Reviewerly/exHarmony huggingface dataset:
Blockchain-Based Identity Authentication Oriented to Multi-Cluster UAV Networking

Unmanned Aerial Vehicle (UAV) networking is increasingly used in field environments such as power inspection, agricultural plant protection, and emergency rescue. To guarantee UAV networking security, UAV identity authentication attracts wide attention, especially in the field environment without perfect infrastructure. Some blockchain-based UAV identity authentication solutions are proposed to establish decentralized and trusted authentication systems without relying on infrastructure. However, these solutions do not support disconnected UAV reconnection or even disband a cluster directly after its head UAV disconnection, which compromises cluster robustness and task result integrity. In this paper, we propose a blockchain based identity authentication solution oriented to multi-cluster UAV networking with a UAV disconnection mechanism and a task result backup mechanism. Specifically, we build a blockchain maintained by head UAVs of all clusters, managing identity information to guarantee the security of decentralized identity management. The UAV disconnection mechanism permits a verified distributed UAV reconnection to ensure the robustness of the UAV cluster, and on this basis, the task result backup mechanism ensures the integrity of the task results stored in a cluster even any UAV disconnection. Finally, extensive experimental results prove the superiority of our solutions in terms of robustness, integrity, delay, and energy consumption.
A cross-chain identity authentication scheme based on DID

Blockchain has gradually played a very important role in many fields. Cross-chain technology is a vital technical means to realize interconnection and value transfer between blockchains. In the field of cross-chain identity authentication, there are problems that the identities of each chain are not unified and the identities are not in the hands of users themselves. In this paper, we investigate this challenge and contribute by presenting a cross-chain identity authentication solution that incorporates Decentralized Identity (DID), smart contract, and Identity Public Key (IPK) security algorithm. We propose a secure cross-chain model architecture based on the IPK algorithm, which uses a relay chain to securely access the blockchain and conduct cross-chain identity authentication. Specifically, in our solution, DID is used as the global identifier of the entire cross-chain network of the blockchain, and cross-chain identity registration and authentication are performed through the relay chain. In order to ensure the anonymity and security of information, we use the key exchange strategy to encrypt cross-chain information. The model we proposed is the first concrete scheme proposed in the field of DID-based cross-chain identity authentication. We implemented a prototype using Fabric and Fisco, and evaluated the performance of the system, and the overall performance in throughput and latency was relatively excellent.
Mobile Robot Shaping Filter Vibration Model for Attached Object

A mathematical methodology to assess the effects of vibrations on a mobile robot's video system components is being developed and implemented. The robot is a mobile platform for placing specialized equipment for various uses. The vibrations of structural components of multi-bearing wheeled vehicles were examined using mathematical models and empirical data. This study supports the use of a stochastic mathematical model to describe mobile robot vibrations. Under diverse robot motion conditions, the vibration model is a correlation function or spectral density of a stochastic process. To replicate a random vibration process with specified features, shaping filter differential equations are supplied. The vibration process, probabilistic moments, and differential equations are given. The probabilistic moment equations and formula were used to analyze vibration amplitudes exceeding a threshold. Random process emissions indicate how well the mobile platform equipment retains its core properties. An extensive mathematical model was analyzed to estimate stochastic vibration emission intensity. The Probabilistic vibration method and emission intensity properties are determined. Theoretical discoveries allow the evaluation of mobile video system components and the determination of fundamental tolerances. The mathematical framework for assessing vibrations was proven by computer simulation.
Indistinguishability Obfuscation: A Key Enabler for Lightweight Provable Data Possession in Cloud Storage

Storage external outsourcing, with its emphasis on data from outside distribution, has been growing in popularity in recent years. A number of intriguing issues regarding security and privacy are raised by this development. The lack of responsibility from external storage of information suppliers is a major worry. In order to help consumers verify the availability and integrity of their outsourcing data on insecure storage devices, this paper provides a comprehensive analysis of two schemas/algorithms. The schemas that have been examined are Provable-Data-Possession (PDP) and Proof-of-Retrievability (POR, which stand for indications of accessibility. In order to reassure customers that their data is safe on untrusted data storages, both protocols use cryptography. Lightweight Cipher Policy Assisted Cloud Data Handler (LCPCDH) is a new model for managing highly secure, lightweight cloud storage. It is cross-validated with the traditional RSA based Cloud Storage Scheme (RSACSS) to assess its performance. A hybrid of RSA with a standard cloud storage solution is the only tried-and-true approach here. According to this new model, the public verifier and the cloud provider neither have access to the actual signatures that authenticate cloud data. However, there are still reliable methods for checking the legitimacy of cloud-based data. For certain unique cases, such as outsourcing electronic checks and contracts, it might be helpful. In order to safeguard the confidentiality of the authentication system and enable blockless confirmation, we have developed a new authenticator named LCPCDH. In this paper, we build the first remote information ownership verification system for cloud storage using privacy-preserving authenticators, based on LCPCDH. Our suggested approach is tested through theoretical analysis and simulated tests to ensure its security and efficiency. The outcomes validate the safety and efficacy of our suggested paradigm.
Multilayer Perceptron Models for Classification of Cervical Precancerous Cells Based on FE-SEM/EDX Features

