Reviewerly/exHarmony huggingface dataset:
Digital Knowledge Sharing and Work Creativity while working from home during the COVID-19 Pandemic Settings: Evidence from Lebanese Teleworkers

COVID-19 imposed a new working behavior. As governments imposed national confinements to contain the virus, companies shifted towards WFH – Working from Home further relying on digital applications to facilitate the exchange of work-related information and digital knowledge sharing (DKS) among co-workers. Although many scholars outlined the influence of DKS on the Creative Performance (CP) of knowledgeable teleworkers according to previous research, WFH was considered as optional work behavior, while it has become a reality during COVID-19. Thus, this paper aims to elucidate the various, still unexplored aspects of working from home, reassessing the correlation between DKS and CP next to studying the possible influence of contextual factors (organizational climate, individual factors, and demographics) on both DKS and teleworkers’ CP. In this context, a cross-sectional survey was distributed online to 263 Lebanese teleworkers. The study settles that digital technology is a pivotal factor in affecting employees’ digital knowledge sharing and therefore overall business performance as well and highlights the need to develop new theoretical approaches specific for the working from home (WFH) context.
Interrogating the interrogatives in Malayalam language

Spoken by approximately 2.88% of Indians, Malayalam is a Dravidian language and one of the twenty-two scheduled languages of India. In the state of Kerala as well as the union territories of Lakshadweep and Puducherry, the language is recognized as an official language. In 2013, Malayalam was named a ‘Classical Language in India’. Languages vary in how they form interrogatives. Malayalam has a dedicated interrogative inflectional form and it is often referred to as grammatical mood. Interrogatives in the Malayalam language are generally divided between yes/no questions, which ask whether or not something is the case and invite an answer of the yes/no type (/ate/-/alla/,/illa/), alternatively, a suffix added to the verb and wh-questions, which specify the information being asked about using a word like which, who, how, etc. can also give answers to the yes/no type questions. However, in the Malayalam language, the markers get meaning changes according to the context. As a result, the same marker can be used to give different meanings. This phenomenon is very evident in question formation. Malayalam use both syntax and prosody to distinguish interrogative sentences from declarative sentences and also marks interrogatives morphologically through a simple vowel change, i.e., by the inflection of the verb. This paper interrogates the interesting phenomenon of interrogatives in the Malayalam language by collecting data from various sources such as native speakers of Malayalam and some standard texts of Malayalam.
Communication-robust multi-agent learning by adaptable auxiliary multi-agent adversary generation

Abstract Communication can promote coordination in cooperative Multi-Agent Reinforcement Learning (MARL). Nowadays, existing works mainly focus on improving the communication efficiency of agents, neglecting that real-world communication is much more challenging as there may exist noise or potential attackers. Thus the robustness of the communication-based policies becomes an emergent and severe issue that needs more exploration. In this paper, we posit that the ego system 1) trained with auxiliary adversaries may handle this limitation and propose an adaptable method of M ulti -A gent A uxiliary A dversaries Generation for robust C ommunication, dubbed MA3C, to obtain a robust communication-based policy. In specific, we introduce a novel message-attacking approach that models the learning of the auxiliary attacker as a cooperative problem under a shared goal to minimize the coordination ability of the ego system, with which every information channel may suffer from distinct message attacks. Furthermore, as naive adversarial training may impede the generalization ability of the ego system, we design an attacker population generation approach based on evolutionary learning. Finally, the ego system is paired with an attacker population and then alternatively trained against the continuously evolving attackers to improve its robustness, meaning that both the ego system and the attackers are adaptable. Extensive experiments on multiple benchmarks indicate that our proposed MA3C provides comparable or better robustness and generalization ability than other baselines.
PENGARUH MEDIA COMIC STRIP TERHADAP MINAT BELAJAR PESERTA DIDIK DALAM PEMBELAJARAN BAHASA INDONESIA

This study aims to determine the effect of Comic Strip Media on Students' Learning Interest in Indonesian Language Learning in Class V of Teppoe Private Elementary School. The type of research used in this study is ex post facto which means after the fact, by taking data by survey, ex post facto research. The approach used in this research is quantitative research. The population is all class V students of Teppoe Private Elementary School, totalling 21 people. And the sampling used is a saturated sample. The results of the study based on simple regression analysis that has been carried out through the SPSS version 25 programme, obtained the results of the respondents studied, namely class V of Teppoe Private Elementary School totalling 21 people. It is known that if tcount ≤ ttable then H0 is accepted and Ha is rejected. If tcount ≥ ttable then H0 is rejected and Ha is accepted. Based on the coefficients table that tcount (3.212) &gt; ttable (2.093) and a probability value of 0.005 &lt;0.05 and in the model summary table by looking at R Square = 0.352 or 35.2% so it can be interpreted that significantly the comic strip media variable (X) affects the student learning interest variable (Y) by 35.2%.
PENGARUH PENGGUNAAN TELEPON SELULER TERHADAP MINAT BACA PESERTA DIDIK PADA MATERI TEKS HIKAYAT

