Reviewerly/exHarmony huggingface dataset:
Hybrid Filter-Genetic Feature Selection Method For Arabic Sentiment Analysis

The dramatic increase in user comments describing their feelings about products, services, and events brings sentiment analysis to the forefront as a way to monitor public opinion about products and events. Feature selection is an important subtask of sentiment analysis, which aims to improve the performance of learning algorithms and reduce the dimensionality of a problem. Feature selection is an important subtask of sentiment analysis, as it can improve the performance of learning algorithms while reducing the dimensionality of a problem. Moreover, the high-dimensional feature spaces caused by the morphological richness of Arabic motivate further research in this area. In this paper, a hybrid filter-based and genetic feature selection algorithm is proposed using four machine learning algorithms, namely decision tree, Naive-Bayes, K-NN and meta-ensemble methods. The performance of the proposed algorithm is compared with the performance of baseline models. A wide range of experiments are conducted on two standard Arabic datasets. The experimental results clearly show that the improved methods outperform the other baseline models for Arabic sentiment analysis. The results show that the improved models outperform traditional approaches in terms of classification accuracy, with a 5% increase in the macro average of F1.
Simplifying Multimodal Composition: A Novel Zero-shot Framework to Visual Question Answering and Image Captioning

Abstract In this work, we perform zero-shot image captioning and visual question answering on images using a simple model composition framework, composing the dense image captioning capabilities of a visual language model with the powerful reasoning abilities of a large language model, ChatGPT. The proposed method utilizes zero-shot learning to enable cross-modal integration of vision and language in order to create a comprehensive visual language model. We achieve zero-shot state-of-the-art performance on VQAv2, demonstrating its effectiveness and high accuracy. The method's simplicity makes it highly scalable and adaptable to a wide range of applications, including integration from OpenAI’s multimodal model, GPT-4, with audio language models in the future. The results demonstrate the vast potential of this simple zero-shot framework in improving the accuracy and relevance of vision and language applications, constituting an effective approach to image captioning and visual question answering, as well as future multimodal composition.
CASE STUDY ON A LARGE-SCALE TIMBER ACADEMIC BUILDING DESIGNED TO ADDRESS CURRENT INDUSTRY CHALLENGES

The need for more sustainable construction has led to the desire to increase the use of wood materials in our buildings.However, challenges in terms of larger column grids, future design flexibility, and fire resistance have occurred in institutional, commercial, and industrial building types that have hindered mass timber's adoption.This study reviews these challenges and provides insight into the design of a mass timber academic building as a viable design solution.The building creates open-concept and future flexible spaces by taking advantage of several novel structural solutions, while achieving fire resistance requirements.The structural solutions include the long span hollowcore mass timber floor panels for large amenity areas, two flat plate "service towers", and a combination of timber braced frames and CLT shear walls for the lateral system, in order to meet the challenges faced.
The Study Method Of Learning and Data Ethics in Elementary School Students' Consciousness

