Reviewerly/exHarmony huggingface dataset:
An Investigation of the Relationship between Receptive Skills among Moroccan High School Students

As the prevalence of the English language in the Moroccan educational system continues to rise, there is a pressing need for an in-depth exploration of language development dynamics, explicitly focusing on listening comprehension and reading proficiency. This correlational study investigated the relationship between listening and reading skills among 80 high school students from Al Mansour Addahbi High School in Sidi Kacem, Morocco. The sample was selected using a simple random sampling technique. Data were collected through standardized listening and reading proficiency tests, and statistical analyses were conducted using SPSS software. The results revealed a significant positive correlation (r = 0.604, p &lt; 0.001) between listening skills and reading skills, indicating that students with higher listening abilities also demonstrated stronger reading skills, and vice versa. Furthermore, regression analysis showed that listening skills significantly predicted reading skills (Beta = 0.604, p &lt; 0.001), emphasizing its importance as a key predictor of reading ability. The findings contribute to the field of EFL education by emphasizing the interdependence of listening and reading skills, suggesting the need for integrated language instruction strategies. Recommendations for future research include exploring this relationship across different age groups and linguistic backgrounds and investigating the long-term impact of language instruction interventions on both skills.
Student assessment of their mathematical education in a postgraduate course in administration

The objective of the research was to assess student satisfaction regarding their mathematical education in a postgraduate course in administration based on remote teaching during the covid-19 pandemic. The research approach was mixed with a sequential exploratory design. A questionnaire was developed and administered to 65 participants about the type of technological devices used, the challenges faced, and students’ assessment of their level of mathematical education. The results showed that students acknowledged experienced logistical, emotional, and academic challenges during the emergency period. Statistically significant differences were also found because remote teaching promoted mathematical education through effective use of video conferencing, enabling the integration of learning into professional performance, assisting in course planning and adaptation explained by the faculty, and benefiting from the use of virtual databases and asynchronous communication. Additionally, the students rated competences related to administrative situations, mathematical terminology, and the use of tables and graphs at a consolidated level. The conclusion is to incorporate Microsoft Teams as a permanent platform because it promotes timely and continuous monitoring by the faculty, which encourages the mathematical education of the students.
Enhancing Trap Shooting Proficiency through Dynamic Home Practice Simulation: A Novel Approach for Precision and Consistency Improvement

I noticed that most trap shooters practice dry firing towards a wall, pretending that there is a target on the wall, going right or left [1]. However, they are not aware if they have come close to or “hit” the target by just imagining it. It is very dull to lift a gun toward a wall with nothing on it. I decided to create a Python program to have a person practice and shoot as if at a range [2]. The program lets a person practice the correct technique which involves not moving the gun with their arms, but with their core. The shooters can practice peripheral vision, pulling the trigger at the right time and following the target. Results have shown that people were more engaged using the program while lifting a gun, than only lifting a gun towards the wall.
An Efficient Content-Based Image Retrieval Using Threefold Technique

Managing large amounts of information in the digital world requires an efficient and effective image retrieval system. Content-based image retrieval (CBIR) has garnered tremendous attention and effort over the past few years. Several CBIR systems have been proposed using both onefold and twofold approaches. This paper introduces a new threefold content-based image retrieval system (TfCBIR), which is built on a threefold approach and consists of two modules. As part of its first module, TfCBIR analyzes images to extract color, texture, and shape information. The second module includes three steps. The first step involves comparing the color feature space of all the images with the query image to find the most similar $$S$$ images. In the next step, the shape feature space is compared with the image query for the $$S$$ images obtained in the first step to retrieve the closest $$S1$$ images. Finally, in the third step, the texture feature space is compared with the query image for the $$S1$$ images found in the second step, and the $$R$$ most relevant images to the query image are obtained as output. The proposed TfCBIR system has been shown to outperform existing state-of-the-art CBIR methods.
Meetei Mayek, Hindi, and English Text Detection from Natural Scene Images Using YOLO

Detecting text in a natural scene image is a crucial computer vision task. This paper presents a multilingual text detection system for detecting Meetei Mayek, Hindi, and English text. The proposed work will serve as a prerequisite for developing a natural scene character recognition system for the mentioned languages. With the evolution of deep learning models, You Only Look Once version 7 (YOLO V7) object detector has been used for detecting text from natural scene images along with language identification. The mean average precision for individual language text detection has been computed. Moreover, the mean average precision with images having more than a single language has also been calculated and the results are appreciable.
Seismic Soundoff: The sound of seismic