Interest in reading is very necessary to support the knowledge that students must master. Reading is certainly a habit that all students in Indonesia must have. Interest in reading grows in every student, so to increase interest in reading each individual needs awareness. This research aims to determine the effect of using cellular telephone communication tools on students' reading interest in class X saga text material at SMK Negeri 3 Bangkalan. This research uses qualitative research by conducting interviews with 2 teachers as informants. Cell phone communication tools influence students' reading interest in saga text material in class.
The Impact of Tenth Grade Students’ Grammar Mastery and Anxiety on Their English Achievement

The aim in the study is to comprehend and determine how students’ anxiety and ability to use grammar influence their English achievement in the X-grade at three schools in the districts of Semendawai Barat and Cempaka, OKU East regency. For this study, ex post facto design was applied. At SMA N 1 Cempaka, SMA N 2 Semendawai West, and SMA N 1 Semendawai West, this research was carried out. The 96 participants from 3 different schools made up the sample. In this study, several data testing methods were employed, including normality tests, multicollinearity tests, heteroscedasticity tests, linearity tests, autocorrelation tests, correlation studies of the r-product moment, simple regression analyses, and double regression analyses. The findings of this study demonstrated that: 1) grammar proficiency significantly influences English success; 2) The achievement of students in English has been considerably impacted by students’ worry; and 3) Although only by 10.8%, grammatical proficiency and anxiety together have a considerable impact on English learning outcomes.
Information System of Superior Plant Varieties

The Food Crops Research and Development Center and research institutes are tasked with producing high-yielding plant varieties through research within the Agricultural Research and Development Agency. The results of the technology research conducted will be promoted and disseminated to the user community which includes agricultural extension workers, academics, researchers, agribusiness entrepreneurs, policy makers, and other parties who need the information. The most effective way of distributing this technological information is by creating a website-based system so that it can be easily updated and distributed.
Meningkatkan Minat Belajar Matematika Dengan Metode Belajar Sambil Bermain

Positive learning experiences stem from active engagement with lessons and greater interaction in learning activities. Play is also important for development because it contributes to the cognitive, physical, social and emotional well-being of children. Therefore the method of learning while playing is a good learning method and can be applied to learning mathematics. The purpose of this Field Work Practice is to motivate children in learning, especially in mathematics. The use of learning while playing methods like this can increase children's interest in learning so they don't feel bored and have more fun when learning math. The intervention used in this practicum activity is a mezzo intervention using the group work method through general or general stages which consist of; Engagement Intake Contract, Assessment, Planning, Intervention, Evaluation, and ending with Termination
Impacts of energy efficiency in cloud-based database systems

Energy efficiency in cloud-based database systems represents a pivotal convergence of technological innovation and environmental responsibility. By optimizing resource allocation, adopting renewable energy sources, and leveraging efficient hardware and infrastructure designs, these systems strive to minimize energy consumption while maintaining peak performance. Embracing green computing practices, these databases aim to reduce operational costs, mitigate environmental impact, and align with regulatory standards. Through real-time monitoring, smart utilization of resources, and adherence to industry certifications, the pursuit of energy efficiency not only enhances the sustainability of cloud infrastructure but also underscores a commitment to driving technological advancement in harmony with ecological preservation.
FRAUD DETECTION USING DATA ANALYTICS: A CASE STUDY OF UNDER INVOICING IMPORTATION FRAUD IN INDONESIA

Fraud detection is a big concern for all the government agencies. In customs areas, fraud detection is needed to ensure that there is no leakage in state revenue, one of which is caused by the under invoicing importation fraud. The data analytic implementations have been used in many studies to handle problems in big data and give solutions. This study aims to explain how data analytics can be implemented to detect the under invoicing importation fraud. Several variables were included in this study, including the variables that show the risk level of importers, commodities, suppliers, and the exporter countries. This study compared various machine learning models including Logistic Regression, Decision Trees, Random Forest, Extreme Gradient Boost, Artificial Neural Networks, Gaussian NB, and K-nearest Neighbors. To evaluate the models, this study measures the performance of the models by comparing accuracy score, precision score and log loss score. The result shows that the Xtreme Gradient Boost performs best in detecting under invoicing fraud with accuracy score at 63%, precision score at 63% and log loss score at 62%. As far as we know, this has been the first work to compare a number of machine learning models to create under invoicing fraud detection. The results of this study will assist examiners in the import clearance process by providing an early warning of the under-invoicing transaction. It can lead to more effective and efficient examination, so that customs agencies can perform well in their service and inspection functions, despite the limited resources
Leveraging Blockchain Technology to Transform Traditional Marketing Strategies into Secure and Efficient Practices

