Reviewerly/exHarmony huggingface dataset:
TECHNOLOGIES FOR THE DEVELOPMENT OF CROSS-DISCIPLINARY COMPETENCE OF FUTURE TEACHERS OF PROFESSIONAL EDUCATION

New technologies determine the civilizational development of mankind, affect the quality of life of people all over the world, regardless of whether it is a big city or a remote rural settlement. The use of new means of livelihood radically changes the character of a person in the modern conditions of reform. Therefore, in today's world, it is very important for a specialist to be able to solve new problems in non-standard situations, as well as independently acquire information and critically evaluate it, and not just accumulate and memorize it. The subject of the study: technologies for the development of cross-disciplinary competence of future teachers of professional education. The purpose of the article: to characterize modern technologies for the development of cross-disciplinary competence of future teachers of vocational training. A feature of the professional activity of a teacher of vocational training is the use of cross-disciplinary competence as a basis for applying knowledge, its synthesis and increasing the effectiveness of student training, forming in them the knowledge and skills necessary for effective professional activity in modern society. Cross-disciplinary competence contributes to overcoming disciplinary boundaries, which are determined by the peculiarity of the pedagogical activity of a teacher of vocational training. The research methodology is based on general research methods of analysis, synthesis and generalization. Conclusions. Cross-disciplinary competence in future teachers of professional education is the basis for successful professional activity. The cross-disciplinary competence of a vocational teacher is based on the ability to comprehensively apply knowledge, synthesize it, transfer ideas and methods from one field to another, and show creativity and originality in all this. For the development of cross-disciplinary competence in future teachers of professional education, in our opinion, it is advisable to use: technologies for the development of communicative competence; technologies for the development of digital competence; technologies for the development of critical thinking; problem-based learning technologies; STEM technologies; technologies of emotional development; training technologies; H. Altshuller's technology.
SCIENTIFIC JOURNAL AS SOCIO-COMMUNICATIVE PHENOMENON: FORMATION AND DEVELOPMENT TRENDS

The need to study a scientific journal as socio-communicative phenomenon is caused by a rapid development of communication processes in the scientific sphere and the need for the integration of Ukrainian science into the world scientific and cultural spaces. The number of scientific journals is growing exponentially, globalization in scientific communication is deepening. Thus, the study of the formation and development trends of scientific journals, the generalization of world and Ukrainian experience in scholarly publishing is extremely important. The research was carried out using analysis, synthesis, classification, comparison. The logic of our research develops from the selection of facts, their study, systematization, and generalization to the prediction of the development of a scientific journal as a social-communication phenomenon. To summarize the theory, historical and logical methods were applied. Based on a systematic approach, we reached the conclusions and distinguished the trends of scientific publishing. The world of scientific journals is a structured and hierarchical system. Their functions include verification, storage and dissemination of scientific knowledge. The main characteristics of a scientific journal as a social communication phenomenon are following: 1) to support of scientific communication; 2) to fix communicative roles of participants of the editorial and publishing process; 3) to focus on civilizational challenges; 4) special language and text; dependence on English as the language of international scientific communication. A scientific journal enables theorists and practitioners to obtain new information in the field of fundamental and applied research, to familiarize themselves with new methods of scientific studies, helps to understand the trends of scientific discourse, contributes to the design and forecasting of scientific activity, provides a guide about how research results should be presented in terms of content and form. As powerful accumulators of verified scientific knowledge, scientific periodicals create the space of scientific communication, uniting the scientific community and building its interaction with society, business and the state. Authors, editors and reviewers, as well as consumers of scientific content, participate in scientific communication through a scientific journal. Awareness of the laws of scientific journal evolution and the generalization of the best practices in this field can be a methodological basis for the development and implementation of an effective policy in the field of scientific press publishing in Ukraine.
Naïve Bayes Supervised Learning based Physical Layer Authentication: Anti-Spoofing techniques for Industrial Radio Systems

