Reviewerly/exHarmony huggingface dataset:
Factors and Models Influencing Value Co-Creation in the Supply Chain of Collection Resources for Library Distribution Providers Under Data Ecology

Under the data ecology, the advancement of relevant technology and the utilization of relevant resources have provided more efficient technical services for various industries. However, with the proliferation of data resources, problems such as information pollution and data redundancy have arisen in the process of supply chain services for collection resources. For solving such problems and enhancing the collection resource supply efficiency of librarians, the study uses data mining technology combined with improved K-Means clustering algorithm to design a value co-creation model of library collection resource supply chain for librarians under data ecology. The outcomes indicate that the shortest running time of traditional K-Means algorithm is 40ms and the longest running time is 115ms in Wine dataset, and the running time of improved K-Means algorithm is stable at 59ms; the shortest running time of traditional K-Means algorithm is 26 ms and the longest running time is 58ms in Iris dataset, and the running time of improved K-Means algorithm is stable at 53 ms. The clustering accuracy of the improved K-Means algorithm in the Wine data set is 98.2%, which is 0.3% exceeding the traditional K-Means algorithm, which is 97.9%; the clustering accuracy in the Iris data set is 100%, which is 2.4% exceeding the traditional K-Means algorithm, which is 97.6%. In summary, it can be seen that the studied data ecology has a good application of the factors and models influencing the value co-creation of the supply chain of library resources for library dispensers.
Cryptographic applications of a new hyperchaotic system with a hidden attractor

This work puts forth a new 4D hyperchaotic 2-scroll dynamics with a hidden attractor. The proposed nonlinear system has three quadratic terms and it is established that there is no fixed point for the proposed dynamics for all values of the system constants. Bifurcation analysis for the proposed system is investigated in detail. Next, we invoke Multisim for the development of an electronic circuit for the proposed hyperchaotic dynamics. Finally, we present some cryptographic applications of the proposed hyperchaotic dynamics. A new algorithm for the construction of substitution boxes (S-boxes) using the presented hyperchaotic system is proposed, in which the performance of the generated S-box demonstrates its efficiency and reliability for designing modern block-cipher cryptosystems. The proposed hyperchaotic system is utilised for generating Pseudo-Random Number Generators (PRNGs), in which the results of NIST SP 800-22 tests demonstrate the randomness characteristics of the generated PRNG sequences.
THE ESTABLISHMENT OF PERSONNEL MANAGEMENT IN THE 20s OF THE 20th CENTURY AS A NECESSARY CONDITION FOR THE DEVELOPMENT OF THE PIONEER MOVEMENT

The purpose of the article is to study the problem of personnel management in the pioneer organization in the 20s of the 20th century. Historical research methods are used to analyze the the-ory and practice of pioneer work. Such sources as resolutions of congresses, plenums of the Central Committee of the RLKSM on the selection and training of pioneer counselors are studied. Special attention is paid to the content of training programs, problems that arose during their implementation. The article also raises the issues of the organization of Pio-neer counselors’ work. As a result, the author comes to the conclusion that the pioneer movement contributed to the development of the country as a result of competent work with pioneers. The author notes that their selection, training and placement were the key to their improvement and administrative growth. In the future, they joined the Komsomol and parties, became a patriotic part of the country's population. Besides, new materials are introduced into scientific circulation, which make it possible to draw historical analogies with modernity, analyze trends, and show a certain relationship between the past and the present.
Application research of improved Apriori algorithm in teaching evaluation of mobile platform for elderly education

How to improve the teaching level of elderly education is of great practical significance to the current 'elderly' countries and regions. In this study, we improve the Apriori algorithm to analyse the teaching evaluation data, and test the performance and apply the analysis. The results show that the minimum and maximum runtime of the traditional Apriori algorithm is 23 ms and 177 ms respectively, while the minimum and maximum runtime of the improved Apriori algorithm is 17 ms and 163 ms respectively, which indicates a better classification performance in data mining. The basic information of teachers was analysed to show the association of teachers' titles, education and age. Compared with other algorithms, the improved Apriori algorithm saves running time to a certain extent, has better accuracy and precision than other algorithms, and can achieve effective analysis of teaching evaluation data on the mobile platform for senior education.
The compound iterative algorithm for rational models based on the Coyote optimisation algorithm

This article proposes a Coyote Optimisation Compound Iterative Algorithm (CO-CIA) for rational models. Particularly, the parameters in the numerator and denominator of rational models make the derivative equation hard to solve. To deal with this problem, the Coyote Optimisation Algorithm (COA) is applied to estimate the parameters in the denominator. Compared with the Bias Compensation-based Least Squares (BCLS) algorithm and the Particle Swarm Optimisation Compound Iterative Algorithm (PSO-CIA), the proposed method has higher accuracy and faster convergence rates. Finally, a simulation example is utilised to verify the effectiveness of the proposed algorithm.
Evaluation

