Reviewerly/exHarmony huggingface dataset:
Quantum computing for production planning

This research investigates the potential of quantum computing in production planning and addresses the limitations of conventional computing approaches. Traditional methods have been partially effective, but they struggle to solve complex optimization problems, accurately predict demand, and manage supply chains efficiently. The unique computational capabilities of quantum computing offer promising solutions to surmount these obstacles and revolutionize production planning processes. This study seeks to bridge the gap between quantum computing and production planning by analyzing the benefits, limitations, and challenges of its applicability in this field. It proposes customized algorithms and methodologies for leveraging quantum computation to enhance production planning efficiency, cost reduction, and decision-making processes. The research demonstrates the potential of quantum algorithms to minimize total production costs while appeasing demand and resource constraints through a numerical example and mathematical formulation. The results emphasize the advantages of quantum computing in terms of cost reduction, enhanced efficiency, and scalability. Comparisons with conventional methods illuminate the benefits and drawbacks of quantum computing in production planning. This research contributes to the development of novel strategies to improve production planning efficiency, lower costs, and enhance decision-making processes, allowing organizations to leverage quantum computing for optimized production operations
Multi-objective metaheuristic optimization algorithms for wrapper-based feature selection: a literature survey

In the data mining and machine learning (ML) discipline, feature selection problem is considered among many researchers in the recent times. Feature selection process targets to minimize feature set number and maximize performance accuracy by identifying optimal features. Multiple objectives are considered while identifying the optimal feature hence multi-objective metaheuristic optimization algorithms (MOMOAs) are applied. In this study, literature review is performed MOMOAs-for solving wrapper feature selection problem (WFS). The literature review for solving WFS problem and discuss the challenges faced by the researchers in solving the feature selection problem. The literature review is performed on all relevant studies published in the last 12 years [2009-2022]. A detailed overview of the feature selection preliminaries, MOMOAs-WFS, role of the classifier in feature selection problem are presented. The outcome of this literature review is to highlight the existing works related to WFS problem using MOMOAs. Finally, the research areas for improvement are identified and emphasized for the scientists to survey in the field of MOMOAs.
The Effect of Class Imbalance Handling on Datasets Toward Classification Algorithm Performance

Class imbalance is a condition where the amount of data in the minority class is smaller than that of the majority class. The impact of the class imbalance in the dataset is the occurrence of minority class misclassification, so it can affect classification performance. Various approaches have been taken to deal with the problem of class imbalances such as the data level approach, algorithmic level approach, and cost-sensitive learning. At the data level, one of the methods used is to apply the sampling method. In this study, the ADASYN, SMOTE, and SMOTE-ENN sampling methods were used to deal with the problem of class imbalance combined with the AdaBoost, K-Nearest Neighbor, and Random Forest classification algorithms. The purpose of this study was to determine the effect of handling class imbalances on the dataset on classification performance. The tests were carried out on five datasets and based on the results of the classification the integration of the ADASYN and Random Forest methods gave better results compared to other model schemes. The criteria used to evaluate include accuracy, precision, true positive rate, true negative rate, and g-mean score. The results of the classification of the integration of the ADASYN and Random Forest methods gave 5% to 10% better than other models.
Scope and financial impact of unpublished data and unused samples among U.S. academic and government researchers

Unpublished data and unused samples are common byproducts of research activity, but little is known about the scope and economic impact of their disuse. To fill this knowledge gap, we collected self-reported anonymous survey responses from 301 academic and government scientists from randomly selected institutions. Respondents estimated that they published ∼60% of their data and 95% had unpublished data. Of those collecting specimens, 60% stored unused samples. Systemic and logistical issues were identified as major contributory factors. The median cumulative self-reported estimated value of unused resources per researcher was $28,857, with life science ($36k) and government ($109k) researchers reporting the costliest assets. Using NSF headcounts, we estimated that the current cumulative value of unused resources at universities is approximately $6.2 billion, about 7% of the current annual R&D budget. These findings provide actionable information that can be used by decision makers to reduce obstacles that undermine scientific progress and productivity.
Sentiment Manifestation of Kannada Tweets