Physical Layer Security (PLS) based authentication schemes are an alternative to conventional security schemes such as e.g. certificates or Message Authentication Codes (MACs). They can provide a more lightweight solution compared to traditional cryptography in order to meet the requirement of secure data transmission. However, errors in Physical Layer Authentication (PLA) techniques can occur due to adverse influences resulting from PLS schemes such as receiver noise or fading channels. Skillfull methods are therefore required in order to detect anormal system behaviour. One promising solution are supervised classification schemes. The application of Naïve Bayes (NB) classifiers for PLA is therefore proposed and evaluated within this work. Prior to that, we analyse the resource efficiency within typical Ultra Reliable Low Latency Communication (URLLC) applications and conduct a security overhead analysis. We propose strategies in order to overcome the problem of missing training data from either the URLLC user or attacker node. A real world Software Defined Radio (SDR) based testbed using OFDM (Orthogonal Frequency Division Multiplexing) is implemented in order to evaluate the performance of NB based PLA. The measurements are conducted within the german campus network frequency band (LTE band 43). Further, we conduct a hyperparameter optimization (HPO) based on random search. The investigated classifiers show promising results in terms of authentication accuracy and Receiver Operating Characteristic (ROC) curve performance.
Balanced Literacy Approach-Based Learning Model Containing Thai Core Values for Basic Literacy Learning in Early Grades

This article presents the findings of research and the development of a learning model based on a balanced literacy approach for early elementary school students' basic literacy instruction. Research and development (R&amp;D) research that has been implemented adopts the Borg and Gall version of the development model. The research has been carried out through a preliminary study stage carried out by applying a qualitative descriptive approach; developing prototype learning models, followed by validation of material and learning experts; the evaluation was carried out by testing the implementation of the model in class I, II, and III. Data collection techniques are questionnaires, observation, interviews. Data analysis with quantitative and qualitative descriptive. The developed learning model consists of 4 stages of learning activities, namely stage I exploring sources of information, stage II implementing a balanced strategy, stage III presenting information, and stage IV reflection. The results of the model validation developed from material experts show an average score of 3.6 (very good category) and an average score of learning expert validation of 3.6 (very good category). The results of the trial implementation of the model show that the average learning achievement in class I is 91 out of an average initial ability of 84. The results of the student response questionnaire to the implementation of the learning model in class I showed an average score of 3.3 (very good category), class II showed an average score of 3.7 (very good category), and class III showed an average score of 3.5 (very good category). Overall, pupils are highly engaged in learning since this learning gives a variety of inventive and diverse literacy exercises.
Preface: 2022 International Conference on Environment Engineering, Nanomaterials and Chemical Technology (EENCT 2022)

2022 International Conference on Environment Engineering, Nanomaterials and Chemical Technology (EENCT 2022) was successfully held online during December 10-11, 2022 in Sanya, China. The conference invited scholars and experts in the fields of environment, chemistry and biology from various universities to participate in the review and guidance of this conference. EENCT 2022 aims to provide an international cooperation and exchange platform for experts and scholars to share their research achievements, discuss the key challenges and research directions, and jointly promote the industrialization cooperation and continuous innovation. This collection of proceedings compiles oral and paper presentations submitted by the authors and scrutinized by the special committee.&#x0D; The opening ceremony was held in the main venue and a speech was delivered by the invited speaker. After the main venue, we divided the invited authors into 2 groups. Each author spoke for about 10-15 minutes on detailed material in the slides, with the same amount of time set aside for questions and discussion. This conference has brought together many excellent works and the latest ideas and concepts. We wish to thank all authors and participants for providing their valuable contributions for this proceeding as well as the reviewers for their constructive recommendations and criticism aiding to improve the presented articles.&#x0D; With our best regards,&#x0D; Conference Organizing Chair&#x0D; Sanya, China
Analisis Kemampuan Siswa Berdasarkan Gaya Bahasa dan Intelegensi dalam Menentukan Unsur Intrinsik Teks Bacaan Cerita Anak

This study aims to analyze students' ability to determine the intrinsic elements of children's story texts. This study used the descriptive qualitative method. It involved the fourth-grade students at State Elementary School 30 South Pontianak with a total o 22 students. Data were collected from a multiple-choice test consisting of 40 questions. Data were analyzed with 4 stages of data collection, data reduction, data presentation, and drawing conclusions. The results showed that the student’s average ability to determine intrinsic elements in children's story texts was 75.8 with a good category. Furthermore, 6 students (0.27%), 9 students (0.42%), and 7 students (0.31%) respectively showed very good, good, and sufficient categories in determining the intrinsic elements of the children’s story text. It can be concluded that some students still have difficulties in determining the intrinsic elements of children’s story texts.
The feature selection strategy of few-shot learning based on causal inference

