Reviewerly/exHarmony huggingface dataset:
Influence of Parents and Parenting Student Achievement Motivation for Class XI IPS SMPN 9 Palu

Iin Irawati, Taufiq Eka Riandhana, Nur Halifah, 2022. The Effect of Motivation on Learning Achievement of Class XI Social Studies Students at SMP Negeri 9 Palu. The purpose of the study was to obtain information about whether there is an influence of motivation on student achievement in class XI I IPS in SMP Negeri 9 Palu. The method used is a quantitative descriptive method. The population is 133 students at SMP Negeri 9 Palu. The number of research samples as many as 57 people using the Proportional Sampling technique. The data collection technique used a Likert scale model questionnaire, Observation, Interview and Documentation. Data analysis techniques are first to reduce data, present data, and draw conclusions. The results showed that the results of the analysis of the implications of motivation research on learning achievement had a significant effect on increasing students' learning motivation. The motivation of students at SMP Negeri 9 Palu Class XI IPS can be said to be good with a percentage of 63.44%. The motivation that arises in students cannot be separated from the teacher himself. A student learns because it is driven by mental strength in the form of desire, attention, will, or ideals, and this mental strength can be classified as low and high depending on the teacher's efforts to encourage students and give awards so that students feel able to become even better.&#x0D; &#x0D; &#x0D; Keywords: Motivation and Learning Outcomes&#x0D;
PENERAPAN MODEL PEMBELAJARAN KOOPERATIF TERHADAP HASIL BELAJAR MATEMATIKA DITINJAU DARI TINGKAT MOTIVASI

The purpose of this study was to determine the differences in various cooperative learning models such as the Jigsaw type, the STAD type, and the GI type. This research is a quasi-experimental research. The sample consisted of three classes, namely class 7A subjected to treatment I, class 7B was subjected to treatment II, and class 7C to treatment III, sampling was carried out using cluster sampling technique. Data collection techniques using the method of tests and questionnaires. The data analysis technique used Kruskal Wallis non-parametric statistics. The results of data analysis resulted in 5 different hypotheses. The first hypothesis is the value of Asym Sig. 0.000 &lt; 0.05, the second hypothesis obtained the value of Asym Sig. 0.000 &lt; 0.05, the third hypothesis obtained the Asym Sig value. 0.280 is greater than 0.05, the fourth hypothesis is obtained by the Asym Sig value. 0.000 is smaller than 0.05 and the last hypothesis is the Asym Sig value. 0.006 &lt; 0.05.
LORA BASED SPEECH TO TEXT CONVERTER

This project's ultimate goal is to convert speech at one end to text at the other.So, instead of GSM and Wi-Fi, we're using the LoRa (Long Range) module to accomplish this.The problem with those technologies is that they are limited to a certain range and also stop working if the signal is poor.To address this, we are employing LoRa technology.A LoRa module consists of a transmitter and receiver pair.The sender contacts the receiver via mobile phone.The separation between the two ends is around 1km.The speech will be converted into text and displayed on the LCD display at the receiver end.This project will aid in the development of long-distance wireless communication with low power consumption and efficient transmission.
Development of Future Teacher’s Pedagogical Thinking: From Social Situation to Pedagogical

The competence of a modern teacher is largely determined by the presence of a well-formed pedagogical thinking. The proposed chapter is devoted to the conditions of its development in the conditions of higher education. The ways of organizing the interaction of students are considered, in which the social situation is professionally problematized, the experience of self-determination is gained in solving the pedagogical situation.
Modelirovanie reaktsii organizma obuchaiushchegosia na potok monotonno postupaiushchei v protsesse obucheniia informatsii. Kriticheskie sostoianiia organizma

The chapter of the monograph examines how the learning process affects the psychophysiological state of a person. The solution of differential equations describing this process is given. The solution shows that the process under consideration causes periodic fluctuations in psychophysiological parameters, while it is possible to go beyond the permissible limits, which leads to damage to the body.
Innovatsionnaia obrazovatel'naia deiatel'nost' v usloviiakh tsifrovizatsii obrazovaniia

In the context of the accelerated introduction of digital technologies, it is education that should develop in accordance with modern requirements, which requires the active introduction of digital technologies in the educational process in order to train competitive teaching staff. The paper describes the activities of the innovation site of the Birsk branch of Bashkir State University. The novelty of the activity of the innovation site lies in the system-cyclic approach to the formation of professional competencies and key competencies of the digital economy: the activity of the site covers all levels of general, higher, additional education and covers the entire range of staffing needs of educational organizations.
Motivatsiia professional'noi deiatel'nosti i professional'nogo razvitiia pedagogov