In the current world scenario, Internet has become a major platform for online learning, exchanging ideas and sharing opinions. Social networking sites like Twitter, Facebook, Instagram are rapidly gaining popularity as they allow people to share and express their views about topics, have discussion with different communities, or post messages across the world. The main goal of sentiment analysis is to detect and analyse attitude, opinions or sentiments in the text. Sentiment analysis has reached its popularity by extracting knowledge from huge amount data present online. The Process of analysis includes selecting features and opinion which is a challenging task in languages other than English. In this project, we have targeted one of the most promising and widely used social media platform- Twitter where opinions are shared as “Tweets”. We have specifically chosen the tweets made in Kannada and analyse the sentiment of those tweets. Kannada is a Dravidian language spoken majorly in the south Indian state of Karnataka, with minorities in all neighboring states. Emotion analysis is the method of defining and evaluating the emotions conveyed in textual data. Emotion detection and classification are straightforward tasks that can be completed based on the emotions conveyed in the text, such as fear, rage, happiness, sorrow, affection, motivation, or neutral.
An Interpretable Prediction Model for Stroke Based on XGBoost and SHAP

Objective: To establish a stroke prediction and feature analysis model integrating XGBoost and SHAP to aid the clinical diagnosis and prevention of stroke. Methods: Based on the open data set on Kaggle, with the help of data preprocessing and grid parameter optimization, an interpretable stroke risk prediction model was established by integrating XGBoost and SHAP and an explanatory analysis of risk factors was performed. Results: The XGBoost model’s accuracy, sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve (AUC) were 96.71%, 93.83%, 99.59%, and 99.19%, respectively. Our explanatory analysis showed that age, type of residence, and history of hypertension were key factors affecting the incidence of stroke. Conclusion: Based on the data set, our analysis showed that the established model can be used to identify stroke, and our explanatory analysis based on SHAP increases the transparency of the model and facilitates medical practitioners to analyze the reliability of the model.
Security by Design

The security should be an area that can cover multiple technical disciplines that needs to be focused on customers and to try protecting against different threats. There can be multiple disciplines that can be part of the security and those can be: assurance, anti-tamper and information assurance and cybersecurity. Security must be taken into consideration throughout the entire product lifecycle in order to maximize the protection of a system. The purpose of this article is to highlight design security flaws which should always be considered as part of the design flow for an application or a product. The recommendations can be applied in combination with different methodologies, depending on what the company chooses to use, wheatear it is Agile or Waterfall. Principle of security by design will be tackled within the article.
Impact of Motivation Factors on the Employees of Airlines Industry

Employees play pivotal role in shaping the accomplishment expansion and even downfall of an organization. Hence there is a need for proper motivation of the employees so that they feel instigated and energized in their task that paves the way for the betterment of the organization. This analysis will predict the potency and efficacy of Human Resource Management approach and methodologies adopted by Human Resource Management of the Airlines Industries to persuade rather influencing their employees thus bestowing them with prolificacy and self -contentment about their job. The study focuses on the action performed by Human Resource Management in stimulating the employees and recognizing several workers inspiration factors for the development of a superior organization. No matter whatever may be the circumstances ,there is consistently and invariably its necessary and high demand for the commitment of the staffs in Airlines Industry. Employee Motivation is of foremost important concern that affect the performance level of employees in Aviation Industry. The main concern of this research work is to bring into lime light the various facets that helps in stir up and dynamize the spirit of the employees , so that they can never feel pressurized by their work load and enjoy every bit of their job to the optimum.
Implementation of a Continuous Integration and Deployment Pipeline for Containerized Applications in Amazon Web Services Using Jenkins

This project focuses on streamlining the software development process by integrating various tools and automating key tasks. Developers contribute code changes to a Git repository hosted on GitHub. These changes trigger Jenkins, a continuous integration and delivery tool, to build the code using Maven, a build automation tool. Maven compiles the code and executes unit tests to ensure its correctness. To access code quality, security vulnerabilities, and bugs, sonarqube, a static code analysis tool, is employed. As part of the automation process, the built code is packaged into a Docker image. This image is then automatically pushed to dockerhub, a container registry, with a new version identifier. Additionally, a shell script is utilized to update the manifest deployment file, which specifies the version and configuration details for deployment, with the newly created version. This ensures that the deployment process is seamlessly synchronized with the latest code changes. By integrating these tools and automating the necessary steps, this project enhances the efficiency and reliability of the software development pipeline. It facilitates rapid code testing, quality analysis, and version management, thereby improving the overall development workflow.
Utilization of Big Data in Libraries by Using Data Mining