본 연구는 초등교육에서의 인공지능 윤리교육의 중요성에 대해 언급하며 실제적인 교수학습방안을 제시하기 위해 진행되었다. 머신러닝으로 인해 이전까지와는 다르게 더욱 빠르게 변화해가는 시대에서 인공지능 리터러시의 중요성이 더욱 부각되고 있다. 이에 따라 AI 리터러시의 AI 기술역량과 AI 윤리역량에 대한 적절한 교육이 필요하며, 특히나 AI 윤리에 대한 교육은 AI 기술역량에 비해 인식이나 적절한 교수학습방법이 부족한 실정이다. AI 윤리는 단순히 인터넷 사용자가 지켜야 할 윤리가 아닌, 개발자와 공급자와 사용자와 인공지능 기술 자체도 지켜야 할 윤리이다. ‘윤리’라는 전통적인 규범은 변화하지 않았으나, 시대의 흐름에 따라 이 전통적 규범의 적용이 인공지능에도 적용되어가고 있다. 필자는 그중에서도 데이터, 알고리즘 등에 관련된 도덕적 문제를 연구하고 평가하는 데이터 윤리에 대한 연구를 진행하였다. 전통적인 개념의 윤리를 데이터를 사용하며 발생하는 다양한 결과에 따라 통찰력을 가지고 이를 올바르게 식별해 낼 수 있도록 접목시켜 미래 인재를 육성하고자 한다. 다양한 윤리적 문제에 대한 접근을 통해 앞으로 나타날 문제에 대해 예방하고 해결 방법을 스스로 찾아나갈 수 있는 학습자를 양성하는 것이 이 연구의 목표이다. 이에 따라 교수자는 빠르게 변화하는 사회 속 사례를 통해 변화를 인지하고 이 변화 속에서 어떤 태도를 갖추어야 할지에 대한 통찰력을 기를 수 있는 교수학습방안을 지속적으로 제공하여야 한다. 따라서 학습자에게 적절한 교수학습방안을 제시할 수 있도록 도울 수 있는 지속적인 연구를 목적으로 한다.This study was conducted to discuss the importance of artificial intelligence ethics education in elementary education and to present practical teaching methods regarding this topic. As machine learning is changing more rapidly, It further highlights the importance of artificial intelligence literacy. Appropriate education regarding AI(Artificial Intelligence) literacy's technology and ethics capabilities is deemed required. Unfortunately, education on AI ethics lacks recognition and appropriate teaching methods compared to AI technology capabilities. AI ethics is limited to only users of the Internet, but also relevant for developers, suppliers, users, and the artificial intelligence technology as well. Although the traditional code of ethics has not changed, the application of this traditional code has been integrated to artificial intelligence as times went by. Among them, we conducted research on data ethics, which studies and evaluates ethical issues related to data, algorithms, etc. We intend to foster future talents by combining the ethics of traditional concepts so that they can correctly identify various results generated from the data. The goal of the study is to train learners who can prevent future problems to arise by approaching various ethical problems and finding solutions themselves. Therefore, professors should continue adapting to changes arising from the rapidly changing environment, and develop insight into what attitude they should take in this change.
Penggalihan kebutuhan berdasarkan pengalaman user persona untuk meningkatkan ekspektasi pengguna terhadap LMS

Lately, many of the educational circles use LMS to conduct electronic learning. This is because the COVID-19 pandemic has an impact on the teaching and learning process. Therefore, the government took a policy to reduce the spread of the COVID-19 virus by carrying out social restrictions. This requires that teaching and learning activities, which were initially carried out in person and face-to-face, must be done online or remotely, which of course creates new problems for teachers and students. Some of the problems that exist include students' ignorance when the lecturer gives assignments, or even the internet problems faced by some students. In previous studies, several researchers used a usability scale to obtain data from multiple users. However, in this case, the authors collected data through interviews with several users regarding what they needed regarding LMS. From the data obtained, the researcher thinks that the LMS is less effective for online learning due to the lack of features contained therein. One of the features needed by some users is the notification feature to find out the latest information that has been shared.
Importance of Accounting Marketing in Post-Corona era

&#x0D; &#x0D; &#x0D; &#x0D; Accounting marketing is an interdisciplinary field that focuses on strategic marketing investments through accounting accuracy and efficiency. Accounting marketing actually means marketing in accounting, which means implementing the principles and rules of marketing to promote accounting and related services. In order to shorten the combination that is actually the keyword of this article, in this paper is used accounting marketing instead of marketing in accounting. Nevertheless, accounting marketing is still in its infancy. In this article, while examining the concepts of accounting marketing, its role in the period before and after Corona is discussed. Accounting marketing strategies are also reviewed and the key to organizations' success in using them is explained.&#x0D; Finally, an eight-step plan is presented to succeed in implementing accounting marketing strategies. As a general conclusion, it is suggested some organizations as well as accounting consulting companies study the steps of this plan for changing and unfavorable conditions of the post-corona period and use benefits of accounting marketing, effectively.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D;
WT-BiFPN: A Novel Approach for Efficient Face Detection using Improved EfficientDet Architecture and Dual-Tree Complex Wavelet Transform