The suggested approach, dubbed Blockchain-Enabled Secure Marketing (BESM), utilizes blockchain technology to usher in a new age in digital advertising. To solve the problems that have plagued marketing in the past, BESM combines three cutting-edge algorithms: Decentralized Identity Verification (DIVA), Consensus-Driven Targeting (CDTA), and Immutable Performance Analytics (IPAA). DIVA offers user privacy and security via decentralized identity verification, leveraging cryptographic hashes and digital signatures. CDTA revolutionizes audience selection by combining consensus-driven decision-making, encouraging accuracy and democratic involvement. IPAA protects marketing performance metrics on the blockchain, making all of the data contained within immutable and public. The results of these experiments show that BESM is superior to conventional approaches, and that it provides superior data security, user privacy, efficiency, and transparency. Algorithms as a whole strengthen the marketing ecosystem by making it more reliable and customer-focused landscapes.
A Brief Discussion on the Utilization of Music Acoustics in Hans Zimmer's Creating Style

Film is a comprehensive art form, while film music and sound design is an indispensable part of film. Hans Zimmer is one of the most talented contemporary film music composers, has won the top awards of film music for many times, his creation style and creating method of film music are also the research direction of modern film musicians. This paper will discuss the application of Hans Zimmer's musical style through the analysis of the sound material and music theme in the film Dune.
The Moderating Role of Uncertainty Reduction on the Relationship between Leadership Styles and Organizational Identification within Saudi Hospitals

This study embarked on an exploration into the dynamics of various leadership styles and their influence on organizational identification, placing a spotlight on the potential moderating effect of uncertainty reduction within the healthcare sector of Saudi Arabia. Adopting a hypothesis testing approach, the research employed a correlation investigation design, ensuring minimal interference from the researcher. The backdrop of this study was set in five hospitals across Riyadh and Makkah, targeting the entire population of permanent nurses. To derive a representative sample, a probability sampling technique was used, more specifically, stratified sampling, which culminated in a sample size of 375 participants. The unit of analysis was set at an individual level, with a cross-sectional study time horizon. Data collection involved a 7-point Likert scale, which underwent a comprehensive descriptive analysis via SPSS, followed by a Partial Least Square assessment using Smart-PLS. The findings highlighted the nuanced interplay between leadership strategies and organizational contexts, emphasizing the significance of adaptability in leadership in alignment with varying degrees of environmental uncertainty.
Students’ Performance, Satisfaction, and Experiences in Graphic Organizer Integrated Online Instruction of Astronomy

This quasi-experimental study determined Graphic Organizer Integrated Online Instruction’s effectiveness in understanding astronomy concepts. Three groups of Secondary Science Education students from a state university in Central Visayas, Philippines, were exposed to text, both text and graphic organizers, and the latter only. Study findings revealed that students across the three groups obtained above-average performances and improved performance; these groups also showed no significant difference in the improved performance. Using graphic organizers yielded high retention and satisfaction among the students, as they were immersed in visual-verbal instruction, a valuable learning scaffold, and a fun experience. In conclusion, the use of Graphic Organizer Integrated Online Instruction was effective in improving student performance, retention, and learning experiences. Integrating these visual tools in online instruction is highly recommended for use at the undergraduate level in the new normal.
Ensuring Brand Safety and Reputation in Digital Marketing with Advanced Cybersecurity Protocols

The ever-changing world of digital marketing makes it more important than ever to protect the integrity of brands. This study presents a novel method called "Enhanced Brand Safety Assurance through Cybersecurity Protocols" that combines three important algorithms: Ad Fraud Detection and Prevention, Real-time Behavioral Analysis, and Threat Intelligence Integration. The security of digital advertising, privacy of sensitive information, and customer confidence may all be assured with this framework's proactive threat detection and mitigation capabilities. A strong protection system against ever-changing cyber threats is created by combining the unique characteristics of each algorithm. To react to the constantly changing cybersecurity scene, the suggested solution uses adaptive thresholds, machine learning, and sophisticated analytics. When compared to more conventional approaches, the suggested solution outperforms them in terms of important efficacy indicators and practical implementation details. Experiments show that it can learn a lot, integrate AI, adapt to threats, monitor in real-time, and identify threats very well. Brands can protect themselves from the complex digital threat environment with this comprehensive and proactive cybersecurity solution that tackles the many problems associated with digital marketing.
Approach to Prevent of Spoken Information Leakage through Gyroscope and Accelerometer Sensors in Mobile Devices with Android Operation System