This article analyzes extensive data libraries and how they benefit when completed. This research has results, namely library data can be called big data if the data fulfills the three characteristics of big data: volume, speed, and variety. Data mining can process big data, for example, by associations that create links between objects. If an extensive data library contains borrowed data, this means being able to establish connections between borrowed collections. Librarians, in particular, can use the results of this comprehensive data work to decide how to proceed. Therefore, it is essential to play a role in improving the library. This research aims to increase discussion between readers and librarians about using Big Data, especially in libraries. The benefit of this research is to broaden the knowledge of readers and librarians about how to utilize big data. The research method used is library research which analyzes writings from various sources.
The Future of Large Language Models: A Futuristic Dissection on AI and Human Interaction

This paper delves into the burgeoning domain of large language models (LLMs) and their impending influence on the dynamics of artificial intelligence (AI) and human interaction. Given the rapid evolution of these linguistic titans, a thorough dissection of their prospective trajectory is undertaken. The paper scrutinises the potential of LLMs in facilitating human-like interactions, investigates their limitations and ethical implications, and postulates potential mitigation strategies. The research is driven by a global perspective, incorporating real-world examples and case studies to elucidate the practical implications of LLMs.
The Implementation of Brainwriting Strategy to Improve Students’ Ability in Writing Recount Text

Writing plays an important role in language acquisition, promoting the students’ experiment to communicate their ideas and strengthen the language ability that they learn in class. However, the researcher found that students had low ability in writing. The research objectives were: (1) To describe the implementation of brainwriting strategy can improve students’ ability in writing recount text. (2) To identify the improvement of students’ ability in writing recount text by using brainwriting strategy. This research used a classroom action research design that conducts in two cycles. The research subject was X IPA 1 grade SMAN 1 Sangatta Selatan students. These research findings showed that: (1) The implementation of the brainwriting strategy where the students divide into some groups that consist of 6 or more participants, then every student write three ideas on the paper until 5 minutes the paper passed to the right person, just like that until all of the participants have got the paper. (2) The improvement of students’ ability to write recount text using brainwriting strategy could be seen from the comparison calculation between the total average cycle I and cycle II scores. The implementation of brainwriting strategy can improve the students’ ability to write recount text.
ADAPTIVE SYSTEMS AS MEANS FOR IMPLEMENTING ANTHROPOCENTRIC APPROACH TO TRANSITION BETWEEN FORMATS

The paper continues the research on the problems both educators and students experience while transferring between modes of instruction: traditional offline, online, mixed and hybrid formats. The factors are external and internal. The external factors, namely, pandemic period lockdown and later the geopolitical conflict involving more than two parties make it impossible for many overseas students to participate in face-to-face classes. Psychological adaptation and university’s capacity to provide for a successful learning process in different formats are the internal factors. Research questions cover the following aspects: 1) students’ expectations of different formats and problems they faced; 2) problems the educators faced; 3) research done previously; 4) solutions suggested; 5) feasibility of the proposed solutions. The findings based on thorough literature review, two surveys, and an expert interview1 show that adaptive educational systems, despite being promising, are not likely to be implemented widely in the observable future. We argue that an anthropocentric approach to educational technologies and adaptive systems are not the solutions to the problems per se. These systems are a powerful instrument to provide for inclusive, comfortable and effective personalised education. The revised principles and key features of the new curricula for social sciences and humanities alongside implementation of adaptive systems can be the best solution in transition between modes of education.
GO FURTHER AND BEYOND: PERSONIFICATION AND INDIVIDUALISATION IN LEARNING AND TEACHING MASTER’S STUDENTS

