Reviewerly/exHarmony huggingface dataset:
Measuring the Usefulness of Machine Translation as a Reading Aid for L2 Learners: Reading Problems and L2 Proficiency

Neural machine translators (NMTs) such as Google Translate may help second language (L2) readers with general comprehension. However, previous empirical studies show mixed results regarding its usefulness. Moreover, how machine translation (MT) can assist learners of different L2 proficiency levels solve reading problems is rarely considered. In this study, high school L2 learners were asked to solve three types of reading comprehension problems (grammar judgment, inferring meaning from context, inferring main idea) under three reading conditions (no aid, MT, glossary). Overall, with MT use, reading comprehension scores were higher than in the no aid and glossary conditions. However, none of the reading aid conditions helped with grammar judgment. Only mid-proficiency learners benefited from MT in both inferring meaning from context and inferring main idea tasks. For high-proficiency learners, the effect of reading aid was not apparent in any of the problems. Interviews revealed that learners preferred MT over the glossary as it allowed them to stay on track whereas the glossary disrupted the reading process. With the omnipresence of MT as an online reference tool, L2 teachers need to consider using MT as a legitimate reading aid for different proficiency levels and reading purposes.
Evaluating Attitude Shift From Tourism Online Reviews Using Word Embedding-Based Approaches

The shift of consumers' attitudes caused by public health emergencies can be reflected in online reviews.This study applies the word embedding-based methods and sentiment propensity analysis to mine tourism online reviews.Specifically, we obtain the comprehensive vector of each review, which consists of the word vectors in the review word embedding, and evaluate the changes in tourists' emotional tendencies in the context of public health emergencies (taking COVID-19 as an example).The empirical results verify the effectiveness of the word embedding-based methods in identifying attitude shift and confirm the divergent effect of emotional valence in predicting the usefulness of tourism online reviews.
A Study on the Optimization of Text Emotional Classification Based on Class Representation Words and Naive Bayes

There is a certain similarity of the characteristic vectors of the comment statements between the comments between the commentary emotion category, bringing certain difficulties to text emotion 3 classification.This article proposes a specification of the specification.It is mainly from 8 aspects of fresh products to 8 aspects (emotional adjustment words + feature words).Add all kinds of representatives selected to a worddefined dictionary, by changing the word words in the comment statement, in turn increases the difference between the comment statement feature vector between the category during the quantization process, thereby enabling classification Easy to identify the emotional polarity of comment statements.After verification, this method achieved a good classification effect, the correct rate reached 86.14%, the recall rate reached 84.97%, which increased 4.24% and 4.42% compared to the method without dictionary.
Research on Credit Risk and Risk Management Countermeasures in the Operation of Blockchain + Supply Chain Finance

Credit risk is the main contradiction that plagues the sustainable development of blockchain + supply chain finance.The default of individual credit subjects will spread to the entire supply chain, and the credit chain will collapse, and the entire credit order will be disorder.Aiming at the credit risk problems faced by blockchain + supply chain finance, this paper gives credit risk management measures for credit risk management in the preloan access stage, loan approval stage, and post-loan management stage.Combining the application value of blockchain + supply chain finance, the relevant policy recommendations proposed in this paper include setting up a trial operation period of block chain + supply chain finance, gradually improving the trading rules, and building a risk early warning mechanism.
An Investigation to Offer Conclusive Recommendations on Suitable Benefit/Cost Criteria-Based Normalization Methods for Topsis

TOPSIS is a popular multi-criteria decision-making method that ranks the available alternatives by examining the ideal-positive and ideal-negative solutions for each decision criterion. The first step of using TOPSIS is to normalize the presence of incommensurable data in the decision matrix. There are several normalization methods, and the choice of these methods does affect TOPSIS results. As such, some efforts were made in the past to compare and recommend suitable normalization methods for TOPSIS. Sadly, such studies merely compared a limited collection of normalization methods or used a noncomprehensive procedure to evaluate each method’s suitability, leading to equivocal recommendations. This study, therefore, employed an alternate, comprehensive procedure to evaluate and recommend suitable benefit/cost criteria-based normalization methods for TOPSIS (out of ten methods extracted from past literature). The procedure was devised based on three evaluation metrics: the average Spearman’s rank correlation, average Pearson correlation, and standard deviation metrics, combined with the Borda count technique. The first study examined the suitability of ten benefit/cost criteria-based normalization methods over TOPSIS.Users should combine the maximum method II and vector method into the TOPSIS application for safer decision-making.The maximum method I and maximum method III have an identical effect on TOPSIS results.
Analisis Manajemen Keuangan Sekolah Pada Sekolah Menengah Kejuruan (SMK)