Field emission scanning electron microscopy (FE-SEM) has been widely applied in research and engineering. Field emission scanning electron microscopy and energy-dispersive X-ray (FE-SEM/EDX) can capture high-resolution cervical cell shape and elemental composition images. This paper aims to utilize the high peaks of the elemental composition based on FE-SEM images and EDX spectra. The features of the cervical cells were extracted the ratio of high peaks. The classification employed neural network Levenberg Marquardt backpropagation and scaled conjugate gradient backpropagation models. The accuracy results reached 84.6%. Levenberg-Marquardt backpropagation classifier required 29 epochs to achieve the best performance.
A Multi-Core Verification Method of Vector Instructions Based on Spike

Verifying the instruction execution against a golden execution model following the ISA is becoming a common practice to verify processors. This method plays an important role in the single-core verification scenario. However, for the correctness monitoring of multi-core processors, the uncertainty caused by shared storage makes the above method unable to meet the requirements better. This paper provides a multi-core function verification scheme of vector instructions based on RISC-V architecture, which monitors the instruction execution time of DUT and triggers the reference model in time through Test Bench. This scheme uses Spike, the instruction set standard implementation model specified by RISC-V Foundation, as the reference model of verification environment. It adds a DPI (Direct Programming Interface) interface for the simulation environment to call, modifies the execution mechanism of vector instructions in Spike's existing model, and then triggers the synchronous execution of Spike with the time of the instruction monitored from each core in the DUT (design under test), and finally compares the execution results of the DUT and Spike. From the top level, although there is no adjudication mechanism for the order of multi-core access data in Spike, the time of data acquisition or update of each core is exactly the same as that in the DUT. So that the multi-core comparison verification of vector instructions can be completed in the simulation stage, and more bugs such as vector instructions and multi-core consistency can be found earlier.
Pupils’ and Parents’ Opinions on Schools with Italian as the Language of Instruction

Abstract The model of education in the ethnically mixed area of Slovene Istria is designed to ensure schooling for members of the Italian national community and their children in their own language, i.e., Italian. Although also attended by pupils of other nationalities, primary schools with Italian as the language of instruction are key for the preservation of Italian culture and language. The authors present selected research findings that shed light on the opinions of pupils and their parents on whether schools with Italian as the language of instruction develop pupils’ communicative competence in both Italian and Slovene, and whether the existing model of education creates conditions that promote the pupils’ awareness of the linguistic and cultural diversity of their environment. The results of the research reveal that the majority of the respondents consider competence in several languages an added value and that the model of education is adequate and good.
Blockchain-Based Architecture for Improving Maize Supply Chain Performance: Designing an Aggregator Platform

Blockchain technology (BcT) presents opportunities for improving transparency and traceability in an agriculture supply chain. The BcT enables the combination of the immutable decentralized data ledger with smart contracts to unify different actors in an agriculture supply chain into a digital platform. The latter is an executable program that enables automatic running if certain conditions are met. It brings BcT implementation in improving supply chain performance in minimizing non-added value processes, especially from the farmer's perspective. An agriculture supply chain comprises several actors with various digital infrastructures and standards. The information regarding products and services is also scattered, and individual actors' various infrastructure facilities silo the access. Thus, this study carries a maize supply chain (MSC) case study. This manuscript presents the development of a conceptual architecture, using the BcT and smart contract feature, for an MSC's aggregator platform.
Bi-Orthogonal Projection Learning for Dimensionality Reduction