Abstract Face detection is a crucial task in computer vision and image processing with various practical applications including security, surveillance and entertainment. In recent years, approaches based on deep learning methods improved significantly with high-accuracy detection results. In this paper, we propose a new framework for anefficient face detection based on improved EfficientDet architecture and wavelet transform. Our method utilizes a combination of innovated bi-directional feature pyramid network (BiFPN) and a dual-tree complex wavelet transform called WT-BiFPN to ameliorate feature representation of faces at multiple scales. We evaluate our approach on two benchmark datasets, including WIDER FACE and our gathered dataset with specific details close to real-world images. Our proposed architecture achieves more than 5% performance improvement on previous state-of-the-art EfficientDet-based methods in terms of mean average precision (mAP). Our method provides an effective accurate face detection solution for several applications and can prevail over low resolution and occlusion in images.
Rental and Loan System in Agriculture using Blockchain Technology

Abstract: This paper proposes a rental and loan system in agriculture using blockchain technology. Agriculture is an important sector of the economy, but smallholderfarmers often face challengesin accessing credit and equipment fortheirfarms. Blockchain technology offers a secure and transparent solution to these issues. The proposed system utilizes smart contracts on a blockchain network to facilitate rental and loan transactions between farmers and lenders. The smart contracts are self-executing, meaning that they automatically enforce the terms of the agreement once certain conditions are met. This ensures that both parties can trust the system and that the terms of the agreement are fulfilled. The system also utilizes a decentralized database to store information about the transactions, such as the terms of the agreement, the amount borrowed or rented, and the repayment schedule. This information is transparent and easily accessible to all parties involved, which reduces the risk of fraud and increases trust between the parties. The rental and loan system can also help to increase access to equipment for smallholder farmers, who may not have the financial resources to purchase their own equipment. By utilizing the system, farmers can rent the necessary equipment for a specific period of time and return it once their needs have been met. In conclusion, the proposed rental and loan system using blockchain technology offers a secure and transparent solution to the challengesfaced by smallholderfarmersin accessing credit and equipment fortheirfarms. The system hasthe potential to increase trust between parties, reduce the risk of fraud, and increase access to equipment for smallholderfarmers.
Exploring New AI-Based Technologies to Enhance Students’ Motivation

Aim/Purpose. The aim of this study is to propose a teaching approach based on AI-based chatbot agents and to determine whether the use of this approach increases the students’ motivation. Background. Today, chatbots are an integral part of students’ lives where they are used in various contexts. Therefore, we are interested in incorporating these tools into our teaching process in order to profit from their benefits, assist and guide students while working with to prevent issues such as plagiarism and mainly to boost students’ motivation. Methodology. Using the proposed approach, new chatbot based learning activities were de-signed in three different courses for computer science engineering students. A mixed-method experimental study was conducted to evaluate students’ impression and satisfaction. Survey results of the students (N=58) who participated in the experiment (experimental group) were compared to the results of the students from the control group (N=60). Contribution. Trending AI conversational agents can be engaged in daily teaching activities as a learning assistant and coach to boost students motivation and skills development. Findings. Our study focuses on the impact of chatbots on student’s motivation. The study aimed to analyze the benefits and drawbacks associated with these conversational chatbots. Our findings revealed the significant role that chatbots can play in enhancing student motivation and improving teaching practices.
Internet of things and the future of digital marketing

In the digital world these days, everywhere you look, traces of the Internet of Things (IoT) can be seen. Businesses will improve with the use of this technology because devices will be able to collect a huge amount of user information. . If this information is used appropriately, commercial activities are able to expand their activities, reduce costs and provide users with devices with more and better features. These devices are only allowed to be accessed by certain people because they contain a large amount of information. However, there are many concerns about these devices. Even though the technology is advancing day by day, the risks related to it also increase. With the trend of marketing toward digitalization, we are witnessing its spread in various businesses. But since the Internet of Things has a solution for every issue and challenge, it also has new and fresh solutions for this issue. In this article, an attempt has been made to explain the role of the Internet of Things in digital marketing.
The outcome of implementing structured softes model as a post simulation debriefing strategy among marine trainees