Education management itself is seen as a process needed in the world of education to achieve the goals of education itself. The purpose of this paper is to explore school financial management in Vocational High Schools (SMK), as well as to find out the effectiveness of existing financial management in schools. The school used as the object was SMK N 2 Balikpapan with research informants namely the school principal, vice principal for finance, school treasurer, and committee. Based on the research, it was found that the main source of school finance came from BOS funds. The management process begins with deliberations and holding meetings of all teachers and employees with the process of preparing the RKAS and preparing the RAB, based on the plans needed by the school which will first be considered by the School Committee. Realization of school financial management sourced from BOS funds and school committee funds in Vocational High Schools for the 2021/2022 academic year has been carried out efficiently financial While the inhibiting factor is still a lack of BOS funds and school committee funds provided to support the process of school facilities and infrastructure or in other words not in accordance with the previous plan for its realization.
The Unlimited Rulebook: Architecting the Economy Mechanics of Games

Economy mechanics involve resource management, combat, object interactions, and power progression systems in games. There is a lack of development tools to reduce their implementation cost while still being game or genre-agnostic. The Unlimited Rulebook is a reference architecture designed to fulfill this purpose, especially for games that lean heavily on self-amending rules and continuous releases. Developed using a consolidated process for reference architectures, our solution effectively reduces implementation effort in the long run in exchange for a thoughtful upfront investment to design a game system.
EVOLUTION OF NEW CHINESE POETRY CHARACTERISTICS OF FORMATION (END OF THE XIX CENTURY, BEGINNING OF THE XX CENTURY)

The socio-political changes that have taken place in the last years of the imperialism of China have also had an impact on literature. Particularly, there were some activities equal to a revolution in poetry. This process was carried out in a short period of time in several stages, sometimes successfully, sometimes unsuccessfully. Poetry has abandoned old traditions and moved closer to the people as much as possible. Despite strong opposition, the usage of bayhua, the common language of the people, did not stop spreading in poetry. Moreover, the abandonment of rhythm, rhyme, and other features of typical classical poetry became a primary goal. It was not the form of a poem, but its idea, its essence, that came to the fore, which began to undermine its artistic and aesthetic value. This article discusses the evolution of the Chinese poetry revolution and the contribution of the writers and schools that participated in it.
Larisa Avram, Anca Sevcenco &amp; Veronica Tomescu (eds.). 2021. L1 Acquisition and L2 Learning. The View from Romance (review)

Review
Diagnosa Kerusakan Motor Honda Sport Non Injeksi Metode Certainty Factor

Users of Honda motorbikes have been increasingly popular for many years, ranging from young people to adults. In general, motorbike users do not understand the damage that occurs to motorbikes and tend to hand it over to technicians without knowing whether the damage is simple or complicated to repair. With these considerations, it is necessary to make a system of tools to detect damage that occurs to motorbikes, so we need a system that can help motorbike users to overcome problems of damage that occurs to motorcycles, especially Honda Sport GL Pro, Megapro, and Tiger. A knowledge-based system for identifying motorcycle damage that is displayed using a web-based programming language. forming a decision tree and used to classify the damage into damage that most affects the motor to minor damage. Complaints are generated so that a system can be created that can help users for initial handling that occurs on motorbikes and is expected to speed up the repair of motorbikes that are classified as mild damage.
Information and communication technologies in the real kindergarten program

The development of information and communication technologies (ICT) and constant connection with the Internet, enables better performance of activities in preschool institutions, based on new educational interactive programs. The paper examines the way in which ICT as a means of educational work has positive effects on child development in the real kindergarten program. The authors of the paper searched the Internet for free resources, which can be used in the function of raising the quality of educational work. Using some of the found resources, the authors independently designed content for the development of concepts about insects and wild animals, which in their opinion, can be applied in a certain way, to improve and modernize practice in accordance with the principles of preschool education.
Гамма каротажийн диаграммыг ашиглан нүүрсэн дэх ураны хэмжээг үнэлэх нь

This paper discusses how estimating the uranium concentration on coal seam by the natural gamma ray togging curves of coal deposit.
Decision Support System for Selecting Tourist Object in Surabaya City Using Simple Additive Weighting Based on Android