Personification and individualization in learning and teaching master’s students aims to mold high-level specialists able to integrate successfully to the international professional community. The article discusses a synergy of approaches such as system and matrix modelling of professional activity, learner-centered teaching techniques, adaptive learning, learning trajectories, event techniques, and formative assessment. These include the potential of an entrepreneur master’s programme leading to a startup. The researcher uses methods such are observation, case study, experiment, and instructional modelling. The study is based on the current Journalism, Advertisement, and PR master’s programmes at Saint Petersburg State University and a new one — Foreign Languages and Translation in the Media. The ultimate goal of this new approach is to enhance students’ awareness of taking a master’s programme as part of their successful careers. Further research will include developing qualitative and quantitative measurement tools to monitor student’s progress.
A generalized dialogue graph construction and visualization based on a corpus of dialogues

A definition of a generalized dialogue graph is proposed to describe the structure of a dialogue in terms of a corpus of homogeneous dialogues. The task of constructing such a graph is relevant in modern conversational artificial intelligence, however, there are few works with meaningful results, often a complete description of the algorithms is not given and the code with the implementation is not published. In the paper, a method for constructing a generalized dialogue graph is proposed, which is implemented in the Python programming language and made publicly available. Experiments were carried out on open data and the results were described.
Rating as a form of modeling the modern reading space

Reading is a multidimensional phenomenon, being not only a tool for receiving information about the world, but also an instrument of ethical and aesthetic education, a way of spending leisure time. The volume of reading characterizes the personality, indicates erudition, interests, and behavioral features. In ancient times books were available to the few, and the attitude towards them was serious. In antiquity it was recommended to confine oneself to a few selected authors and re-read them. After the invention of book printing, reading gradually losst its elitist character, the book became the most important source of information. In modern society the spread of the Internet and digital technologies has led to a decline in the popularity of traditional reading. The opportunity to obtain compressed information from the Internet and the feeling of accessibility of any information without the need to comprehend and memorize it change the structure of cognitive processes, tune the brain to assimilate ready-made forms, resulting in a loss of interest in reading and an increase in functional illiteracy. It is all the more important to maintain interest in reading, to form the need for it, to draw attention to the best classical and contemporary works. This is the goal of various ratings that are regularly published in print and online publications. They come in two varieties: sales ratings and stimulant ratings. The former reflect the requests of readers, the latter model these requests. Sales ratings record the emergence of interest in a particular book, which can be caused by various factors, for example, the appearance of a film adaptation or the occurrence of situations in real life similar to those described in the book. Stimulant ratings aim to introduce the reader to the type of serious, focused and complicated reading with the help of modern tools: catchy titles resembling advertising slogans, appeals to prestige, the use of debitive and imperative modality. Stimulant ratings are published in quality press and other responsible media, and their influence on the formation of readers’ preferences is undoubtedly great. They perform informative, advertising, educational functions. Introduction to the culture of reading is a socially significant problem. To a certain extent ratings help to solve it. Their role in the modern digital society focusing on the rapid acquisition of compressed information is to form the need for reading, to promote books worthy of attention and to model the reading space.
Memory Troubleshooting

A central characteristic of Java programs is the dynamic creation of objects while the application is running. In well-formed code, the garbage collector can automatically remove unused objects in a balanced manner. That is to say that, at some point, the number of removed objects equals the number of newly created objects. Unfortunately, and especially with complex applications in a corporate environment, software deficiencies might lead to functionally unused objects somewhat hanging around and not being cleared by garbage collection. If such objects pile up over time, that's called a memory leak.
Integrasi library Json Retrofit Dengan Framework Codeigniter Pada Aplikasi UMKM UD Rahma

MSMEs (Micro, Small and Medium Enterprises) are businesses established by individuals / individuals / business entities that meet the criteria, MSMEs usually have limited capital, because capital only comes from business owners or a small group of people who invest capital for these MSMEs. Code Igniter is one of the widely used frameworks, where the main purpose is to minimize the code when creating a website. The advantages of Code Igniter include being open source, being able to run in all PHP versions, the program only requires few resources so that the program runs lightly and quickly, using the Model View Controller (MVC) so that it makes it easier for programmers when a website change occurs, has complete documentation, ranging from installation steps to code or functions / classes in website creation. From the results of this study, it has succeeded in integrating the JSON retrofit library in applications built for ordering products in android applications with the CI framework also successfully used to create its web-based backend application with beta test results in terms of appearance and user convenience of 72%.