Reviewerly/exHarmony huggingface dataset:
Cold Start Recommendation based on Cross-domain Sharing Knowledge Transfer Learning

Due to the sparse initial interaction data, the cold-start problem poses a challenge to recommendation networks, e-commerce websites, and video platforms, etc. Traditional user profiling can predict preferences but raises privacy concerns. To address this issue, this paper proposes a cross-domain knowledge-shared transfer learning model that is initially trained on a cross-domain mixed dataset to allow multi-task learning. This shared knowledge enhances the generalizability of the model and minimizes the dependence on sparse data. Different from traditional recommender systems, this model can utilize limited user-item interaction data to make accurate recommendations and reduce the cold-start problem. After initial training, the model is fine-tuned on the target domain data. To avoid overfitting and inefficiency, an extended Transformer module is used, extracting multi-scale hidden states and a Transformer encoder, which are updated at each time step. Experimental results on the Amazon dataset show that the model can adapt to new tasks more efficiently, reducing computational cost and risk of overfitting.
Design of Intelligent Evaluation System for Lyrics and Songs Matching Based on Intelligent Optimization Algorithm

With the rapid improvement of the Internet, intelligent algorithms are used in various fields. In this paper, the intelligent optimization algorithm (IOA) is applied to the evaluation system for the matching degree of music lyrics. The intelligent evaluation system of the matching degree of lyrics and songs based on the IOA can more accurately evaluate the matching degree of the lyrics and songs. The purpose of this paper is to evaluate and test the music based on the IOA using the fire fly algorithm music lyrics matching degree intelligent system. Compared with the class scores, the results show that the intelligent evaluation system for the matching degree of music lyrics has been improved under the IOA.
Perbandingan Model Pembelajaran Discovery Learning dan Model Pembelajaran Langsung terhadap Hasil Belajar Peserta Didik Kelas X P.Mia SMA Negeri 1 Parangloe (Studi Pada Materi Pokok Ikatan Kimia)

The research was a quasi-experimental that aimed to know the difference discovery learning and direct learning of student’s achievement in class X P.Mia Senior High School 1 Parangloe. The study design used is posttest only control group design. The population was class X P.Mia Senior High School 1 Parangloe which consisted of 102 students from three classes. The class selected as a sample was class X P.Mia 2 which consisted of 35 students as an experimental 1 class and class X P.Mia 1 which consisted of 31 students as an experimental 2 class. Experimental 1 class taught using discovery learning whereas experimental 2 class taught using direct learning. The independent variable in this research was discovery learning and direct learning, whereas the dependent variable was student’s achievement. Data collection technique was obtained that giving test the student’s achievement for posttest. Results of inferential statistical analysis prerequisite test showed that the data were not normally distributed. Testing the hypothesis with Mann Whitney test conducted by α = 0,05 were Zcalculated= 2,155 &gt; Ztable = 1,96. Conclude that there are difference of discovery learning and direct learning of student’s achievement in class X P.Mia Senior High School 1 Parangloe in.
Pengaruh Media Animasi pada Model Pembelajaran Quantum Teaching terhadap Hasil Belajar Siswa Kelas X Mia 2 SMA Negeri 22 Makassar ( Studi pada Materi Pokok Ikatan Kimia )

This research is a quasi-experimental which aims to know the effect of using animation as the media in Quantum Teaching model to student’s learning achievement of Class X Mia 2 at SMA Negeri 22 Makassar. The research design used post-test, that is only control group design.The population of this research are students from Class X Mia 2 of SMA Negeri 22 Makassar which consists of four classes with 134 students. This research used cluster random sampling. The samples are from Class X Mia 2 which consists of 35 students classified as the experimental group and Class X Mia 1 which consists of 31 students classified as the control group. In experimental group, the students were taught by using animation as the media in Quantum Teaching,while control group were taught through Quantum Teaching without animation as the used media.This research used Quantum Teaching and animation media as the independent variables, while students’ learning achievement on main material of chemical bonds as the dependent variable. The data collection were obtained by giving post-test to measure students’ learning achievement on the main material of chemical bonds.The result of prerequisite test showed homogenous variants which were not distributed normally. Hypothesis were tested by Man Whitney test as explained: α = 0,05 were obtained from Zhitung= 3,76 &gt; Ztabel = 1,65. To summarize from this research, there is an effect of using animation as the media in Quantum Teaching on students’ learning achievement of Class X Mia 2 at SMAN 22 Makassar (as applied in main material of chemical bonds).
Interactive teaching in high school mathematics teaching

With the deepening of educational reform, teachers' teaching concepts have also undergone tremendous changes. The traditional teaching mode is no longer suitable for the needs of the current educational development, in order to improve students' interest in learning and cultivate students' ability to learn mathematics, teachers must reform teaching methods and methods. As a new type of teaching, interactive teaching can not only improve students' interest in learning, but also give full play to the interaction between teachers and students. This paper mainly analyzes and elaborates on the significance, implementation and application methods of interactive teaching in high school mathematics teaching.
An Efficient Ontology Based Machine Learning for Classifying High Definition Satellite Images (Chandrayaan-3)

