Reviewerly/exHarmony huggingface dataset:
Current Assessment Methods of Investigator's Psychological Readiness for Professional Activities: Improvement Perspectives

Despite the fact that this category of psychological readiness for professional activity is actively considered and researched, scientists do not have a consensus on its semantic content. This situation complicates the development and implementation of the methodological apparatus. Summarising the theoretical analysis, it can be noted that the intersection of the concepts of “psychological readiness” and “professional activity of an investigator” is insignificant. The foregoing allows us to formulate the purpose of the article, which is to find out the ways to improve the assessment of investigators' psychological readiness for professional activity. The aim involves the following tasks: 1) to identify the structure of investigators' psychological readiness for professional activity; 2) to select and analyse the available psychodiagnostic methods aimed at identifying the level of psychological readiness for professional activity of representatives of high-risk professions; 3) to find out the prospects for improving the methodology for assessing investigators' psychological readiness for professional activity. The research methodology included the following steps: 1) analysis of the available options for the structure of psychological readiness as such; 2) substantiation of the author's approach to the structure of psychological readiness of investigators for professional activity; 3) selection of psychodiagnostic methods used to determine the psychological readiness of individuals for high-risk professional activity; 4) finding a correspondence between the parameters studied using psychodiagnostic methods and the components of the structure of psychological readiness of investigators for professional activity; 5) mathematical and statistical analysis of the effectiveness of the psychological readiness of investigators for professional activity. The theoretical and methodological analysis of the research allowed us to develop an approach to considering the structure of psychological readiness of investigators for professional activity. The structure of psychological readiness includes five components: 1) intellectual and cognitive; 2) emotional and volitional: 3) behavioural and reactive; 4) moral and ethical; 5) value-evaluation. The study revealed that psychodiagnostic techniques used in the practice of identifying psychophysiological characteristics of representatives of high-risk professions characterise the structure of investigators' psychological readiness for professional activity unevenly. The behavioural and reactive component can be measured most adequately, and the emotional and volitional component more or less adequately. The degree of representation of methods for determining the peculiarities of the value-evaluation component is insufficient. The possibility of measuring the intellectual-cognitive and moral-ethical components is extremely low and as such does not reflect real needs.
Peningkatan Hasil Belajar IPS Dengan Penerapan Model Student Facilitator And Explaining Pada Kelas IV SDN 004 Bangkinang

This research was based on the low social studies learning outcomes of class IV SDN 004 Bangkinang, therefore the researchers provided a solution in the form of applying the Student Facilitator and Explaining learning model to improve student learning outcomes Recognizing the Development of Production, Communication and Transportation Technologies. The formulation of the problem in this research is how to apply the Student Facilitator and Explaining model to improve social studies learning outcomes in the material Understanding the Development of Production, Communication and Transportation Technology in class IV students at SDN 004 Bangkinang. This research was conducted in class IV SDN 004 Bangkinang. This research was conducted in two cycles and each cycle held two meetings. The subjects of this study were 16 grade IV students at SDN 004 Bangkinang, with 10 male students and 6 female students. Data collection techniques used in this study are observation, documentation, and testing techniques. Based on the results of the study it can be concluded that in cycle I it was still quite sufficient with an average of 75.93, then out of 16 students only 12 students or 75% achieved completeness individually. Student learning outcomes in cycle II were relatively good with an average of 86.87 and 15 students completed or 93.75% who achieved completeness individually. Thus it can be concluded that by applying the Student Facilitator and Explaining learning model it can improve learning outcomes Recognizing the Development of Production, Communication and Transportation Technology in class IV students at SDN 004 Bangkinang.&#x0D; &#x0D;
Managing Identity and Access Management (IAM) in Amazon Web Services (AWS)