This chapter critically evaluates the previously outlined software architecture, which aims to redirect trust in cloud applications to the blockchain using the RAD methodology. The primary focus is on the architecture's effectiveness in reducing the inherent adoption risks of cloud applications. To assess this, the evaluation uses a scenario-based approach. This method is respected for its maturity and widespread acceptance in architecture evaluations. Each scenario illustrates different interactions between stakeholders and systems. Each scenario serves as a measure of the architecture's competence. Semi-structured interviews and the Mann-Whitney U-test are integral to this evaluation. They provide deeper insight and statistical validation of the architecture's capabilities. A multifaceted view from multiple stakeholder perspectives is obtained by examining the architecture's performance and behavior in these detailed scenarios. The ultimate goal is to conclusively address the central research question, RQ7, by unambiguously revealing the extent to which the developed software architecture can mitigate the risks associated with deploying cloud applications.
Security Implication of Mutual Police and Societal Corruption in Nairobi County, Kenya

This paper uses data collected for an MA Thesis on the security implication of the mutual police and societal corruption in Nairobi County, Kenya. The study was motivated by increased insecurity in Embakasi North constituency despite tight security in the area. This study attributed this to mutual police and societal corruption that this study sought to establish. This study was guided by the Erosion Theory (ET) of corruption explaining why so many potentially good people get drawn into the vice. The study used cross-sectional survey design and stratified random sampling techniques and enlisted, 196 respondents and 10 Key Informants (K. I’s). The main data collection methods were the questionnaires for the main respondents and interviews for K. I’s. The main data collection tools were the questionnaires and Key Informants schedules. Quantitative data will be analyzed with the aid of statistical package for social sciences (SPSS). This study unraveled both, Macro and Micro police contextual obstacles where the extent and implications of the state organs such as the legislature, executive, and justice sector institutions suggested corrupt political contexts, hence constraining policing function with criminological approaches to corruption. With reference to the second objective, the study revealed the main forms of police corruption in the area which included receiving bribes to; release suspects from lawful custody, assist suspects evade arrest, cover up criminal activities, reveal police operations; protection of illegal activities, evidence tampering &amp; theft and disclosure of privileged Information amongst others. These forms of corruption benefited organized criminal groups, which were said to be potentially risky to an extent of disabling both individuals and entire institutions, besides seeking state capture; in polity and economy. Finally, the study revealed a deeper relationship between police and society corruption based on determinant factors such as culture (p=0.01), systemic failure of governance(p=0.01), and failed economy (p=0.02). Deeper insight of police corruption seems to draw from a society wide cultural corruption paradigm. This study recommends that recommends an anti-corruption approach that goes beyond targeting “bad apples” and adopt a systems approach. Further, Political will from a benevolent dictator with presidential degrees on matters corruption will help crush this cancerous vice to the nib.
Readability Analyses of Integrated Science Textbooks for Junior High Schools in Ghana

This study investigated the readability levels of some integrated science textbooks approved for use in junior high schools (JHS) in Ghana. To assess the readability levels of the approved integrated science textbooks in order to ascertain their difficulty or ease, the researchers used the Flesch Readability Ease and Flesch-Kincaid Readability Formulas Cloze Test to determine the comprehension levels for a sample of students. A sample of 135 pupils, drawn from rural, peri-urban and urban JHS years 1 through 3 in the Ashanti region participated in the study. The outcome of the assessments revealed that the selected textbooks had a problematic level of comprehension for many of their intended readership except those who had additional resources for assistance. The study also revealed that these approved books employed long sentences and multi-syllabic words to deliver lessons and instructions, making them difficult for JHS pupils to understand.
Human-AI system co-creativity for building narrative worlds

This paper explores the human-AI system co-creativity for building narrative worlds (NWs) through active human-machine collaboration. It proposes a hypothesis of structuring a narrative world for the AI system, working on the gap between the main disciplines of Design Studies and Human-Computer Interaction (HCI). Through the lens of the creative collaboration between humans and AI, this paper finds the emerging field of Interactive Digital Narrative (IDN) that stands in the abovementioned gap. Creativity has long been considered unique to humans, but in this contribution, creativity is considered in collaboration with an AI entity. The AI system becomes a tool for designers, in this case, a collaboration tool, to find novel ideas to write stories, accelerating the storytelling process. This contribution proposes a method to explore the influences of AI systems on human creativity within the design process of creating stories. The study begins with a review of the literature on the meaning of creativity as perceived through the collaborative activity of human and AI systems. The topic of interest is related to the process of story construction, the phase of crafting narrativity, through which it is possible to find creative ideas for narrative world-building. The aim is to explore the AI system's computational creativity potential as a supporting tool for the designer in world-building.
Design of Mobile Learning for Mathematics Subjects on Building Volume Materials for Class V Students at SD Negeri 1 Jatikuwung, Karanganyar