1. ABSTRACT: This research studies the impact of implementing the structured SOFTES model as a debriefing strategy after the simulation training on marine trainees. One hundred trainees were split to two groups, each group was fifty trainees and took a questionnaire that was used to collect data. The experimental group was trained on the SOFTES model with its simulation training and the control group took the normal training only. SOFTES model is examined through multiple factorial elements, which are; Student, Objectives, Facilitator, Time, Environment, and Skills competency. Descriptive analysis was used for variables and comparing analysis using the T-test was used to study the effect of SOFTES model on the self-analysing and self-evaluation of the trainees from two groups and indicate which group has better behaviour in analysing. The impact of implementing the SOFTES model on the trainees’ self-analysing was showed as a positive and significant. Also the difference between means was showed which indicates the experimental group has less anxiety and increased self-confidence than the control group.
A Simple and Effective Method of Cross-Lingual Plagiarism Detection

Abstract We present a simple cross-lingual plagiarism detection method applicable to a large number of languages. The presented approach leverages open multilingual thesauri for candidate retrieval task and pre-trained multilingual BERT-based language models for detailed analysis. The method does not rely on machine translation and word sense disambiguation when in use, and therefore is suitable for a large number of languages, including under-resourced languages. The effectiveness of the proposed approach is demonstrated for several existing and new benchmarks, achieving state-of-the-art results for French, Russian, and Armenian languages.
Struktur dan Unsur Kebahasaan Teks Cerita Fantasi Siswa Kelas VII SMPN 1 Tanjuang Baru

This type of research is a qualitative research with descriptive method. This research was conducted at SMPN 1 Tanjung Baru. The instrument in this study uses a test. Data collection techniques with data research in this study by means of documentation and table instruments. Checking or checking the entire data using data triangulation. Based on the research results, it can be concluded two things. These two things are as follows. First, in writing fantasy story texts, class VII UPT SMP Negeri 1 Tanjuang Baru students have not used the text structure properly. Second, when viewed from the language in the text of fantasy stories for class VII UPTSMP Negeri 1 Tanjuang Baru students, there are still many errors found.
The Technique of Formation of Valuable Attitude for Amateur Theatre by Future Leaders

The dynamic development of theater culture in Russia, including the culture of Amateur theater, the growing popularity of Amateur theater in modern society, and the awareness of Amateur theater as a phenomenon of Russian national culture makes it urgent to improve the training of managers of Amateur theater groups in institutions of arts and culture. The study of literature, generalization of practical experience, and experimental research data led the authors to the conclusion that the direction of this improvement is to educate students in a value attitude to Amateur theater and their chosen profession. The functions of value attitude education: epistemological (knowledge), axiological (value), regulatory-normative and creative. Components of the pedagogical model: adaptive-diagnostic, planned-correctional, informational-activity, variative-creative, evaluative-effective. The results of the chosen pedagogical model gave positive results, which makes it possible to consider the proposed way to improve the training of specialists correct and appropriate.
International Problems in the Information Policy of Russian Digital Media

The article is devoted to the study of international issues in leading digital media in Russia. This topic has been and remains a priority on the media agenda of the country. Given the increasing globalization and increasing international factors, the mass audience needs timely and accessible information in this area. When analyzing the materials, attention was paid to the problems, substantive characteristics, structural organization, genre specifics, linguistic and stylistic aspects, which, interacting, form a diverse panorama of international information covered by publications. The information policy of such publications as Lenta.ru, Meduza, Vzglyad and White Square Journal is investigated.
Anomalous Behavior Detection in ATM using Artificial Intelligence