The article considers the results of research work on the study and analysis of the current state of motivation for professional activity and professional development of teachers of Saint Petersburg state budgetary educational institutions of general education. Recommendations for improving the activity of educational institutions in the field of formation of teachers' motivation are outlined. The necessity of organizing purposeful, systemic work on the formation of internal motivation of professional activity and professional development among teachers is substantiated.
Development of Students’ Creative Abilities in the Process of Learning in Art Disciplines

The relevance of the study is due to the problem of developing the creative abilities of students of artistic orientation in education. In art universities, the problem of teaching the creative potential of students is acute. Therefore, it is important in the educational process to form the creative potential and artistic and creative abilities of students, depending on their aesthetic needs. Of particular importance is revealed the concepts of artistic image, form and content of the creative work of future artists. It is important to subordinate the entire educational process to the fulfillment of the main tasks of the professional development of young artists.
Reflection of the problems of the digital age in cinematic reflection: the image of the Double

The article attempts to consider the relationship between the Self and the Double through the prism of modern cinema, which, being an integral part of the culture of the digital age, esthetically reveals the problem of the duality of the human Self. On the example of the film &amp;quot;The Enemy&amp;quot; by D. Villeneuve, we observe the process of splitting the subject, the meeting of a person with his double. It is assumed that digitalization makes it possible to consider the Cartesian conclusion about doubt in a new way. Doubt is an indicator of a failure in the measured existence of a person, causing a double to come to life, while the double, in turn, doubts you, emphasizing the presence of yourself and you, who gave birth to him. “I think, therefore, my twins exist” is a thesis that characterizes the modern digital reality in which a person resides due to the constant alienation of a part of his Self, his self-consciousness into virtuality.
ICRP: Internet-Friendly Cryptographic Relay-Detection Protocol

Traffic hijacking over the Internet has become a frequent incident over the last two decades. From minor inconveniences for casual users to massive leaks of governmental data, these events cover an unprecedently large spectrum. Many hijackings are presumed to be caused by unfortunate routing mistakes, but a well-organized attacker could set up a long-term stealthy relay, accessing critical traffic metadata, despite suitable encryption schemes. While many studies focus on the mitigation of known attacks, we choose to design a complete detection method regardless of the attacker’s strategy. We propose a two-party cryptographic protocol for detecting traffic hijacking over the Internet. Our proposal relies on a distance-bounding mechanism that performs interactive authentication with a “Challenge–Response” exchange, and measures the round-trip time of packets to decide whether an attack is ongoing. Our construction is supported by worldwide experiments on communication time between multiple nodes, allowing us to both demonstrate its applicability and evaluate its performance. Over the course of this paper, we demonstrate our protocol to be efficient—itrequires only two cryptographic operations per execution inducing negligible workload for users and very few loss of throughput, scalable—no software updates are required for intermediate network nodes, routing protocol independent—this means that any future update of the route selection process will not induce changes on our scheme, and network friendly—the added volume of transiting data is only about 1.5%.
Mapping Analysis of Development of Digital Book History of Dumai Port Based on Discovery Learning to Increase Historic Awareness of High School Students at Special Purpose State SMA and State SMA 1 Dumai City

The purpose of this study is to analyze and map the needs of students and teachers for the development of digital teaching materials, namely the digital book of the history of the port of Dumai City as local history, and see the level of historical awareness of high school students in Dumai City. This research is part of development research (R&amp;D). This type of research is an expo facto research where researchers collect data systematically directly from respondents through data collection instruments. The process of data collection is a critical stage in research. The data that has been collected will be used to test the hypotheses that have been proposed in the study, where the data were obtained through interviews, observations, and questionnaires. The data analysis technique was carried out in a quantitative descriptive manner. The results of the study indicate that (1) there is a positive view of the need for the development of this digital book in the significantly Assisted State Senior High School and Dumai City 1 Public High School; (2) students' learning motivation is still relatively low for history subjects, this is due to the limited use of digital media used in the learning process; (3) history learning media is still very conventional; and (4) students' historical awareness of the existence of local history is still low.
AN OVERVIEW OF HADOOP JOB SCHEDULING ALGORITHMS FOR BIG DATA