Education plays a significant role in enriching people's lives and building a better future. Mathematics has universal characteristics and has an important role in various fields of science. Grade V students at SD Negeri 01 Jatikuwung, Karanganyar. There is still a lack of interest in learning mathematics in the material of geometric volumes. Mobile Learning can help increase students' interest in learning mathematics. In making this mobile learning using the MIT App Inventor software. The design of mobile learning uses the ADDIE research method (Analysis, Design, Development, Implementation and Evaluation). This mobile learning design was also tested using Black Box testing, from Black box testing how many functionalities of the 9 tests the results were "valid" and resulted in a comparison of 9/9 x 100% = 100%. The data collection method used a questionnaire with five question indicators that were tested on the principal and homeroom teacher of class V, and this test resulted in a score of 88%, with the "Very Good" criterion. can increase the learning interest of fifth grade students, as reflected in the student questionnaire score of 74% with the "Good" criteria
Lexical Cohesive Devices and English Writing Quality

This mixed-methods study investigated the use of lexical cohesive devices (LCD) for 56 Arab English as a Foreign Language (EFL) learners in the UAE. The quantitative descriptive approach was used to find out the frequency of LCD in learners’ essays, and the quantitative correlational approach was implemented to examine the association between LCD and the writing quality. However, the qualitative descriptive approach utilized semi-structured interviews of 4 EFL teachers and 15 EFL learners to identify the challenges that they encountered regarding using LCD in essay writing. The findings demonstrated that repetition and collocations were the most frequently used LCD, while meronyms and hyponyms were the least common in participants’ essays. There was also a moderate positive correlation between cohesive density and the writing quality. The difficulties reported by the participants in dealing with LCD included themes pertaining to awareness and instruction, de-contextualization of cohesive devices (CDs) and feedback and correction.
MultiStyle: Characterizing Multiplayer Cooperative Gameplay by Incorporating Distinct Player Playstyles in a Multi-Agent Planner

This paper presents MultiStyle, a multi-agent centralized heuristic search planner that incorporates distinct agent playstyles to generate solution plans where characters express individual preferences while cooperating to reach a goal. We include algorithmic details, an example domain, and multiple different solution plans generated with unique agent playstyle sets. We discuss our intent to incorporate this planner in a tool for game level designers to help them anticipate and understand how teams of players with distinct playstyles may play through their levels. Ultimately, MultiStyle generates solution plans with a novel and increased expressive range by attempting to satisfy sets of action and proposition preferences for each agent.
Improving fault localization via weighted execution graph and graph attention network

Abstract Software fault localization is commonly recognized as arduous and time consuming. Spectrum‐based fault localization (SBFL) has been widely used due to its lightness. However, the effectiveness of SBFL is limited since it only considers simple statistics on the coverage information, ignoring the tie problem that the spectrum matrixes of some statements are the same. Most existing deep learning‐based fault localization (DLFL) techniques convert the coverage information into a vector, which utilizes the spectrum in a simplified manner and still has limitations in practice. To solve the above problem, we propose an approach via the weighted execution graph and graph attention network (WEGAT). We use a graph structure to represent the coverage information between test cases and program elements. Then, we generate a weighted execution graph by applying the predicate execution sequence. Furthermore, we combine the weighted execution graph with the AST as an integrated graph, which is the input of the GAT for fault localization. We evaluate WEGAT in within‐project and cross‐project prediction scenarios on the Defects4J benchmark. Experimental results show that our approach outperforms traditional SBFL (Ochiai, DStar and Tarantula) and DLFL (TraPT, CNN‐FL, Grace, and AGFL) methods, effectively improving the accuracy of fault localization.
PERANCANGAN APLIKASI PEMESANAN DAN PERCETAKAN PADA PT SANGKAKALA INDAH MENGGUNAKAN METODE UCD (USER CENTRAL DESIGN) BERBASIS ANDROID

