a synthesis of methods.This new approach is referred to as "trichotomy," with the "mixed method" being the emerging methodology for conducting research that combines elements of both qualitative and quantitative methods.Integrating these methodologies aims to enhance the quality and efficacy of research.This study explores early career researchers' challenges, including the dichotomy between qualitative and quantitative research methodologies and the utilization of mixed methods.Furthermore, the existing research literature was examined, and it is argued that discussions on research methods in academic texts and university courses should incorporate mixed methods and address the perceived dichotomy between qualitative and quantitative research methodologies.
Research on the Construction of Heterogeneous Resource Data Relation Extraction System Based on Computer Knowledge Graph

In this paper, multi-source heterogeneous online review data is used to construct a knowledge graph framework. The pattern layer constructs the conceptual framework of knowledge map by centering on the information source, content and form of online reviews. word2vec is used to obtain entities, relationships and attributes from heterogeneous texts, and data fusion and knowledge graph analysis are carried out. A two-stage knowledge graph model construction method is proposed to solve the multi-chain knowledge graph model of service value chain. The system realizes the storage of knowledge graph. Finally, the effectiveness of the knowledge map for online review research and mining is verified systematically. The results reveal the characteristics of multi-source heterogeneous online review data.
Comparison of Memory-less and Memory-based Models for Short-Term Solar Irradiance Forecasting

The world's energy consumption is continuously rising due to rapidly growing human population and expanding industrial sector. Integrating Renewable Energy Resources (RERs) with the power system comes up with severe challenges as the nature of these resources is intermittent. Among RERs, solar energy is a viable means of producing power. However, due to the intermittent nature of solar energy, accurate forecasting is necessary for smooth operation of power systems. The operational applications such as load balancing and economic dispatch can be facilitated and made more effective using very short-term forecasting. Therefore, this study proposes a memory-less third-order Markov model for very short-term solar irradiance forecasting. The proposed model uses the Random Forest (RF) for dimensionality reduction and model performance is evaluated using Root Mean Square Error (RMSE), Mean Square Error (MSE) and Normalized Root Mean Square Error (NRMSE). The results are compared with the existing Long-Short Term Memory (LSTM). The 3rd-order MC outperforms LSTM model. In terms of NRMSE, an improvement of 40.5%, 39.9% and 63.4% is recorded for the datasets of three Pakistani cities, Islamabad Karachi and Lahore, respectively.
Entanglement properties of a quantum-dot biexciton cascade in a chiral nanophotonic waveguide

We analyse the entanglement properties of deterministic path-entangled photonic states generated by coupling the emission of a quantum-dot biexciton cascade to a chiral nanophotonic waveguide, as implemented by {\O}stfeldt et al. [PRX Quantum 3, 020363 (2022)]. We model the degree of entanglement through the concurrence of the two-photon entangled state in the presence of realistic experimental imperfections. The model accounts for imperfect chiral emitter-photon interactions in the waveguide and the asymmetric coupling of the exciton levels introduced by fine-structure splitting along with time-jitter in the detection of photons. The analysis shows that the approach offers a promising platform for deterministically generating entanglement in integrated nanophotonic systems in the presence of realistic experimental imperfections.
Post-COVID-19 Impact on the Oman Tourism Market: Coping Strategies of the Hospitality Sector in Dhofar Governorate

The COVID-19 pandemic spread rapidly worldwide. The tourism industry has suffered deep losses that have profoundly impacted attracting tourists and services offered, where many hotels are temporarily or permanently closed. This exploratory study has been conducted to study the impact of the pandemic on the hospitality sector in Oman. It contributes to the literature by providing new managerial insights and perspectives on the management of hotels during crises. Employing a case study approach supported by qualitative analysis, the study investigated the experiences of hotel managers in coping with challenges presented by the pandemic, the benefits of government support programs, employee retention, and adopting revenues and cost-saving strategies during the crisis. The study collected authentic opinions through semi-structured interviews with hotel managers in the Dhofar region (Oman). The analysis revealed that hotel managers suffered from several issues (challenges): stress, shortage of employees, financial losses (e.g., liquidity problems), closures, reopening, and difficulties adapting to change. This study emphasizes coping strategies to mitigate the onslaught of the COVID-19 crisis, which the tourism industry encountered amid the pandemic and post-pandemic. The study also provides suggestions that hotel managers, in collaboration with government officials, need to set up more support programs that will address the challenges faced by the hospitality sector, which is the crux of this research.
A MODEL FOR PREDICTING SCHOOL READINESS USING DATA MINING TECHNIQUES