This paper proposes a novel bi-orthogonal projection learning (BOPL) for dimensionality reduction (DR) methods, which further extends the existing DR to a more flexible, robust, and sparse embedding framework. Unlike conventional methods that use only one kind of projection for learning in DR, the proposed BOPL introduces two kinds of projection, which are orthogonal and provides the true projection the freedom for more accurate data transformation in subspace learning. Inspired by the observation that the two projections share many similar data structures, the projections are expected to preserve the similarity structure of data by using two different reconstruction ways. The proposed method can also handle data corrupted by noises since a sparse item is employed to compensate for the noises during DR. Several novel unsupervised DR methods (i.e., BOPL_PCA, BOPL_NPE, and BOPL_LPP) are derived from the proposed framework. The results of experiments on the natural and synthetic data sets demonstrate that the proposed methods outperform the existing well-established DR methods.
Practical Construction of Professional Core Elements for Higher Vocational Students

Education practice is a scientific way to realize the core professional quality of vocational college students characterized by professional attributes and era implication; Sort out and disclose the connotation and representation dimension of professional core quality of vocational students in the new era; Build the "four platforms+four modules" practical teaching and education model, track and evaluate the effect through the whole process based on the data platform, and provide reference and inspiration for the cultivation practice of vocational students' professional core literacy.
Research competence as one of the components of the system of key competencies

The main problem is that the study of research competence does not lose its relevance nowadays, but on the contrary, requires special attention of teachers of secondary schools. The main subject of the study is teaching students research skills to the most effective methods of mastering key competencies. Objective: the role of research competence in the learning process of students. Methods: analysis, synthesis and comparative analysis are the main research methods. Results and their significance: as a result, the concept of "research competence" was studied. Various views on this idea are considered. In the last ten years, the program of socio-economic development of Kazakhstan has determined the main directions of the development of the system of education of students. The research has both theoretical and practical significance, since its results can be used in the development of programs and methods for the development of research competence in biology lessons.
Relationships among Quality Parameters of Tests

Background: Tests involve distinct test parameters like reliability, validity, difficulty value, discriminating value, responsiveness, etc. To assess quality of test, relationships among the test parameters are needed. Method: The paper describes methods of finding discriminating value of test/scale (
Detecting Objects Using Haar Cascade for Human Counting Implemented in OpenMV

Sight is a fundamental sense for humans, and individuals with visual impairments often rely on assistance from others or tools that promote independence in performing various tasks. One crucial aspect of aiding visually impaired individuals involves the detection and counting of objects. This paper aims to develop a simulation tool designed to assist visually impaired individuals in detecting and counting human objects. The tool's implementation necessitates a synergy of both hardware and software components, with OpenMV serving as a central hardware device in this study. The research software was developed using the Haar Cascade Classifier algorithm. The research process commences with the acquisition of image data through the OpenMV camera. Subsequently, the image data undergoes several stages of processing, including the utilization of the Haar Cascade classifier method within the OpenMV framework. The resulting output consists of bounding boxes delineating the detection areas and the tally of identified human objects. The results of human object detection and counting using OpenMV exhibit an accuracy rate of 71%. Moreover, when applied to video footage, the OpenMV system yields a correct detection rate of 73% for counting human objects. In summary, this study presents a valuable tool that aids visually impaired individuals in the detection and counting of human objects, achieving commendable accuracy rates through the implementation of OpenMV and the Haar Cascade Classifier algorithm.
Perceived Value of Digital Literacy Skills: Case of Edcrunch Trainees

This article explores digital literacy within the context of Spiritual Renaissance and the "Digital Kazakhstan" education initiatives, focusing on the experiences of participants in the EdCrunch Academy Training program. Our study, encompassing the initial cohort of 41 trainees in Kazakhstan, utilizes a mixed-method approach. Qualitative data was gathered through Zoom interviews, while quantitative data was collected using a Google Forms rating scale. Participants enrolled in the EdCrunch program primarily sought both professional development and learning innovative teaching methods, including the integration of educational apps into their lessons. The respondents’ ratings on the "Transferability of pedagogical skills to the classroom" and "Content related to educational technology/apps" yielded satisfaction levels with respective logits of -0.37 and -0.61. However, the platform's structure and content organization received lower ratings, with logits of 0.63 and 0.36, indicating dissatisfaction. Furthermore, trainees continue to apply pedagogical skills gained through EdCrunch, particularly utilizing educational technology tools such as Wordwall, Kahoot, and Quizlet to create interactive tasks, which fosters their students’ engagement and motivation during classes.
Pengaruh Minat Belajar dan Kualitas Pertemanan Sebaya Terhadap Konsep diri Remaja SMA/SMK Sederajat di Kecamatan Pondok Kelapa Kabupaten Bengkulu Tengah

