Reviewerly/exHarmony huggingface dataset:
Adaptation Strategy to Speak Sundanese as Intercultural Communication In Padjadjaran University

Intercultural communication often occurs in student life. The diverse campus consists of multi-ethnic students. One of them is the existence of Padjadjaran University which is a campus thick with its motherhood and is an educational destination for students outside Bandung. The purpose of this study was to find out how non-Sundanese students adapted and used what strategies to speak Sundanese with Sundanese students at Padjadjaran University. The theory used for this study is the accommodation communication toeri. this research method is qualitative. This study used Communication Accommodation Theory (CAT). The subjects of this study were three students from Padjadjaran University and the object of the study was what strategy they used to speak Sundanese as intercultural communication. The data collection technique of this study used semi-structured in-depth interviews. The results of this study showed that the three students used convergence strategies in intercultural communication. This strategy emphasizes speakers to follow the local language because they feel they have something in common with the Sundanese identity, are willing to use the Sundanese language and learn to use their accents and tones, and have the same motivation, namely using the Sundanese language to adapt to the local culture.
On the use of discrete-time quantum walks in decision theory

We present a short review of discrete-time quantum walks (DTQW) as a potentially useful and rich formalism to model human decision-making. We present a pedagogical introduction of the underlying formalism and main structural properties. We suggest that DTQW are particularly suitable for combining the two strands of literature on evidence accumulator models and on the quantum formalism of cognition. Due to the additional spin degree of freedom, models based on DTQW allow for a natural modeling of model choice and confidence rating in separate bases. Levels of introspection and self-assessment during choice deliberations can be modeled by the introduction of a probability for measurement of either position and/or spin of the DTQW, where each measurement act leads to a partial decoherence (corresponding to a step towards rationalization) of the deliberation process. We show how quantum walks predict observed probabilistic misperception like S-shaped subjective probability and conjunction fallacy. Our framework emphasizes the close relationship between response times and type of preferences and of responses. In particular, decision theories based on DTQW do not need to invoke two systems ("fast" and "slow") as in dual process theories. Within our DTQW framework, the two fast and slow systems are replaced by a single system, but with two types of self-assessment or introspection. The "thinking fast" regime is obtained with no or little self-assessment, while the "thinking slow" regime corresponds to a strong rate of self-assessment. We predict a trade-off between speed and accuracy, as empirically reported.
Extremal Steering Assemblages

Non-local correlations between a fully characterised quantum system and an untrusted black box device are described by an assemblage of conditional quantum states. These assemblages form a convex set, whose extremal points are relevant in many operational contexts. We give necessary and sufficient conditions for an assemblage to be extremal using linear independence conditions, and an algorithm to decompose a generic assemblage into extremal points. A Matlab implementation of this algorithm is provided in the supplementary material.
Changes in Curriculum Learning Goals

These demands have led them to increasingly see research and inquiry as key in students' development (Brew
Evaluations of imputation methods for missing data with random forest modeling: an application with unbalanced data with a three categories outcome, the linkage to HIV care Uganda study

Abstract Background: Incomplete observation units may contain important information about the population being studied, analysis conducted with the complete portion of the dataset, done in most standard statistical software, may produce biased or low statistical power results. In this paper we investigate the behavior of imputation methods for a linkage to HIV care study dataset with more than 60% incomplete cases. Methods: Missing data imputation algorithms amelia , missForest , mice and hmisc were considered. Two sets of simulations were conducted: first with the subset of data containing only complete observations and second with the whole dataset. Imputation accuracy and general behavior for each imputation algorithm were accessed in the first set. Random forest models were fit to evaluate overall prediction accuracy and sensitivity in both sets of simulations. Results: The imputed values by missForest, a single imputation method, were more accurate for all incomplete variables and scenarios. Median overall prediction accuracy of HIV status, a three levels outcome, was slightly higher after imputations with missForest and amelia ( approximately 52%, 61% and 65% for samples of 350, 700 and 1050 units respectively). In general, different missing percentages (20%, 40% and 60%) did not result in large changes in prediction or imputation accuracy and larger sample sizes performance improved for imputation and overall prediction accuracy but mixed results were observed with sensitivity. For the second set of simulations, missForest and amelia produced better overall prediction accuracy with larger samples (1200 versus 350 units). For new HIV positive HIV class, hmisc and mice presented better sensitivity, with median sensitivity 65% versus 50% and approximately 90% versus 20% for samples with 350 and 1200 units respectively, compared to incomplete samples. Conclusions: Imputation with mice and hmisc may be used for imputation when the main interest is to increase sensitivity in predicting new HIV positive. Furthermore, it is interesting to investigate which method gives more advantage for other performance measures of interest. Trial registration: NCT02545673
A new educational grading system based on fuzzy techniques