Study the school readiness is an interesting domain that has attracted the attention of the public and private sectors in education.Researchers have developed some techniques for assessing the readiness of preschool kids to start school.Here we benefit from an integrated approach which combines data mining and social network analysis towards a robust solution.The main objective of this study is to explore the socio-demographic variables (age, gender, parents' education, parents' work status, and class and neighborhood peers influence, Supportive Family, Health Status, Family Problems, Motivation, Family Problems, Gaming Devices, Sleeping quality, School Support, Extended Family Support) and Average Marks, data that may impact the school readiness.This paper proposes to apply three models of Data Mining Techniques using R and Python Script Languages to predict school readiness.Real data on 148 Primary School children was used from Life school for Creativity and Excellence a private school located in Ramah village, and white-box classification, clustering and association methods, such as induction rules were employed.Experiments attempt to improve their accuracy for predicting which children might fail or dropout by first, using all the available attributes; next, selecting the best attributes; and finally, rebalancing data and using cost sensitive classification.The outcomes have been compared and the models with the best results are shown.
The Concept Of Management And Utilization Of The Islamic Education Budget At SD Islam Al Maarif 01 Singosari

Education funding is a fundamental factor in the implementation of education because it is related to the use of the budget or operational financing as a whole. In financing Islamic education, an even and balanced concept is needed which must be considered in managing the budget. This research aims to analyze the concept of management and utilization of the Islamic education financing budget at Al Maarif 01 Singgosari Islamic Elementary School, Malang district. The approach uses descriptive qualitative data collection techniques in the form of field observations, interviews, and documentation related to the administration of management and utilization of the budget in the education unit. The research results show that the management and utilization of the education budget have been adjusted to the technical guidelines (JUKNIS) that have been set. Management of the education budget at Al Maarif 01 Singgosari Islamic Elementary School has been carried out by the concept of Islamic education financing management which begins with financial planning (budgeting) through a financial budgeting process that is carried out the stages in a systematic manner and considers balance and equity in the aspects subject to the budget. The process of financial oversight begins with compiling a RAPBS that has been adapted to the needs of the school. Supporting and inhibiting factors in managing Islamic education financing at Al Maarif 01 Singosari Islamic Elementary School, namely: (1) The school has the right to arrange operational and non-operational financing according to needs, (2) Everything related to reporting is the personal responsibility of the financial manager ( school treasurers) and school principals who are assisted by operators (3) utilization of funding sources from the government in the form of BOS (School Operational Assistance) and BOSDA (Regional School Operational Assistance) is still not optimal and evenly distributed because the disbursement of funds within three months and less on time and (4) committee contributions in the form of tuition fees are still not current so parents need to be more aware of and play a role in financing education. Keywords: Management, Budget, Islamic Education
Plus Token and investor searching behaviour – A cryptocurrency Ponzi scheme

Abstract In July 2020, the Chinese government warned that the Plus Token was a Ponzi scheme based on blockchain. More than 200 million investors were involved in this scam. We investigate how investors' search behaviour is associated with their decision making. We find that the bitcoin bag of words Baidu index is positively and significantly related to bitcoins transferred to Plus Token addresses, suggesting that public prominence of searches about bitcoin and blockchain tends to be related to investor decisions regarding the Plus Token project.
Research on asphalt materials based on machine vision and generate adversarial networks

With the rapid development of artificial intelligence and deep learning, computer vision-oriented generative models have been widely used. Among them, the generation of adversarial network has the most far-reaching influence. To solve the problem of dynamic instability in the training of generative adversarial networks, this paper proposes a rapid construction method of generative adversarial networks based on hidden layer characterization. The generation process of the adversarial network is divided into two independent generation processes to generate the representation of the experience hidden layer and the final result respectively, so as to stably generate the training dynamics of the adversarial network and capture more data patterns. This method can effectively and stably generate the training dynamics of the adversarial network. Finally, theoretical analysis proves that this method can stably generate the training dynamics of adversarial network and reduce the difficulty of adversarial training. Large-scale experiments on multiple data sets demonstrate the effectiveness of the proposed method.
An Analysis of the Effect of Self-directed Grammar Learning Model with the DDL on Middle School Students’ Grammar Competency

The purpose of this study is to investigate the effect of the self-directed grammar learning model on middle school students’ grammar comprehension and its application. The subject of study is 122 1st-grade students in G middle school, 61 of whom participate in self-directed grammar learning lessons and the rest in lecture-style grammar lessons. As research tools a diagnostic test, formative tests, and summative tests were administered and the collected data was analyzed through SPSS 25.0. Also, teacher logs, class observation reports from 3 teachers, and interviews with the students were employed to explore a variety of perspectives on the two different lesson styles. The result of this study showed that the self-directed grammar learning model has a positive influence on middle school students’ grammar comprehension and its practical use. According to data collected, students who took self-directed grammar learning lessons have experienced great improvement in their grammar comprehension and its practical use skills. However, comparing the test results of the control group and the experiment group, it is shown that there is not a significant grammar competency difference between the two groups where one was in lecture-style grammar lessons and the other in self-directed grammar learning lessons, respectively.