Identity and Access Management (IAM) plays a pivotal role within Amazon Web Services (AWS) by governing the utilization of cloud resources and enhancing the overall security of the AWS ecosystem. IAM allows AWS users to effectively manage resource access while ensuring a robust security framework. This exploration delves into the fundamental concepts that underpin IAM, shedding light on authentication and authorization processes, best practices, practical implementation scenarios, and the convergence of IAM and security, and provides a forward-looking perspective into emerging trends in the field. IAM's significance lies in its ability to control access for individual users and groups, roles, and policies, ensuring the principle of least privilege and minimizing security risks. Multi-factor authentication (MFA) is a key facet of IAM within AWS, offering an extra layer of security and identity verification. This enables organizations to fortify access control measures, safeguarding their AWS resources from potential threats. In addition to these foundational concepts, this exploration delves into practical implementations, elucidating how IAM can be leveraged to meet realworld security and compliance requirements. IAM's robust features enable users to define and manage access permissions with precision, catering to the specific needs of their organizations. Furthermore, this abstract introduces the IAM Query API, which provides a means to interact directly with AWS services. The IAM Query API supports GET and POST methods through APIs, offering developers and administrators a more streamlined approach to managing access to AWS resources. IAM is a linchpin in AWS security, ensuring that access to cloud resources is fine-tuned, well-protected, and compliant with best practices. The continued evolution of IAM, including integrating emerging technologies and security measures, promises to further enhance the security posture of AWS users and the cloud computing ecosystem.
Peningkatan Hasil Belajar IPA Dengan Penerapan Model Problem Based Instruction Siswa Kelas IV SDN 004 Bangkinang Kota

This researd is based on the results of student on science subject grade IV SDN 004 Bangkinang City. One of the solution to solve this problem is to apply Problem Based Instruction model. The purpose of this researd is to describe the Improving of Science learning subject on topic environment changes by applying Problem Based Instruction Model at 4 grade students of SDN 004 Bangkinang city. The method of this research is Classroom Action Research (CAR) implemented in two cycles and each cycle held two meetings. Each cycle consists of two meetings and four phases, are planning, implementating, observating, reflecting, and schedule of this research begun from April until May 2017. The subjects thery are of this researd is student grade 4 of SDN 004 Bangkinang city. which 16 students, the are 10 male students, and 6 female students. of colection the techniques of used in this researd are observation, documentation, and test. Based on the results of learning is can be concluded that the first cycle is still quite average with an average of 74, then from 16 students only 12 students or 75% who achieve mastery individually. The result of Student learning in cycle II is good with an average of 86.60, and 14 students complete or 87.5% who achieve mastery individually. Thus it can be concluded that with the applications of Problem Based Instruction Model can improve the results of learning environmental changes at 4 grade students SDN 004 Bangkinang City
Pelatihan Penyampaian Kata Sambutan Bagi Pengajian Remaja Nurussalam Aek Badak

The training for delivering the speech text was carried out because self-confidence among PRN youth still needed to be motivated. The PKM method this time offers training implementation that starts with delivering material and practicing with practice. Manuscripts that have been written by each participant are given a section with a slash (/) as a pause marker. This activity is a continuation of the speech writing training which was carried out on the same object. The expected result is that the skills of PRN youth in honing their public speaking skills can be further improved. In this way, PRN youth can take more part in their environment in various social events.
DNEF: A New Ensemble Framework Based on Deep Network Structure

Deep neural networks have achieved tremendous success in various fields, and the structure of these networks is a key factor in their success. In this paper, we focus on the research of ensemble learning based on deep network structure and propose a new deep network ensemble framework (DNEF). Unlike other ensemble learning models, DNEF is an ensemble learning architecture of network structures, with serial iteration between the hidden layers, while base classifiers are trained in parallel within these hidden layers. Specifically, DNEF uses randomly sampled data as input and implements serial iteration based on the weighting strategy between hidden layers. In the hidden layers, each node represents a base classifier, and multiple nodes generate training data for the next hidden layer according to the transfer strategy. The DNEF operates based on two strategies: (1) The weighting strategy calculates the training instance weights of the nodes according to their weaknesses in the previous layer. (2) The transfer strategy adaptively selects each node’s instances with weights as transfer instances and transfer weights, which are combined with the training data of nodes as input for the next hidden layer. These two strategies improve the accuracy and generalization of DNEF. This research integrates the ensemble of all nodes as the final output of DNEF. The experimental results reveal that the DNEF framework surpasses the traditional ensemble models and functions with high accuracy and innovative deep ensemble methods.
Compliance Is a Must: The FBXperts View

In view of these descriptions, one might think that all those companies are lucky whose CFOs have also been IT managers at some point in their careers—but this is not often the case in practice. And even if they had been: Even that is no insurance against cyber risks. And then there are all the other dangers that make the topic of compliance and co. so sensitive. The risks are often also of a personal nature, and obviously liability issues are involved in many cases. The attitude of our major family companies is clear, as revealed by our interviews:
Web3 Security Analytics