Paolo Dell'Aversana highlights his recent article in The Leading Edge, “An expanded idea of imaging in geophysics through multimodal data analysis.” The article explores a dual-sensory approach to understanding seismic data. This episode unlocks secret information hiding in seismic data that is waiting to be discovered.
Enhanced Task Scheduling Using Optimized Particle Swarm Optimization Algorithm in Cloud Computing Environment

The most significant constraint in cloud computing infrastructure is the job/task scheduling which affords the vital role of efficiency of the entire cloud computing services and offerings. Job/ task scheduling in cloud infrastructure means that to assign best appropriate cloud resources for the given job/task by considering of different factors: execution time and cost, infrastructure scalability and reliability, platform availability and throughput, resource utilization and makespan. The proposed enhanced task scheduling algorithm using particle swarm optimization considers optimization of makespan and scheduling time. We propose the proposed model by using dynamic adjustment of parameters with discrete positioning (DAPDP) based algorithm to schedule and allocate cloud jobs/tasks that ensues optimized makespan and scheduling time. DAPDP can witness a substantial role in attaining reliability in by seeing the available, scheduled and allocated cloud resources. Our approach DAPDP compared with other existing particle swarm and optimization job/task scheduling algorithms to prove that DAPDP can save in makespan, scheduling and execution time.
Students’ Academic Freedom According to the Expert Interviews

&nbsp;&nbsp;&nbsp; The article is based on qualitative research -the expert interviews. 14 professionals well-acquainted with the educational and university context working in the following spheres: philosophy, science of education, sociology, and the sphere of organizing and management of higher education participated in the research. They were former and present representatives of these spheres, members of non-governmental organizations and representatives of the civil sector who are known to Georgian society via various mass media facilities as experts on education. The research took place in Tbilisi in July and August 2023. Alongside the empirical research, the fundamental scientific works and various secondary data on academic freedom were analyzed. Since the disintegration of the Soviet Union, the universities in Georgia have not made serious progress regarding academic freedom. Though academic freedom is guaranteed and protected by the Consitution of Georgia, the general situation in the country, especially during the recent decade – economic and political instability, vulnerability of labour rights, scanty investment into education and science - does not create profitable conditions for proper development of universities. Therefore, the most important aspects of academic freedom as the condition of arranging university activities and as the fundamental value are still on the agenda in our country. Students' academic freedom is among them as well. Asa resultof the research, it became clear that the academic freedom of students is limited; the factors limiting the academic freedom of students are the following: labour market demands, limited free choice in the process of learning and research; artificial barriers existing in the university management, weakness of the organizations and movements protecting students’ interests, absence of the experience necessary to protect academic freedom, conformist culture, favouritism, hidden mechanisms of pressure and controle, bureaucracy, etc. All these and other factors hinder the realization of students'academic freedom
Patent-Eligible Invention Requirement Under the European Patent Convention and its Implications on Creations Involving Artificial Intelligence

Artificial Intelligence and its subfield, Machine Learning are areas of computer science; thus, they rely on algorithms, models, computer programs and software applicable in numerous areas. Since respective creations involve resources and shift from hardware to software, there is an incentive to protect them legally. Due to their dual nature, the algorithms, models, computer programs, and software might be too “technical” to avail copyright protection but not “technical” enough for a patent. Whereas trade secret protection might not be sufficient means of protection in all cases.The article explores the issues and, as its main argument, builds further on the academic proposals on the sui generis mechanism. It also suggests certification as the potential approach to avail the desired protection instead of diluting the existing protection frameworks. An alternative would be to lie on the complete availability or trade secret protection, none of which would be an adequate balance.
REVIEW OF CLOUD DATABASE BENEFITS AND CHALLENGES