This article aims to examine how much influence interest in learning and the quality of peer friendship on self-concept in high school / vocational students of the same level in Pondok Kelapa District, Central Bengkulu Regency. The population in this study was adolescents in SMA/SMK sub-district of Pondok Kelapa, Central Bengkulu. This research uses a quantitative approach with a descriptive type of research. The sample in this study was 130 high school / vocational students as respondents. The type of data collection used in this study is a Likert scale questionnaire or using questionnaire survey techniques by distributing targets to respondents, as many as 30 statements consisting of 10 statements from self-concept indicators, 10 statements from learning minar indicators and 10 statements from peer friendship quality indicators. The analysis techniques used are Data Normality Test, Reality Test, Correlations Test, Descriptive Statistics Test, Model Summary Test, and Anova Test thus testing is carried out testing is carried out using. Based on the results of research and discussion, it can be concluded that the interest in learning and the quality of peer friendship affect the self-concept of high school / vocational students in Pondok Kelapa district, Central Bengkulu district. The influence of learning interest and friendship quality on self-concept reached 16.7%, while the remaining 83.3% was influenced by other variables.
Exploring the Connection between Organizational Justice and Personnel Commitment among Teachers at the Postgraduate Level

This study investigates the connection between organizational justice and personnel commitment among postgraduate-level teachers. The study adopted a correlational research design. A random sample of 255 teachers was selected from eleven universities in Lahore, and data was gathered using a structured questionnaire comprising two sections. Data analysis involved statistical calculations, including means, percentages, and correlation analysis, with SPSS version 18.0 utilized for this purpose. The findings of the study revealed that organizational justice significantly influenced teachers' personnel commitment. Distributive justice emerged as the most significant predictor of personnel commitment, while procedural and interactional justice moderately predicted teachers' commitment. The study recommends that management should prioritize fairness in reward distribution, involve employees in decision-making processes, and maintain a respectful and dignified approach when communicating decision outcomes to staff. Consistency in rule application, accuracy in information usage, and the prevention of bias in employee-related matters are also advised for effective management.
Aspect-Oriented Programming (AOP)

Aspect-Oriented Programming (AOP) is a paradigm that introduces an effective and modern technique to software design and improvement. In contrast to standard Object-Oriented Programming (OOP), AOP makes a speciality of modularizing move-cutting issues, inclusive of logging, protection, and errors managing, that regularly traverse multiple modules in a machine. This summary explores the key ideas, mechanisms, and programs of AOP, dropping light on its transformative effect on software architecture. At the middle of AOP lies the idea of elements, which encapsulate go-slicing concerns and allow their modularization. AOP enhances OOP via permitting builders to explicit worries that cut throughout the natural barriers of instructions, offering a greater cohesive and maintainable manner to control gadget-extensive functionalities. The abstract delves into the mechanisms of AOP, which includes pointcuts, advice, and weaving, which collectively empower builders to separate move-cutting worries from the main commercial enterprise good judgment. The flexibility added by way of AOP facilitates the advent of cleanser, extra modular code, as builders can attention on the core worries inside man or woman modules without being encumbered with the aid of pervasive cross-reducing functionalities. The summary also explores the idea of weaving, a technique through which elements are integrated into the code, allowing the seamless software of move-reducing issues without altering the prevailing codebase. Moreover, this summary addresses the numerous programs of AOP across numerous domain names. From improving code maintainability and selling reusability to improving system scalability and facilitating the implementation of safety regulations, AOP emerges as a versatile paradigm with a wide variety of programs. The modularization of pass-reducing worries simplifies the development technique, making it easier to recognize, take a look at, and evolve software program systems over time. In conclusion, AOP stands as a paradigmatic shift in software improvement, supplying a unique angle on handling pass-cutting issues. By supplying an extra streamlined and maintainable technique to handling system-huge functionalities, AOP represents a valuable addition to the software program engineer's toolkit, fostering cleaner, more modular, and adaptable codebases throughout various utility domain names.
Myaka : Aplikasi Pengelolaan Arsip Digital Sekolah

This study aims to describe filing management using the Myaka application. The method used in this study is to use a qualitative approach with descriptive methods. Data was collected through interviews, observation, and documentation studies. The results of this study indicate that the development of information and communication technology (ICT) has now spread to the world of education, namely with the management of digital archives. The Myaka application is school software as digital archive data used by schools to manage grades, attendance, report cards, question analysis, student data, and teacher data collected in one system. This study found that Myaka, as a digital archive storage application, has fulfilled the requirements in the archive life cycle starting from the creation, storage, distribution, user, maintenance, and disposition.