This chapter offers a comprehensive overview of on-chain analytics and monitoring in Web3, discussing both preventive and reactive approaches to security and risk management. It explains key concepts, techniques, and principles of on-chain analysis, emphasizing the importance of balancing proactive and responsive strategies in a decentralized digital economy. The chapter covers the evolution and future prospects of preventive on-chain analysis, highlighting the growing reliance on machine learning, AI-driven tools, and the need for enhanced cross-chain and privacy-preserving capabilities. It also discusses reactive on-chain analysis, stressing the value of real-time monitoring, manual expert analysis, and the potential for automation and integration with smart contract operational services. Additionally, the chapter delves into various tools and platforms for on-chain analysis, discussing their advantages, limitations, and implications for security and user experience. It concludes with a forward-looking discussion on the future of on-chain analysis, envisioning greater integration, innovation, and collaboration across preventive and reactive strategies, while addressing cross-chain, interoperability, and privacy concerns in the Web3 ecosystem. Overall, this chapter serves as a valuable resource for understanding on-chain analytics and monitoring in Web3 and their contribution to the security, resilience, and success of the decentralized digital economy.
Blind Recognition Method for Non-Cooperative Communication Signals Based on Aerial Computing

Aerial computing is one of the highlights of 6 G space-air-ground integrated networks, with real-time monitoring and analysis capabilities to support non-cooperative communications. However, existing non-cooperative communication signal blind recognition methods separate the recognition of encoding methods and modulation types, leading to the waste of resources. This article draws on aerial computing, combines aerial computing and deep learning, and proposes a blind recognition method of non-cooperative communication signals based on aerial computing. This method enables simultaneous identification of the encoding method and modulation types of different communication signals, effectively conserving computing and communication resources. Finally, simulation experiments are conducted under various conditions, demonstrating the superior recognition accuracy of the proposed method.
Towards Intelligent Aviation: The Integration of Voice Assistants in Autonomous Aircraft

This paper explores the integration of a virtual assistant into an autonomous aircraft, focusing on the utilization of cutting-edge technologies for automatic speech recognition, speech synthesis, and natural language processing. By leveraging the power of Edge AI, particularly NVIDIA Jetson devices, we demonstrate how this amalgamation of technologies creates a lightweight, mobile, and efficient voice assistant system. We introduce a novel approach to enhance the operational capabilities of autonomous aircraft, facilitating human-machine interaction and enhancing overall user experience. This research paves the way for the application of edge-based voice assistants in autonomous vehicles, offering a glimpse into the future of intelligent and responsive in-flight systems.
Portable Cloud-Based Data Storage Security Using Dual Encryption

Secure data transfer is a must for all cloud-based structures. Cloud infrastructure is used by many networks, including those for e-commerce, online banking, and even software programs, to move enormous amounts of important data every day. This paper primarily addresses risk factors, which are security concerns encountered when managing cloud data. This research focuses on a hybrid encryption solution for cloud privacy and security. Elliptic Curve Cryptosystem (ECC) and Advanced Encryption Standard (AES) are the two best asymmetric encryption methods and symmetric encryption technology, respectively. The AES-ECC hybrid cryptosystem combines the advantages of the AES algorithm for faster data encryption with the ECC method for symmetrical session key exchange. The proposed solution minimizes the delay factor and is computationally efficient, robust, and secure
Combining Modern Technology and Real-Time Invoice Reporting to Combat VAT Fraud: No Revolution, but a Technological Evolution

An invoice reporting system based on blockchain technology can offer confidentiality, 100% VAT fraud detection and advantages for businesses. In order to fully understand the benefits that a blockchain-based invoice reporting system can bring to VAT, in this article the author gives an example of how blockchain technology can actually be used to fight VAT fraud, without making things overly complicated. The author also explains that implementation would not be a revolution of the VAT system, but only a technological evolution.
Manajemen Strategis Sistem Informasi Menggunakan Metode The Open Group Architecture Framework (TOGAF) (Studi Kasus: SMA Galatia Bekasi)

Information systems in this era of globalization have a role in carrying out every activity in all fields. The use of computer technology and information systems is very helpful for humans in all jobs, especially in light and difficult jobs. Information systems strategy is a necessity that can help business organizations achieve the company's business goals. The Open Group Architecture Framework (TOGAF) is an architectural framework that provides methods and tools to assist the acceptance, production, use, and maintenance of Enterprise Architecture. Galatia High School located in Harapan Indah still uses a manual system to carry out their activities. Therefore, Strategic Management of Information Systems is needed to facilitate their activities and improve the quality of their services. This research was conducted by conducting direct observations and interviews with the Principal, Deputy Principal, and Administration. The interview results obtained were analyzed using the TOGAF technique. The author also uses literature studies from books, journals, and previous research. This research will produce an information strategy management system to increase the competitive value of Galatian High School and assist Galatian High School in realizing their vision.
Model for Determining Follow-up Actions in Slum Areas in North Sumatra: Case Study in Tebing Tinggi City