This paper proposes a new supervised algorithm for detecting abnormal events in confined areas such as ATM rooms and server rooms. The objective of this work is to establish a robust technical foundation that supports a secure and convenient social infrastructure, with abnormal behavior detection using image processing being one of the key technologies. Abnormal behavior detection involves creating a model based on normal behavior data and identifying any behavior that deviates from this model as abnormal. However, collecting comprehensive abnormal behavior data in advance can be challenging. Therefore, the ability to detect abnormalities using a model built solely on normal behavior data is highly valuable for practical implementation. This proposed work presents examples of abnormal behavior detection using image processing techniques applied to ATM surveillance videos. Additionally, typical examples of abnormal behavior detection through motion image processing are demonstrated. Furthermore, our approach enhances system security by verifying the identity of the cardholder during ATM transactions. The combination of image processing algorithms and supervised learning enables effective identification of abnormal events, contributing to a more secure and reliable social infrastructure.
Machine Learning-based Automated Diagnosis of Breast Cancer from Mammography Images

This paper presents a novel machine learning-based system for the automated diagnosis of breast cancer using mammography images. The proposed system employs a nature-inspired feature extraction algorithm to accurately identify and highlight the salient features within the mammographic scans. The features derived are highly representative and effective in distinguishing between malignant and benign cases, thus addressing the inherent complexity and variability within the breast tissue structures. To enhance the prediction accuracy, a hybrid decision tree and gradient boosting algorithm is introduced. The decision tree algorithm provides a transparent and interpretable model, facilitating easy understanding and justification of the diagnosis decisions. The gradient boosting algorithm further refines the model by iteratively correcting the errors of the decision tree model, leading to a substantial improvement in diagnostic performance. The proposed system was tested on a comprehensive dataset and compared with the existing state-of-the-art diagnostic tools. The results demonstrated significant improvements in terms of accuracy, sensitivity, and specificity, thus showing promise in aiding radiologists in making more accurate and confident diagnoses. This research paves the way for a more robust, reliable, and automated system in breast cancer detection, thereby enhancing the effectiveness of breast cancer screening and early detection strategies.
Contro tutto e contro tutti: The linguistic pragmatics of protest in the Italian futurists’ manifestoes

The speech act theory by J.L.Austin and the conception of the degree of strength of illocutionary force (point) by J.R. Searle and D.Vanderveken underlies the study of exercitive speech act as the act of objection/protest expressed by prepositions contro and against ‘против’. Historically, protest as a genre goes back to the Ancient rhetorical tradition, but in the 20th century, it has also become an aesthetic foundation of the Avant-garde poetic discourse. The expression of protest and a critical attitude towards the dominant discourse become one of the grounds for the interaction of the Avant-garde poetic and political discourses. Discourse and linguopragmatic analysis of the Italian Futurists’ manifestos is carried out from the standpoint of the linguistic creativity that manifests itself in the form of the Avant-garde linguistic experiment. Further, the Italian Neo-avant-garde (Neoavanguardia, Gruppo ‘63) develops the idea of confronting linguistic and cultural norms in its poetical texts and manifestoes like Linguaggio e opposizione (1961) by Nanni Balestrini or Ideologia e linguaggio (1965) by Edoardo Sanguineti. The markers of adversative semantics include such grammatical and lexico-grammatical means as но, однако, впрочем, против, напротив, вопреки, наперекор; ma, anzi, mentre, però, bensì, pure, eppure, contro, piuttosto, etc. The paper focuses on the pragmatic and semantic features of the preposition contro as one of the most frequent opposition markers in the Italian Futurists’ manifestos. The study distinguishes methods of deviation from standard use, aimed at increasing the illocutionary force and the performative potential of the message.
An Analysis of Reversible Data Hiding Techniques in Images

The reversible data- hiding fashion conceals some sensitive information in an image for secure communication. Only an authorised party may decrypt the concealed communication and recreate the cover image. The strategies put forth by different experimenters haven't yet been suitable to reflect a picture with a high embedding rate and advanced reconstructed image quality. In this exploration, certain significant reversible data- caching strategies are addressed and a system is proposed that can enhance the quality of the reconstructed image, the embedding capacity, and the denoising of the image. This approach can offer a secret data transfer that's further authentic, private, and dependable. Keywords: Embedding rate, Encryption, Prediction error, PSNR, Reversible data-hiding, Steganography