Rapid advancements in Big data systems have occurred over the last several decades. The significant element for attaining high performance is "Job Scheduling" in Big data systems which requires more utmost attention to resolve some challenges of scheduling. To obtain higher performance when processing the big data, proper scheduling is required. Apache Hadoop is most commonly used to manage immense data volumes in an efficient way and also proficient in handling the issues associated with job scheduling. To improve performance of big data systems, we significantly analyzed various Hadoop job scheduling algorithms. To get an overall idea about the scheduling algorithm, this paper presents a rigorous background. This paper made an overview on the fundamental architecture of Hadoop Big data framework, job scheduling and its issues, then reviewed and compared the most important and fundamental Hadoop job scheduling algorithms. In addition, this paper includes a review of other improved algorithms. The primary objective is to present an overview of various scheduling algorithms to improve performance when analyzing big data. This study will also provide appropriate direction in terms of job scheduling algorithm to the researcher according to which characteristics are most significant.
Optimizing Online Time-Series Data Imputation Through Case-Based Reasoning

When working with Intelligent Decision Support Systems (IDSS), data quality could compromise decisions and therefore, an undesirable behaviour of the supported system. In this paper, a novel methodology for time-series online data imputation is proposed. A Case-Based Reasoning (CBR) system is used to provide such imputation approach. The CBR principle (i.e., solving the current problem using past solutions to similar problems) may be applied to data imputation, using values from similar past situations to replace incorrect or missing values. To improve the performance of the data imputation process, optimal case feature weights are obtained using genetic algorithms (GA). The proposed methodology is validated with data obtained from a real Waste Water Treatment Plant (WWTP) process.
Adapting a Fuzzy Random Forest for Ordinal Multi-Class Classification

Fuzzy Random Forests are well-known Machine Learning ensemble methods. They combine the outputs of multiple Fuzzy Decision Trees to improve the classification performance. Moreover, they can deal with data uncertainty and imprecision thanks to the use of fuzzy logic. Although many classification tasks are binary, in some situations we face the problem of classifying data into a set of ordered categories. This is a particular case of multi-class classification where the order between the classes is relevant, for example in medical diagnosis to detect the severity of a disease. In this paper, we explain how a binary Fuzzy Random Forest may be adapted to deal with ordinal classification. The work is focused on the prediction stage, not on the construction of the fuzzy trees. When a new instance arrives, the rules activation is done with the usual fuzzy operators, but the aggregation of the outputs given by the different rules and trees has been redefined. In particular, we present a procedure for managing the conflicting cases where different classes are predicted with similar support. The support of the classes is calculated using the OWA operator that permits to model the concept of majority agreement.
Testing Reinforcement Learning Explainability Methods in a Multi-Agent Cooperative Environment

The adoption of algorithms based on Artificial Intelligence (AI) has been rapidly increasing during the last years. However, some aspects of AI techniques are under heavy scrutiny. For instance, in many cases, it is not clear whether the decisions of an algorithm are well-informed and reliable. Having an answer to these concerns is crucial in many domains, such as those in were humans and intelligent agents must cooperate in a shared environment. In this paper, we introduce an application of an explainability method based on the creation of a Policy Graph (PG) based on discrete predicates that represent and explain a trained agent’s behaviour in a multi-agent cooperative environment. We also present a method to measure the similarity between the explanations obtained and the agent’s behaviour, by building an agent with a policy based on the PG and comparing the behaviour of the two agents.
Analysis of Education Management Information Systems of the Ministry of National Education in Terms of Interoperability

This research, which aims to reveal the current state of the Ministry of National Education (MoNE) information systems in terms of interoperability, was carried out with the basic qualitative research design under the scope of qualitative research. The data that constituted the source of the research were collected from teachers, vice-principals and school principals working in public schools at high school level. Semi-structured interview forms were used as data collection tool. The obtained data were analyzed by content analysis method. As a result of the analysis, the findings were gathered under two themes as intra organizational and interorganizational interoperability. The results of the research showed that the Ministry of National Education has some features in terms of both intraorganizational and inter-organizational interoperability, but it cannot fully use the opportunities arising from the use of the central Education Management Information System (EMIS), and accordingly, there are areas that need to be developed in both dimensions in terms of interoperability. In terms of in-house interoperability, suggestions have been made such as transferring the data in the Education Information Network (EBA) to eschool, moving more student data between education levels, and transferring the data expected from the management levels through information systems by making it pre-defined. In terms of interorganizational interoperability, it is recommended that the MoNE information systems be made interoperable with the Ministry of Health, Higher Education Institution and Social Security Institution.
Fuzzy-LORE: A Method for Extracting Local and Counterfactual Explanations Using Fuzzy Decision Trees