&#x0D; In this Final Project will be discussed regarding the implementation of the Attraction Decision Support System in Surabaya using Simple Additive Weighting. The problem to be taken is to get the best results from 50 attractions in the city of Surabaya based on the user's location by using an Android-based operating system, to make it easier for users to access this application. To obtain the value of distance criteria, this application uses the Haversine formula. The results of the study of the decision support system application for the selection of attractions in the city of Surabaya using the Simple Additive Weighting method is the highest value obtained from attractions based on the user's location with weights for each criterion especially the distance criteria which has a weight of 0.3. &#x0D;
THE EFFECT OF THE PARTNERS READING STRATEGY ON THE ACHIEVEMENT OF READING BY TH

The current research aims to find out the effect of the partner's reading strategy on reading material achievement among third-grade primary students.The research sample consisted of (70) students after excluding students who had failed from the Arab Raya School of the General Directorate of Education in Baghdad, Rusafa IIfor the academic year 2019-2020.In the light of the research results, the researcher can conclude the following: The use of a partnership reading strategy in teaching reading to grade 3 primary school leads to an increase in reading achievement in a cooperative learning situation among students to achieve participation and persistence in discovering and acquiring knowledge, explaining it and comparing it to their perceptions and prior knowledge to teach learn and acquire new information and apply it to the life situations they face.
Dataset: Digital Forensics and Artificial Intelligence: A Decade of Progress and Trends (2012-2022)

This data article aims to streamline research on Digital Forensics and Artificial Intelligence by providing a comprehensive dataset derived from Lens.org. Using a three-step filtering process based on document type, publication date range, and subject matter, a total of 76 articles published between 2012 and 2022 were extracted. The analysis revealed that the University of Lausanne was the top institution, computer science was the dominant field of study, and the United Kingdom was the most active region in this domain. This dataset is valuable for researchers and practitioners seeking insights into the digital forensics and artificial intelligence landscape.&#x0D; Highlights:&#x0D; &#x0D; Comprehensive dataset of 76 articles in digital forensics and artificial intelligence from 2012 to 2022.&#x0D; Analysis reveals top institutions, fields of study, and most active regions in the domain.&#x0D; Valuable resource for researchers seeking insights into the digital forensics and AI landscape.&#x0D; &#x0D;
LITERATURE REVIEW MOTIVATION AND PERFORMANCE DETERMINATION: TRAINING ANALYSIS AND PERFORMANCE ASSESSMENT

Previous and relevant research has a great influence on the research to be carried out. Previous research serves to strengthen the theory of the relationship between variables. This pre-research was conducted with the aim of building a hypothesis with a descriptive method. This pre-research aims to determine the effect of the variables, namely training and performance appraisal, on motivation and performance. The results of this library research are: 1) Training has an effect on motivation; 2) Rating k performance has an effect on motivation; 3) Training has an effect on performance; 4) Rating k performance affects performance; and 5) Motivation has an effect on performance .
AI Empowered IoT for Sustainable Energy Technologies

Sustainable energy technologies are advantageous for a company to enhance their performance significantly. Brand value and brand equity of a firm is managed by this AI process in IoT framework. In this study, the role of AI in IoT is discussed briefly. Importance of IoT framework is also mentioned in this study. Machine learning is enhanced by a firm to enhance their performance globally. In this study, qualitative research design is used by a researcher to gain in depth knowledge and information related to this study. Researcher follows a secondary research type to collect existing data from several types of journals. Benefits of these sustainable energy resources are to reduce energy spending, minimise carbon emission and maintain a green energy framework in workplace. Several types of sustainable energy sources are critically mentioned in this study. A company always tries to reduce usage of carbon footprint and inorganic products during working hours. For this reason, sustainability and environmental factors are maintained by a company significantly. Photovoltaic systems are controlled by a company with help of applications of AI technology in IoT process. Modern technology is effectively beneficial for a company to earn more profit from market. Keyword : AI, IoT, sustainable energy, technology
A Study on Resource Management Techniques in Cloud Computing