The analysis of satellite images to determine the kind of land, forest cover, plant type, and other aspects of a particular image has become a standard practice. Object-based image classification for land-cover mapping with remote-sensing data has received a lot of interest in recent years. Several researches have looked into a range of sensors, feature extraction, classifiers, and other important elements throughout the last decade. These data, however, have yet to be gathered into a complete reference on the implications of different guided object-based land-cover categorization methods. To solve this issue, we provide an ontology-based conceptual UKNN classification algorithm in this study. We create an 18-field database from the rit18 database's qualitative and quantitative data in this research. Instead of unexplainable characteristics provided by a CNN, this proposed study uses an ontology-based methodology framework to enable picture classification using features extracted from hyper spectral image data. The image is initially given a Gaussian filter. The suggested UNet K nearest neighbours (UKNN) classifier is utilised to translate the ontology components into image-based parameters, which are then used to improve the classification process. When a typical support vector machine (SVM) is compared to UKNN, we find that UKNN outperforms SVM in classification accuracy
Yawning Heights by A. A. Zinoviev as a Model of Philosophical Dystopia

This article analyses A. A. Zinoviev’s dystopia Yawning Heights. The author substantiates the thesis about the fundamental difference between philosophical and artistic dystopias. In the author’s opinion, the fundamental difference is rooted in the scientific and artistic methods of cognition of the world, specific ways of creating philosophical and artistic pictures of the world, and types of narrative. The author of a literary text moves towards a model of the world from an artistic image. The philosophical picture of the world presupposes a conceptual vision of the world and evidence-based argumentation of this concept. This methodological difference entails unique author’s strategies that determine the poetics and style of philosophical and literary texts. The emotional-sensual perception of the world by the author of a literary text determines the type of narrative in which the logical-analytical approach to reality is secondary in comparison with the figurative one. For scientific thinking, the analyticity and infallibility of conclusions are primary. The philosophical approach presupposes integrity, and in a certain sense completeness. The artistic picture of the world is focused on a dialogue with the reader, and therefore on the additional construction of the semantics of the text through the reader’s experience. The dystopia Yawning Heights is evaluated by the author of the article as a scientific but not a literary text. Observation, analysis, hypothesis, and assumption are a tool for analysing social reality, in which, according to Zinoviev, there are universal laws that are common to any human community and social system. The philosopher transfers the scientific method into the novel, moves in the comprehension of social laws from the abstract to the particular, i.e., from society to the individual. Zinoviev uses mask characters to evaluate the laws of sociality that depersonalise a person. The method, which is also typical of a literary text, receives a special interpretation from the philosopher. The schematic character of images reflects a law common to all social individuals, in which the particular is subordinate to the general, and psychological and personal differences are leveled. Zinoviev created a special genre — a philosophical dystopia, which is guided not by artistic, but by scientific logic.
MANIPULATION OF INFORMATION: THEORETICAL ASPECTS OF SCIENTIFIC DISCOURSE

The article substantiates the main aspects of information manipulation. It identifies which of these are related to mass media and who among Ukrainian and foreign researchers have studied them. The focus is on the fact that manipulation technologies in the media are used to shape public opinion, influence the behavior of average citizens, and control various narratives. Studying media manipulations develops critical thinking skills and increases media literacy among information consumers, allowing them to distinguish between reliable information and manipulative content. This enables them to make informed decisions and reduces the risk of being misled or manipulated by deceptive media tactics. Manipulations in the media pose a significant threat to democratic processes, as fake news and disinformation campaigns undermine public trust, distort and manipulate political narratives. Recognizing manipulations in the media provides citizens with tools to counter these threats. Thus, the democratic principles of transparency, accountability, and informed participation are protected. Manipulations in the media are often associated with unethical practices, including the spreading of disinformation, twisting facts, or using deceptive techniques to create sensations. Studying manipulation in the media allows journalists to become more familiar with such tactics and encourages adherence to ethical standards in journalistic materials. Information consumers who understand what media manipulations are can verify information and not succumb to the influence of deceptive or biased content. The study of media manipulation is critical to developing critical thinking, protecting democratic processes, promoting ethical journalism, understanding human behavior, and strengthening digital citizenship. This enables individual citizens and society in general to navigate the complex media landscape and counteract the negative consequences of manipulative influences.
Multi-Agent Dynamic Leader-Follower Path Planning Applied to the Multi-Pursuer Multi-Evader Game