Classification systems based Machine Learning hide the logic of their internal decision processes from the users. Hence, post-hoc explanations about their predictions are often required. This paper proposes Fuzzy-LORE, a method that generates local explanations for fuzzy-based Machine Learning systems. First, it learns a local fuzzy decision tree using a set of synthetic neighbours from the input instance. Then, it extracts from the logic of the fuzzy decision tree a meaningful explanation consisting of a set of decision rules (which explain the reasons behind the decision), a set of counterfactual rules (which inform of small changes in the instance’s features that would lead to a different outcome), and finally a set of specific counterfactual examples. Our experiments on a real-world medical dataset show that Fuzzy-LORE outperforms prior approaches and methods for generating local explanations.
Streamlining Text Pre-Processing and Metrics Extraction

Natural Language Processing involves reshaping and refining data sets into data that can be used for analysis, ensuring that the data is well formatted. The efficiency gap of data scientists spending most of their time preparing data is an opportunity for the technology sector to work on solutions to the problem. For this reason, a web tool has been developed that is capable of, on the one hand, speeding up the text cleaning process and, on the other hand, facilitating the extraction of metrics by analyzing and processing the texts through customized dictionaries in LIWC format, uploaded by the users themselves, and through sentiment analysis. All this, from a single interface that allows the user to customize the whole pipeline offering different modules for pre-processing and metrics extraction in order to be a solution to facilitate, streamline and automate the whole process.
Enhanced kinship verification analysis based on color and texture handcrafted techniques

Abstract Nowadays, kinship verification is considered an attractive research area with a great interest in computer vision. It significantly affects applications in the real world, such as finding missing individuals, forensics, and genealogical research. However, verifying kinship relations between people using facial images is not straightforward. Many limitations affect kinship verification accuracy. Therefore, this paper proposes a new approach for verifying kinship based on facial image analysis. The proposed approach goes into six stages: preprocessing, feature extraction, feature normalization, feature fusion, feature representation, and kinship verification. The preprocessing stage is responsible for converting RGB images into other color models. Different types of handcrafted feature descriptors (i.e., color and texture descriptors) are extracted in the feature extraction stage. The texture features are represented by scale invariant feature transform (SIFT), local binary pattern (LBP), and heterogeneous auto-similarities of characteristics (HASC), whereas the color features are represented by color correlogram (CC) and dense color histogram (DCH). Then, all the features are set to the same range in the feature normalization stage to be suitable for feature fusion. The feature fusion stage takes place where the different types of features are concatenated together. Next, in the feature representation stage, the parent and child features are gathered into one feature vector. Finally, the kinship verification stage produces the final decision of being kin or non-kin using the gentle AdaBoost ensemble classifier. KinFaceW-I and KinFaceW-II datasets were used to evaluate the proposed approach, where the obtained results were 79.54\% and 90.65\%, respectively. It is noteworthy that the proposed approach outperforms many state-of-the-art approaches that verify kinship, including those dependent on metric learning and deep convolutional neural nets (CNNs).
A STUDY ON CSR ACTIVITIES IN BANKING SECTOR AS A FACTOR OF ECONOMIC GROWTH

Corporate Social Responsibility (CSR) is the compliance of social and environmental aspects throughout the operation of the organization. Business rivalries started taking heavy toll on the quality, transparency, environment and the society in general endangering the peaceful coexistence of business and society. The businesses houses started realizing that they would have to rise over and above the profitability and take care of all those associated with their survival in the society directly or indirectly. This realization resulted into the concept of Corporate Social Responsibility (CSR). This research paper moves around developing an understanding about the corporate social responsibility (CSR), its concept and finding out its scope taking the case study of the SBI.
Student's Media Competence: New Opportunities to Counteract Information Manipulations In Network Interactions

The purpose of the study was to assess the media competence of students, to determine the possibilities and limitations for its formation in the context of the intensification of digital network interactions.The focus of the study is on studying the skills of students in terms of assessing the reliability of information sources, the adequacy and completeness of information, as a tool to counter information manipulations.The key research method was a questionnaire survey of students (N = 148).A low level of formation of media competence of students in terms of skills for assessing the reliability of an information source has been established, which becomes a factor in the vulnerability of students in the context of the spread of disinformation.Established the presence of dysfunctions that impede the formation of media competence: a test system for assessing knowledge, the absence of special tasks aimed at developing the skills of searching, evaluating using information.The functional weakness of higher education in terms of the formation of ethical principles of digital interaction of students has been established.The conclusion is made about the demand for a reflective pedagogical method, collective discussion of media texts, work on media platforms.