Even in various cities, inadequately habitable residential areas tend to become slums and no longer meet the standards of a healthy residential environment. This study utilizes descriptive analysis and multiple linear regression analysis with a total of 100 respondents. The Slum Environment Follow-up Determination Model shows the results of the settlement conditions in Tebing Tinggi City, where many people live in unsuitable places, with damaged or inadequate building structures, high housing density, and wooden buildings. As a result, they are vulnerable to fire hazards. Additionally, there is a lack of clean water services, drainage facilities, household waste disposal, waste management, and poor environmental road quality (many roads lack upper pavement or are dirt roads), as well as inadequate street lighting. The low levels of education and income indicate a low socioeconomic status in the slum areas of Tebing Tinggi City. Factors such as Building Density Level (BDL), Environmental Drainage, income, and education collectively significantly influence people's decisions to live in slum environments. However, factors such as Building Density Level (BDL), Environmental Drainage, income, and education partially influence people's decisions to live in slum environments. The pattern of community participation in tackling slum areas remains the same, with an average of 57% not participating in decision-making, implementation, achievement, and program result evaluation.
An Efficient Sentiment Classification Method with the Help of Neighbors and a Hybrid of RNN Models

Some texts that are challenging to recognize on their own may become more understandable in a neighborhood of related texts with similar contexts. Motivated by this intuition, a novel deep text sentiment classification (DTSC) model is proposed to improve the model’s performance by incorporating the neighborhood of related texts. Our framework uses a nonparametric approach to construct neighborhoods of related texts based on Jaccard similarities. Then, a new deep recurrent neural network architecture is proposed, comprising two distinct modules: bidirectional long short-term memory (Bi-LSTM) and gated recurrent unit (GRU). The proposed model aims to effectively capture informative features from the input text and its neighbors. The result of each module is processed through the maximum operation, which selects the most pertinent data. Finally, the extracted features are concatenated and subjected to classification to achieve accurate sentiment prediction. Previous studies have commonly employed a parametric approach to represent textual metadata. However, our approach utilizes a nonparametric approach, enabling our model to perform strongly even when the text vocabulary varies between training and testing. The proposed DTSC model has been evaluated on five real-world sentiment datasets, achieving 99.60% accuracy on the Binary_Getty (BG) dataset, 98.32% accuracy on the Binary_iStock (BIS) dataset, 96.13% accuracy on Twitter, 82.19% accuracy on the multi-view sentiment analysis (MVSA) dataset, and 87.60% accuracy on the IMDB dataset. These findings demonstrate that the proposed model outperforms established baseline techniques in terms of model evaluation criteria for text sentiment classification.
Analysis of Website Quality Using The Webqual 4.0 Method at SMA Negeri 12 Tangerang

Currently, information technology has become a determining factor for success in all aspects. This web media is a suggestion that can be used in schools where websites are used to convey information to students and the general public. SMA Negeri 12 Tangerang Regency is one of the educational institutions that wants to ensure that their website provides a satisfying experience to its visitors. By conducting a webqual 4.0 analysis, SMA Negeri 12 Tangerang Regency can gain deeper insight into the strengths and weaknesses of the website. This research aims to measure the quality of the website of SMA Negeri 12 Tangerang Regency based on the webqual 4.0 dimension variables, namely quality of use, quality of information, and quality of interaction. The method used in this research uses a quantitative method with stages of identifying webqual 4.0 variables, sample selection, data collection, data analysis, data interpretation, and validation. With the results of this research, you can carry out reliability testing, hypothesis testing, t test and f test. So the results can be concluded that during the t test the variables X1, variable Y.
Manajemen Pendidikan Literasi Finansial Anak Usia Dini

Management of financial literacy education is an important aspect in children's development from an early age. The ability to manage money and understand financial concepts are crucial skills for everyday life. Therefore, management of financial literacy education for early childhood is a relevant topic and needs serious attention. This research aims to investigate effective management methods and strategies in providing financial literacy education to young children. Through a qualitative approach, this research analyzes various resources that can be used in the context of financial literacy education for early childhood. These resources include storybooks, educational games, practical activities, as well as the role of teachers and parents in the educational process.