Multi-agent collaborative path planning focuses on how the agents have to coordinate their displacements in the environment to achieve different targets or to cover a specific zone in a minimum of time. Reinforcement learning is often used to control the agents' trajectories in the case of static or dynamic targets. In this paper, we propose a multi-agent collaborative path planning based on reinforcement learning and leader-follower principles. The main objectives of this work are the development of an applicable motion planning in a partially observable environment, and also, to improve the agents' cooperation level during the tasks' execution via the creation of a dynamic hierarchy in the pursuit groups. This dynamic hierarchy is reflected by the possibility of reattributing the roles of Leaders and Followers at each iteration in the case of mobile agents to decrease the task's execution time. The proposed approach is applied to the Multi-Pursuer Multi-Evader game in comparison with recently proposed path planning algorithms dealing with the same problem. The simulation results reflect how this approach improves the pursuit capturing time and the payoff acquisition during the pursuit.
Enhanced Deep Learning-Based Model for Sentiment Analysis to Identify Sarcasm Appeared in the News

In the field of natural language processing (NLP), detecting emotions or sentiments can be a challenging task, and sometimes emotions can be more complex than just positive or negative. However, detecting sarcasm in textual data adds another layer of complexity. Despite this, identifying the underlying sarcasm in the text has become a recent area of interest among NLP researchers. Headlines in newspapers often use sarcasm to engage readers, but readers may have difficulty recognizing it, leading to a misinterpretation of the news and spreading misinformation. As a result, there is an urgent need for technology that can automatically identify sarcasm with high accuracy. Recent studies in this domain have revealed a need for a robust and efficient model. Deep learning approaches have proven to be effective in sarcasm detection. In this work, we propose a novel two-stage model that uses a word-embedding technique to select relevant features followed by an advanced deep-learning architecture to classify sarcasm in news headlines. Our proposed method demonstrates promising results in identifying sarcasm in text with an accuracy rate of approximately 97 %. We have fine-tuned the hyper-parameters to increase the precision level, which enhances the efficacy of our model. Our work provides a significant contribution to the field of NLP by presenting a reliable and effective model for sarcasm detection. The comparison of our model with recent advancements indicates that our approach outperforms them. By using our model, readers can avoid misinterpretations and the spreading of misinformation. Therefore, our work can have a positive impact on society, and we believe that it can inspire future research in the field of sarcasm detection.
Strategic Management of Technology in Psychology: Implications for Decision-Making

This review article systematically examines the significant advancements in epidemiological methods from 2005 to 2023, highlighting the evolution and impact of contemporary approaches in the field. Employing a thorough literature search across key databases, the review focuses on peer-reviewed articles, reviews, and meta-analyses that underscore innovative methodologies and applications in epidemiology. The inclusion criteria prioritized studies that introduced new techniques, integrated technology, or applied interdisciplinary approaches. This article synthesizes these advancements, revealing trends such as the incorporation of big data analytics, machine learning, and genetic epidemiology, which have substantially enhanced the scope and accuracy of epidemiological research. The review also discusses the challenges and ethical considerations emerging from these advanced methods, particularly in data privacy and the complexity of analysis. The findings underscore the shift towards more dynamic, precise, and interdisciplinary methods in epidemiology, reflecting the field's adaptation to the demands of modern public health challenges. This comprehensive overview not only provides a valuable resource for epidemiologists and public health professionals but also sets the stage for future research directions, emphasizing the need for continued innovation and ethical vigilance in epidemiological practices.
Fiat digital currencies: from idea to implementation

This publication is devoted to the study of a new financial and legal instrument central bank digital currencies (CBDC) that is had distributed worldwide. Fiat digital currencies are being issued already in some countries, in others the issue of their introduction is under discussion only. Based on the method of comparative law and other methods of scientific research, the author opens out the common legal features of digital currencies of various countries and their differences as well. The foreign experience made it possible for author to generate the advantages and disadvantages of the digital currencies of central banks. Among the first, the simplification of cashless payments, the reduction in the costs of making money transfers, transparency for central banks and financial supervisory authorities of operations with digital currency, an increase the level of security and safety of funds, etc. Disadvantages CBDC are the distrust of citizens in digital currencies, the inability to solve the problem of weakness and instability national currency with the help of a new digital tool, the enormous costs of the Central Bank of the Russian Federation, credit institutions of creating this system, developing special programs for clients integrated with the digital platform, the possibility of leakage of personal information, as well as full openness of information about users. The Russian practice of introducing the digital ruble has not been left without attention. The publication also touches upon some legal problems of this subject and proposes their solutions. The author, in addition to general scientific methods, primarily uses such special methods of scientific knowledge as the formal legal method, the method of comparative law, empirical methods such as collecting of the data on the distribution of digital currencies of the central banks of the world, comparative analysis of legal documents, observation.
Don’t Just "Google It"