The volume of data is increasing rapidly, that is why using cloud computing to store and process data may be inevitable. Providers offer many database services in public cloud that include many types of traditional relational and non-relational databases, as well as special purpose databases. Organizations can then migrate their data to cloud databases, however, decisions makers need to be aware of cloud benefits and challenges. Data in cloud is globally distributed, computing resources can be scaled up or down according to demand, cloud providers guarantee high level of service availability, many manual database administration tasks are automated. Data partitioning, replication and scaling ensure high performance. Certain applications of databases are cheaper than in private environments, however, sometimes using cloud database may be more expensive. Security is considered as a one of the main cloud database concerns due to storing data in external infrastructure. Due to regulations, organizations have to consider data privacy issues. Shared infrastructure offered in cloud is beneficial, however, sometimes isolated environments are better for cloud databases.
Designing Innovative Model of Education Content Based on Traditional Values of Folk Culture in Context of Interaction of General and Additional Education

The relevance of this article is determined by the tasks of preserving the values of folk culture as a source of social transformations in our society for its stable functioning and development. The aim of the work is to substantiate the innovative model of the content of education – the School of Folk Culture as a value model in the interaction of general and additional education. The article identifies the organizational and pedagogical conditions for the education content based on the values of folk culture, including the structure, curricula and programs, subjects and subject cycles for different levels of both school and additional education, including their interaction. Groups of folk culture values are revealed: family, labor and public service. The concept of education content in folk culture has been clarified, and the didactic factors of folk culture included in the structure of the education content model have been determined. The constituent components of the fundamental core of the ethno-cultural educational standard for the Schools of Folk Culture have been developed.
The Effect of Using Flashcard to Improve Language Skills in Children with Speech Delay

Language is one of the essential aspects of life because it is a communication tool used in interacting with social beings. One of the aspects of early childhood language development is speaking. The ability to speak is essential for children to meet their communication needs. Speech delay is a tendency that is difficult to feel when you want to convey information or interact with other people. This study aimed to determine whether the use of picture word card media can affect the language improvement of children who experience speech delay. The type of research used is single-subject research. The independent variable in this study is the therapy of giving picture word cards, and the dependent variable is language ability. The subjects in this study were children aged three years who experienced speech delay. The data collection method used observation, which refers to aspects of language development that consist of understanding, expressing, and literacy. Analysis of the data used in the analysis of paired sample T-test and descriptive in the form of tables and graphs. The results of this study indicate that the use of picture word cards can significantly improve language skills in children with speech delay, with t = -5.382 and p = 0.001 &lt;0.05. The data analysis is the analysis of paired sample T-test and descriptive in the form of tables and graphs. The results of this study indicate that the use of picture word cards can significantly improve language skills in children with speech delay, with t = -5.382 and p = 0.001 &lt;0.05. The data analysis is the analysis of paired sample T-test and descriptive in the form of tables and graphs. The results of this study indicate that the use of picture word cards can significantly improve language skills in children with speech delay, with t = -5.382 and p = 0.001 &lt;0.05.
The number of distinct adjacent pairs in geometrically distributed words: a probabilistic and combinatorial analysis

The analysis of strings of $n$ random variables with geometric distribution has recently attracted renewed interest: Archibald et al. consider the number of distinct adjacent pairs in geometrically distributed words. They obtain the asymptotic ($n\rightarrow\infty$) mean of this number in the cases of different and identical pairs. In this paper we are interested in all asymptotic moments in the identical case, in the asymptotic variance in the different case and in the asymptotic distribution in both cases. We use two approaches: the first one, the probabilistic approach, leads to variances in both cases and to some conjectures on all moments in the identical case and on the distribution in both cases. The second approach, the combinatorial one, relies on multivariate pattern matching techniques, yielding exact formulas for first and second moments. We use such tools as Mellin transforms, Analytic Combinatorics, Markov Chains.
Application of the KNN method to check soil compatibility using a microcontroller for android-based banyuwangi citrus fruit plants