Statistical learning methods require large-scale data to make the significant generalized probability and observation error close to each other. Few-shot learning can alleviate this situation, but it cannot break through the limitations of statistical learning methods. The training model only depends on the correlation between data distributions. There may be potential risks in applying these models to decision-making in the natural environment. This paper studies feature selection in small sample regression analysis based on AutoMPG and MOP The performance of the two datasets on the regression task is first verified through three classical regression analysis models. Then, through the causal inference method, this paper analyzes the causal effect of the relationship between the features in the dataset and finds that two groups of features do not have a causal relationship. Finally, by setting up a simulation environment, this paper illustrates the potential risks of not considering the causal effect in feature selection.
The Influence of Grammarly towards Indonesian EFL Students’ First-Degree Thesis Writing Confidence

Students completing their studies in the English Education Study Program must be required by thesis writing and submission. It was also acknowledged that the supervisors had afforded proper supervision. Nevertheless, for the English structure of the thesis writing correctness, it still needed help from an application, Grammarly. Therefore, this research aimed to describe the research participant’s engagement and how the application has influenced confidence in writing a thesis, and the confidence is exposed as a case to picture out. To determine which students worked using the application to write their thesis, a questionnaire was distributed to forty students enrolling in the ninth semester of the academic year 2019/2020. The result of the determination found twenty-nine students using the application to refine their writing subjects, and three of them working on their thesis writing completion under supervision using premium Grammarly were selected as the participants for this research. The selection criteria were on the basis of positive attitudes towards Grammarly, working on the thesis writing completion, and possessing a premium Grammarly account. The data of this research were participants’ error types collected from the thesis draft reviewed and their revision, and their opinion of the engagement and influence of Grammarly on writing confidence resulted from the interview. This research revealed that the participant’s thesis writing confidence was influenced by Grammarly diversity. Despite that diversity, as the case, this research inferred that the participants have positive emotions and attitudes in using Grammarly. The implication of this research is the promotion number of Grammarly users in the first-degree study program to make the supervision faster and the thesis writing better.
LBMMS

In the area of computer machinery, cloud computing is magnificent. It has been utilized in recent years to produce cost-effective and adaptable information technology services from exploring online webs to elevated-performance computing and communications outsourcing. The different sorts of bandwidth consumers have been rapidly expanding in recent years. Cloud computing, also known as internet computing, has grown in popularity as a way to deliver a variety of services and resources to online users. Cloud computing makes use of the internet to do large-scale operations. The primary goal of cloud computing is to transparently exchange and estimate data and services across a large network of nodes. One of the most important features of cloud computing is load balancing. The load is separated into three categories: CPU load, memory capacity, and network load, which is the dimension of work performed by a computer system. Load balancing is distributing a system’s load among many nodes to develop resource efficiency and task response time by evading a state in which a few nodes are excessively loaded while others are underloaded. This work presents load balancing with Max-Min of summation (LBMMS), a scheduling method that combines minimal completion time and the lowest cost. LBMMS can enable the effective usage of computing resources in cloud computing for our case study.
Relevance of Multifactor Authentication for Secure Cloud Access

Authentication is one of the key aspects that establish information security. When a user is to be authenticated in a cloud environment, the deployment of a strong, effective and robust authentication system becomes a crucial requirement, especially when access is to be granted for financial and critical data access applications. The usage of a single-factor knowledge-based scheme solely does not meet the security requirements. Even the usage of a possession-based or a biometric-based scheme alone does not prove to be a user-friendly and cost-effective solution. Such schemes incur huge setup and maintenance expenditures and interfere with the privacy of users by invading their biological factors. The only robust solution for verifying the users’ identity in an insecure cloud environment is the usage of an authentication scheme based on multiple factors. Although multifactor authentication techniques elevate security levels, they may suffer from poor usability issues. Thus, it is imperative that a multifactor authentication scheme should achieve higher security and the effective usability at the same time. Depending upon the expenditure and the level of security required, organisations have a large number of choices for implementing multifactor authentication techniques. Such models may incorporate knowledge-, possession- or biometric-based scheme. This chapter focuses on the importance, need and implementation options of various multifactor authentication models for insecure cloud environment that proves to be cost-effective, secure and user-friendly, thereby striking an adequate balance between enhanced security and effective usability. It further discusses the application areas, challenges and future of multifactor authentication.
M3IL: Multi-Modal Meta-Imitation Learning