This paper examines the argumentative retort “Just Google it” in response to cases of epistemic exploitation. Critical assessments of the reply often examine the phrase from an argumentation theory standpoint, which views it as at best rude and at worst a violation of argumentative norms. However, these critiques ignore one of the functions of the term—to avoid epistemic exportation. The response may be a useful tool for Black individuals to offload some epistemic burdens concerning racial arguments, but due to racially biased search engine algorithms, the phrase has the high potential to exacerbate racial disagreements. Directing disagreeing interlocutors to “Google” anti-Black oppression and having them self-research unjust institutions runs the substantial risk of reinforcing an interlocutor’s original stance, due to the ways in which search engine algorithms utilize word embedding. Rather than using the phrase “Just Google it,” this paper concludes with a few alternative suggestions to combat epistemic exploitation.
HUBUNGAN INTENSITAS PENGGUNAAN GAME ONLINE DENGAN INTERAKSI SOSIAL PADA REMAJA DI LINGKUNGAN 4 KELURAHAN HUTASUHUT KECAMATAN SIPIROK

Game online merupakan aplikasi permainan yang berupa petualangan, pengaturan strategi, simulasi, dan bermain peran yang memiliki aturan main dan tingkatan-tingkatan tertentu. Intensitas penggunaan game online adalah besarnya minat atau seringnya seseorang dalam memainkan permainan melalui akses jaringan internet secara online yang memiliki sifat kuantitatif dan kualitas. Jenis penelitian ini adalah penelitian kuantitatif. Sedangkan rancangan penelitian menggunakan uji spearman. Populasi dalam penelitian ini sebanyak 32 remaja dengan teknik pengambilan sampel total sampling. Variabel independen dalam penelitian ini adalah intensitas penggunaan game online dan variabel dependennya adalah interaksi sosial. hasil analisis menggunakan uji sperman dapat kan nilai signifikansi p value = 0.016&lt; 0,05 maka Ha diterima, artinya ada Hubungan antara intensitas penggunaan game online dengan interaksi sosial pada remaja di Lingkungan 4 Kelurahan Hutasuhut Kecamatan Sipirok. Semakin tinggi tingkatan ukuran frekuensi intensitas yang dihabiskan dalam bermain game online, berarti semakin buruk juga interaksi sosial remaja. Dan semakin rendah tingkatan ukuran frekuensi yang dihabiskan dalam bermain game online, berarti semakin baik juga interaksi sosial remaja.&#x0D; Prediabetes is a serious health condition in which blood sugar levels are higher than normal, but not high enough to be diagnosed as type 2 diabetes. Prediabetes occurs mostly in respondents aged &gt;45 years. WHO data found that after reaching the age of 30 years, blood glucose levels will rise 1-2 mg%/year during fasting and will increase by 5.6-13 mg%/year 2 hours after eating. The purpose of this study was to determine the risk factors that cause prediabetes in the city of Padangsidimpuan. This research is a cross-sectional study with a total sample of 52 respondents selected by purposive sampling. The results showed that the majority of respondents aged 40-49 years were 22 people (42.3%), the majority of respondents had BMI &gt; 25 kg/m2 of 30 people (57.7%), the majority of light physical activity were 28 people (53 .8%), the majority had families with a history of DM as many as 37 people (71.2%). From the results of the study it can be concluded that the risk factors for prediabetes in Padangsidimpuan City include age, BMI, physical activity, family history of DM. The higher the age, the risk for uncontrolled blood sugar levels will be even greater. It is expected that patients with prediabetes will be able to carry out good self-care so as to prevent complications from prediabetes into diabetes and other microvascular and macrovascular diseases.
Hubungan Durasi Penggunaan Media Sosial Terhadap Kejadian Asthenopia Pada Mahasiswa FKP UNRI

Introduction: The duration of using gadgets to access social media is unlimited and continuously causes the eyes to see objects on the screen. The eyes are continuously accommodated to see letters or numbers on the monitor which will result in eye fatigue (Asthenopia), research objectives: to determine the relationship between the duration of social media use and the incidence of Asthenopia in students of the Faculty of Nursing, University of Riau, materials and methods: This study using a correlational analytic design with a cross sectional approach. The study was conducted at the Faculty of Nursing, University of Riau with 237 students as samples taken by proportionate stratified random sampling technique by taking into account the inclusion and exclusion criteria. The measuring instrument used is a questionnaire. The analysis used was univariate and bivariate analysis using the Chi Square, the results of the study: The results of the bivariate statistical test showed that there was a relationship between the duration of social media use and the incidence of Asthenopia in students of the Faculty of Nursing, University of Riau with p Value (0.021) &lt; (0.05). Overall, there were 176 people (74.2%) who experienced asthenopia. On average, students experience Asthenopia in the low fatigue category due to the duration of using social media which is not good for eye health, suggestions: Students are expected to be able to control and reduce the duration of social media use in order to prevent the occurrence of Asthenopia.