The development of technology today is very fast, without exception, both information and communication technology. Therefore, an efficient step is needed to anticipate it. Information and communication technology is now starting to enter various aspects of life, one of which is in the business world. This is because a lot of work is assisted by information technology which is able to minimize the level of errors even to the level of losses that will occur. PT Sangkakala Indah is a company engaged in the printing sector, namely serving the design of document notes, banners, banners and is currently facing problems in the field of ordering. The ordering system at PT Sangkakala Indah is still done conventionally. For example, in recording orders, making order invoices to taking orders and transaction reports, they still rely on recording on notes and the difficulty of communication between graphic designers and customers. This of course can cause loss or damage to the order data or sales transaction. \Digital printing is a printing method for producing printouts that are done using digital-based images or documents. With this method, documents or print applications can be processed quickly and easily. This digital printing is an innovation from its predecessor, offset printing, which is classified as wasteful of raw materials and production time. Digital printing has advantages such as producing sharp print and color applications, lower costs, being able to print in small quantities, and being able to streamline production timeUser centered design (UCD) is called human centered design.
THE METHOD OF PROJECTS AS A MEANS OF DEVELOPING SENIOR STUDENTS

The purpose of this article is to investigate the effectiveness of using the method of project-based learning in «Technology» classes as a means of developing senior students. The article examines the impact of the project-based method on the organization of developmental activities for high school students during classes. The method of projects is a means of comprehensive development of students. As a result, this creates conditions where knowledge ceases to be the goal of the educational process, and becomes a means of further self-development and self-education. The practical significance lies in substantiating the importance of using the project-based method as a means of comprehensive development of senior students during «Technology» classes.
Decoding the animated text-based captchas to verify their robustness against automated attacks

In order to protect the web against automated attacks, CAPTCHAs are most widely used mechanism on the internet. Numerous types of CAPTCHAs are introduced due to weaknesses in the earlier designs. Animated CAPTCHAs are one of the design alternatives. Instead of presenting the whole information at once, animated CAPTCHAs present information in various frames over the specific interval of time. As CATPCHAs are ubiquitously used to avoid the serious threats from bots therefore it is important to verify their effectiveness. In this research we have verified their robustness against machine learning attacks. It has been proved that adding the extra time dimension does not necessarily ensure protection against automated attacks. We have attacked the Hello CAPTCHA scheme, which is the most popular animated CAPTCHA scheme available on the internet. By applying novel image processing and machine learning techniques, these CAPTCHAs are decoded with high precision. A pre-trained CNN is used to recognize the extracted characters. In this research, 6 popular types of animated CAPTCHAs along with 41 sub types were successfully deciphered with an overall precision of up to 99.5 %.
Own experience of using holographic neuronavigation using an augmented reality helmet in neurosurgery

Objective: to optimize surgical access to intracranial lesions (tumors, arteriovenous malformations, cysts, etc.) by using a holographic neuronavigation system with augmented reality helmet. Materials and methods: The study included thirty-four patients who underwent cerebral neurosurgical interventions. Creation and clinical use of mixed reality neuronavigation (MRN) system holograms was possible in all cases, which allowed accurate localization of lesions. The additional time required for synchronizing the MRN system with the clinical environment was estimated, which decreased with the number of MRN system uses. Operators evaluated the effectiveness of the technology and in most cases provided positive evaluations after use. Results: A semi-automatic MRN recording system on HoloLens smart glasses has been developed and tested for accuracy and performance. 34 patients with intracranial lesions were prospectively included in the study. Three-dimensional holograms of lesions, markers, and surrounding anatomical landmarks based on multimodal imaging were generated for each patient and then imported into the MRN system in AR helmet. After point recording, holograms were projected onto the patient’s head and observed through the AR helmet during the planning and conducting of surgical interventions. Conclusions: In this small pilot study, the authors found that mixed reality neuronavigation system MRN can be applied in the workflow of a neurosurgical operating room and is a possible method of preoperative identification of lesion boundaries for surgical access planning. Future studies are needed to identify strategies to improve and optimize the accuracy of MRN system.
TOTPAuth: A Time-based One Time Password Authentication Proof-of-Concept against Metaverse User Identity Theft

As the metaverse evolves and prospers, identity theft is becoming a critical security concern. Traditional PIN-based authentication methods are vulnerable to physical attacks such as video recording or the use of pen and paper. To address this open research issue, researchers are exploring new and more effective VR authentication methods. This paper proposes a time-based one-time password (TOTP) authentication proof of concept for VR users, namely TOTPAuth. TOTPAuth protects VR users against identity theft under two threat models — pen-and-paper and video recording. We conducted empirical evaluations of TOTPAuth, and our results show that it is a highly effective defense against attackers’ attempts to observe and steal user identities. However, there are some trade-offs to consider, like a lower entry accuracy and a longer entry time. For readers interested in exploring TOTPAuth further, the source code is available on GitHub at https://github.com/lpy0927/TOTPAuth/tree/master.