Imitation Learning (IL) is anticipated to achieve intelligent robots since it allows the user to teach the various robot tasks easily．In particular, Few-Shot Imitation Learning (FSIL) aims to infer and adapt fast to unseen tasks with a small amount of data. Though FSIL requires few-shot of data, the high cost of demonstrations in IL is still a critical problem. Especially when we want to teach the robot a new task, we need to execute the task for the assignment every time. Inspired by the fact that humans specify tasks using language instructions without executing them, we propose a multi-modal FSIL setting in this work. The model leverages image and language information in the training phase and utilizes both image and language or only language information in the testing phase. We also propose a Multi-Modal Meta-Imitation Learning or M3IL, which can infer with only image or language information. The result of M3IL outperforms the baseline in the standard and proposed settings. Our result shows the effectiveness of M3IL and the importance of language instructions in the FSIL setting.
Evaluation of Quantum Key Distribution for Secure Satellite-integrated IoT Networks

There has been a dramatic increase in the number of Internet of Things (IoT) devices and their applications. Furthermore, there is a growing impetus to integrate IoT networks on a global scale, using satellites to expand the range of IoT connectivity into geographically remote areas. Ensuring the security of satellite backhaul for IoT networks is thus of paramount importance. The steady advance of quantum computing in recent years threatens to nullify classical cryptographic approaches based on assumptions of computational hardness, motivating the need for post-quantum cryptography. Quantum computing algorithms have been developed that, once a quantum computer of sufficient scale is realised, will be able to break classical cryptosystems efficiently (at polynomial-time complexity). A promising method of securing information against this threat at the physical layer has emerged in the form of quantum key distribution (QKD). QKD exploits the fundamental physical properties of light to guarantee information-theoretic security. Research into the application and standardisation of QKD to secure satellite backhaul, however, is still in its infancy. This paper presents a brief overview of the theoretical basis for QKD, whilst also providing a survey of contemporary QKD protocols. It evaluates the ability of these protocols to secure satellite backhaul in the context of a typical satellite-IoT network architecture. Furthermore, it highlights the vulnerabilities, as well as the technical challenges associated with this endeavour. Finally, it proposes directions for future research and development into protocols and standardisation for the satellite-integrated IoT domain. Several challenges must be overcome before QKD can evolve into a global-scale solution for securing satellite-IoT. Secret key generation rate remains very low in practical demonstrations of trusted-relay QKD satellite architectures. Further research is needed to overcome or mitigate the fundamental rate-distance trade-off before satellite QKD can be considered practicable in an IoT application. Alternatives that do not rely on trusted nodes are contingent on nascent technologies such as quantum repeaters and quantum memory. Whilst in theory QKD provides perfect information-theoretic security, it remains vulnerable to attacks that exploit imperfections in real-world equipment. Further effort is needed to develop QKD protocols that can safeguard against the aforementioned challenges.
Towards a Critical Review of Cybersecurity Risks in Anti-Poaching Systems

Anti-poaching operations increasingly make use of a wide variety of technology for intelligence and communications. These technologies introduce cybersecurity risk, and they need to be secured to provide greater protection to the information and people involved in anti-poaching operations, ultimately protecting vulnerable animals better. A hypothetical network of anti-poaching technologies was simulated in Graphical Network Simulator 3 (GNS3), consisting of various field devices identified in the literature, and a main control room with relevant hardware devices. A virtual Kali Linux machine was connected to the network and played the role of a digital attacker or intruder. Several cyber-attacks were carried out, to show the risks inherent to such an interoperable and socio-technical network. These attacks included Man in the Middle (MitM) and Denial of Service (DoS) attacks. These attacks were then mitigated via system configurations. Further risks and threat considerations were identified in the literature. Using the STRIDE, DREAD and Attack Tree threat models, the risks to an anti-poaching network were classified and calculated. The most prevalent threats and the attacks performed in the simulation were all calculated to have a high risk level, posing a great threat to an unsecured network. The STRIDE classes of Denial of Service and Elevation of Privilege posed the most risk to the system, both having a calculated average risk score of 9 out of 10. Mitigations to general network threats and those identified in the simulation are mentioned. Additionally, authentication for such a system was investigated, as improper authentication practices were deemed a risk and provides a foothold for further risks in the network. Recommendations made, include the proper configuration of network devices, especially the router and switch, and the use of anti-virus, firewalls, and intrusion detection systems, as well as having an external audit performed annually. Multi-factor authentication, with a password/fingerprint combination, is recommended.