Paper considers questions of the statistics analysis of the usage of mobile devices. The threat of spoken information leakage through gyroscope and accelerometer sensor in mobile device is considered. The approach for analyzing and evaluating threat level of audio information leakage from mobile device with installed android operation system is proposed.
Motivasi sebagai Kunci Peran dalam Pendidikan

Motivation is one of the key factors that influences human behavior in various life contexts. Motivation is an important factor in motivating students to learn and achieve academic success. Motivation is the main driver behind academic achievement and student development. Motivation itself is divided into two factors, namely external and internal. External motivation is motivation that comes from outside. Usually includes the family, school and surrounding environment, both social and non-social environments. while internal motivation is motivation that comes from within the student. Usually includes integrity, self-confidence and desire to achieve something. The aim of this research is to find out about the factors that influence student learning motivation and the role of motivation in learning as well as how to increase and maintain student motivation. The research method used is a literature review (Library Research) located in the library/reading room online and offline. The research data source used is a primary source. Motivation is the main factor in learning, namely its function is to give rise to, underlie and drive the act of learning. From this research, it can be found that there are several factors that influence student learning motivation and the role of motivation in learning as well as ways that can be done to increase and maintain student motivation.
Study of Convolutional Neural Networks in the Processing of Medical Images and Classification of Breast Tumors (in Russian)

The problem of medical images analysis and classification of breast tumors is considered. For its solution the application of different convolutional neural networks CNN VGG16, VGG19, ResNet50 v 2, Inseption и Xception is suggested. The experimental investigations of the suggested CNN on the standard data set BreakHis were carried out in problems of binary and multi-class classification. The comparison with known results was performed and efficiency of different CNN was estimated. The best class of CNN for this problem was determined with the highest accuracy.
DEBATE AS A PRACTICE OF ACTIVE CITIZENSHIP

This contribution aims to analyse the spread of Debate as a learning methodology in various European and global contexts, also considering the different debate protocols existing. The study considers the following countries: Italy, England, Bulgaria, Estonia, Finland, France, Germany, Greece, Czech Republic, Slovenia and Romania. Each national debating society aims to spread the practice of regulated debate as an opportunity to promote dialogue and active citizenship. Fundamental is the development of the ability to assert one’s own ideas in a democratic manner, listening and accepting to different ideas.
The Coherent Multi-disciplinary Knowledge Case of Prehistorical Insight: Information Science at the Edge of Structured Data Comprehension

Up to these days, we are experiencing an omnipresent lack of a general approach for cognitive addressing of knowledge structures. This article presents new results and component reference implementations based on frameworks of coherent conceptual knowledge. Coherent conceptual knowledge provides valuable instruments for multi-disciplinary contextualisation, e.g., for contexts in prehistory and protohistory. This research addresses scientific methodologies, valorisation and intelligent re-valorisation of any scientific insight, cognostic addressing of structures, also known as nucleal cognstructures. The resulting component reference implementations enable productive, fertile environments, and learning-improvement-cycles. Central goal of this research is a consistent coherent conceptual integration of knowledge. Prehistory and prehistoric archaeology and their contexts and contextualisation provide a plethora of instructive multi-disciplinary scientific scenarios of high complexity. Thus, component reference implementations for these scenarios are implementation blueprints for informational modeling, industrial learning, and improvement cycles. The results of this long-term research provide solutions based on practical information science, beneficial for prehistory, prehistoric archaeology, and their multi-disciplinary contexts as well as for providing approaches to general solutions.
Strategy of Underground Construction Planning Based on Cognitive Modeling Methodology

Strategy to planning urban underground construction is considered as a tool for sustainable development concept for megapolises. The cognitive methodology, which is viewed as a decision-making process regarding behavior of complex systems in desirable future, is proposed for evaluating prospects of urban underground construction. Introducing disturbances to the vertices, the decision-maker is looking for the answer to the question: “What will happen if ...?” The conducted studies using this methodology allowed to propose a number of scenarios for assessing advisability of underground construction, considering highlighted groups of geological and technogenic factors, uncertainties of various nature and risk factor groups. The employed technique is a new tool for evaluating various risks, likelihoods of negative scenarios and related additional expenses, as early as a pre-project stage of underground construction.
A Method of Increasing the Accuracy of Segmentation of a Speech Signal Based on Its Fractal Characteristics

The paper considers the analysis of approaches to the segmentation of the speech signal into vocalized and not vocalized fragments. The necessity of improving the accuracy of segmentation due to a more accurate description of the process of speech signal representation is shown. A rational method for calculating the fractal dimension to increase the accuracy of the speech signal segmentation process has been determined.