This study is based on the “resource management techniques” in cloud computing and this study has been filled with valid and authentic insights which have been collected to evaluate the subject matter. At the beginning of this study, the concept of cloud counting has been clarified and then its importance has been shown within a proper manner. By showcasing the concept of cloud computing, a generic awareness has been developed that to retain all types of crucial files, it is important to develop cloud storage within any sort of system. Also, there are several types of “resource management techniques” that have been depicted with the help of collecting crucial insights which are related with the help of gathering valid and authentic insights. Also, there are some important materials and methods and in this study, secondary data has been collected by following an inductive approach and also, qualitative research design has been chosen and implemented to bring betterment in the study. The resources have been collected from peer reviewed journals which consist of the information based on cloud computing, “resource management techniques” and cloud resource management. Also, several challenges of using resources management techniques within cloud computing with the help of crucial and effective insights have been depicted. Keyword : Cloud computing, resource management, techniques.
Understanding Post-hoc Explainers: The Case of Anchors

In many scenarios, the interpretability of machine learning models is a highly required but difficult task. To explain the individual predictions of such models, local model-agnostic approaches have been proposed. However, the process generating the explanations can be, for a user, as mysterious as the prediction to be explained. Furthermore, interpretability methods frequently lack theoretical guarantees, and their behavior on simple models is frequently unknown. While it is difficult, if not impossible, to ensure that an explainer behaves as expected on a cutting-edge model, we can at least ensure that everything works on simple, already interpretable models. In this paper, we present a theoretical analysis of Anchors (Ribeiro et al., 2018): a popular rule-based interpretability method that highlights a small set of words to explain a text classifier's decision. After formalizing its algorithm and providing useful insights, we demonstrate mathematically that Anchors produces meaningful results when used with linear text classifiers on top of a TF-IDF vectorization. We believe that our analysis framework can aid in the development of new explainability methods based on solid theoretical foundations.
Contextual Trust

Trust is an important aspect of human life. It provides instrumental value in allowing us to collaborate on and defer actions to others, and intrinsic value in our intimate relationships with romantic partners, family, and friends. In this paper I examine the nature of trust from a philosophical perspective. Specifically I propose to view trust as a context-sensitive state in a manner that will be made precise. The contribution of this paper is threefold. First, I make the simple observation that an individual's trust is typically both action- and context-sensitive. Action-sensitivity means that trust may obtain between a given truster and trustee for only certain actions. Context-sensitivity means that trust may obtain between a given truster and trustee, regarding the same action, in some conditions and not others. I also opine about what kinds of things may play the role of the truster, trustee, and action. Second, I advance a theory for the nature of contextual trust. I propose that the answer to "What does it mean for $A$ to trust $B$ to do $X$ in context $C$?" has two conditions. First, $A$ must take $B$'s doing $X$ as a means towards one of $A$'s ends. Second, $A$ must adopt an unquestioning attitude concerning $B$'s doing $X$ in context $C$. This unquestioning attitude is similar to the attitude introduced in Nguyen 2021. Finally, we explore how contextual trust can help us make sense of trust in general non-interpersonal settings, notably that of artificial intelligence (AI) systems. The field of Explainable Artificial Intelligence (XAI) assigns paramount importance to the problem of user trust in opaque computational models, yet does little to give trust diagnostic or even conceptual criteria. I propose that contextual trust is a natural fit for the task by illustrating that model transparency and explainability map nicely into our construction of the contexts $C$.
Applying unsupervised keyphrase methods on concepts extracted from discharge sheets

Clinical notes containing valuable patient information are written by different health care providers with various scientific levels and writing styles. It might be helpful for clinicians and researchers to understand what information is essential when dealing with extensive electronic medical records. Entities recognizing and mapping them to standard terminologies is crucial in reducing ambiguity in processing clinical notes. Although named entity recognition and entity linking are critical steps in clinical natural language processing, they can also result in the production of repetitive and low-value concepts. In other hand, all parts of a clinical text do not share the same importance or content in predicting the patient's condition. As a result, it is necessary to identify the section in which each content is recorded and also to identify key concepts to extract meaning from clinical texts. In this study, these challenges have been addressed by using clinical natural language processing techniques. In addition, in order to identify key concepts, a set of popular unsupervised key phrase extraction methods has been verified and evaluated. Considering that most of the clinical concepts are in the form of multi-word expressions and their accurate identification requires the user to specify n-gram range, we have proposed a shortcut method to preserve the structure of the expression based on TF-IDF. In order to evaluate the pre-processing method and select the concepts, we have designed two types of downstream tasks (multiple and binary classification) using the capabilities of transformer-based models. The obtained results show the superiority of proposed method in combination with SciBERT model, also offer an insight into the efficacy of general extracting essential phrase methods for clinical notes.