The city of Banyuwangi needs a touch of information technology in the agricultural sector, namely in the process of planting orange fruit, because orange fruit planting is carried out continuously to meet export needs. Citrus fruit planting is sometimes carried out without paying attention to the existing soil nutrient content, this condition can result in less than optimal harvest results. The research was carried out by creating a soil nutrient detection application with the aim of providing information to farmers about the soil nutrient content including nitrogen, calcium, phosphorus, pH and moisture resistance before planting citrus fruit. From the results of trials conducted by researchers with farmers based on various types of soil used as trial data, the information shows a match of 89.6%. The results of the research produced an Android-based soil nutrient checking application that farmers can use to check soil nutrients when planting citrus fruit. In conducting the research, the researcher created an application by applying the KNN method and utilizing a microcontroller to input the data. By combining methods and tools, microcontrollers can assist the implementation process so as to provide information in the form of soil suitability for planting citrus fruit based on the nutrient content of the soil being examined. The contribution made from the research results is the application of a KNN method which is used to check soil nutrients so that it can maximize the results of the detection carried out. Meanwhile, another contribution is the use of a tool in the form of a microcontroller which is used to automatically input data which can be obtained using the Bluetooth service in the soil nutrient check application.
Vladimir Grigor’yevich Kornilov (on the centenary of the birth)

The creative life of the outstanding writer Vladimir Grigor’yevich Kornilov is described in the article. The author’s reminiscences of Vladimir Kornilov, the former’s impressions of this person form the basis of the feature article; Vladimir Kornilov’s contribution to the formation and development of Kostroma writers’ organisation is noted as well as his attention and painstaking work with novice writers. Courage, realism and writing skills of Vladimir Kornilov are emphasised in particular. It is mentioned in the article about Vladimir Kornilov’s awards, about his achievements in the field of literature and social activities; warm memories of people who knew Vladimir Kornilov, are cited.
Inquiry Based Learning Approach in Teaching “Phase Transitions” for Experimental Skills Formation in Nearly 16 Years Old Students

Inquiry-based learning is an important pedagogical approach through which teachers can introduce students to the world of science and scientific research. Learning through inquiry is an active learning that requires students to take responsibility, make decisions, cooperate and self-assess. The role of the teacher is crucial when using the research approach in physics lessons, so it is important that he knows the experience of other colleagues, their ideas and good practices. The teacher is the one who guides the students in conducting research, supplying equipment and processing experimental data. We are convinced that the best way for students to understand the essence of science is by doing their own scientific research. The report offers an idea for the formation of experimental skills by conducting inquiry on several specific problems related to thermal phenomena. Teams of students are formed, who choose to work on one of several proposed experimental tasks related to phase transitions. These tasks are borrowed from the International Young Physicists Tournament (IYPT) and are adapted to the conditions of the Bulgarian school and the respective curriculum. In solving them, students follow the steps of a scientific research - discuss the specific situation and formulate a scientific question, perform a physical experiment, collect and analyse results, draw conclusions that are confirmed experimentally. The proposed tasks are related to the following topics: • Melting and solidification of crystalline and amorphous bodies (two tasks) • Conditions on which the evaporation process depends (one task) • The specifics of the boiling process (one task). The formation of experimental skills occupies an important place in the physics curriculum for 8th grade Bulgarian schools. In recent years, there has been a tendency in the teaching of physics to develop more and more active practical and experimental skills. Teachers are looking for ways to do this both during classes and extracurricular activities, using modern interactive methods and approaches. The report describes the methods by which the learning process is organized and offers a proven technology of training on these physics topics. Key words: inquiry-based approach, experimental skills, physics training, phase transitions
Automatic Image and Video Tagging Survey

Marking content with descriptive terms that depict the image content is called “tagging,” which is a well-known method to organize content for future navigation, filtering, or searching. Manually tagging video or image content is a time-consuming and expensive process. Accordingly, the tags supplied by humans are often noisy, incomplete, subjective, and inadequate. Automatic Image Tagging can spontaneously assign semantic keywords according to the visual information of images, thereby allowing images to be retrieved, organized, and managed by tag. This paper presents a survey and analysis of the state-of-the-art approaches for the automatic tagging of video and image data. The analysis in this paper covered the publications on tagging in Scopus and the Web of Science databases from 2008 to 2022.
An Integrated Information Gain with A Black Hole Algorithm for Feature Selection: A Case Study of E-mail Spam Filtering

The current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets, and feature selection is based on a fitness function that is proportional to the accuracy achieved using a Naive Bayesian Classifier (NBC). When measuring the performance of the BBH with the SpamBase dataset, the performance of the classifier and the dimension of the selected feature vector used as a classifier input are considered. The experiments revealed that the BBH can produce good FS results even with a small set of selected features. This shows that when utilizing the NBC-based BBH, good spam email categorization accuracy is possible.