Abstract In this article, the authors propose a new educational grading system based on fuzzy techniques including five interrelated modules. Through an example used to illustrate the process of the proposed fuzzy educational grading system, we find that the proposed system satisfy the essential needs for educational grading systems as well as can overcome the limitations of some existing fuzzy educational grading systems. After making a discussion between the marks obtained from the proposed fuzzy educational grading system and the marks by the traditional method, we find that the proposed evaluation system can evaluate students' answer sheets in a more objective and intelligent manner. The aim of the proposed method is not to replace existing fuzzy educational grading systems but to enrich the present systems for students' learning achievement evaluation.
Attention-based Bi-Prediction Network with Knowledge Distillation for Versatile Video Coding (VVC)

Abstract In video coding, inter bi-prediction contributes to improve the coding efficiency significantly by producing precise fused prediction block. Although block-wise bi-prediction methods, such as bi-prediction with CU-level weight (BCW), are applied in Versatile Video Coding (VVC), linear fusion-based strategy is still difficult to represent diverse pixel variations inside a block. In addition, a pixel-wise bi-prediction method called bi-directional optical flow (BDOF) has been proposed to refine bi-prediction block. However, non-linear optical flow equation in BDOF mode is applied under assumptions so this method is yet unable to accurately compensate various kind of bi-prediction block. In this paper, we propose an attention-based bi-prediction network (ABPN) to substitute the whole existing bi-prediction methods. The proposed ABPN is designed to learn efficient representations of the fused features by utilizing attention mechanism. Furthermore, the knowledge distillation (KD)-based approach is employed to compress the size of the proposed network while keeping comparable output as the large model. The proposed ABPN is integrated into the VTM-11.0 NNVC-1.0 standard reference software. When compared with VTM anchor, it is verified that the BD-rate reduction of the lightweighted ABPN can be up to 5.89\% and 4.91\% on Y component under random access (RA) and low delay B (LDB), respectively.
The Psychological Contract and Employee Job Performance: The Role of Employee Involvement

Many organisations today are bothered by how to ensure good employee performance whose main aim is to remain competitive given a stiff competitive environment.There has been growing belief that the psychological contract influences employee performance in an organisation without knowledge that this relationship can well be enhanced with employee involvement.This study specifically focused on the psychological contract and employee job performance with a focus on employee involvement and how it mediates between the adoption of the psychological contract and employee job performance in an organisation.In establishing this linkage, the authors employed a qualitative systematic review with a Prisma in which the researcher's reviewed literature that relates to the variable in the study to reach at a logical conclusion.The findings revealed that while the psychological contract affects employee job performance, involving employee will result into more positive results to employee job performance.Where the psychological contract is positive and employees are well involved will lead to better employee job performance which will also have a positive impact on business performance.
Pre-image attack of the MD5 hash function by proportional logic

Hash functions are important cryptographic primitives that map arbitrary length messages to fixed length message summaries such that: it is easy to compute the digest given a message, while invert the hash process (for example, finding a message that maps a summary of a specific message) is difficult. An attack against a hash function is an algorithm that nevertheless manages to invert the hash process. Hash functions are used in authentication, digital signature, and key exchange systems. The most widely used hash function in many applications is the Message Digest-5 (MD5) algorithm. In this paper we study the current state of the technique of realization of the preimage attack of MD5 using solver SAT, we try improvements in the process of encoding and resolution. An important part of our work is to use the methods of propositional logic to model the attack problem and to determine which heuristic leads to the best resolution. Our most important result is a new encoding of the addition to several operands which considerably reduce the time required for the SAT solvers to find a solution to coding’s previously known.
Kinematics and Dynamics of a Particle in Gravitation Field

It is accepted that three-dimensional physical space is a hypersurface with a Riemannian metric in four-dimensional space. The metric tensor of this three-dimensional space is defined by Einstein's equations. Another coordinate of four-dimensional space is time. In this space, the equations of the world line of a particle with a mass m are defined under certain initial conditions: the starting point of the space and the vector of the particle's initial velocity. This approach removes all the problems and contradictions noted in the monograph [1], and the resulting equations adequately describe, for example, the curvilinear motion of planets without energy change.
Pengaruh Learning Cycle Terhadap Hasil Belajar IPS Tema Kayanya Negeriku pada Siswa Kelas IV di Sekolah Dasar

This exploration applies quantitative exploratory strategies, the center is to see that there is no impact of the Learning Cycle on friendly examinations learning results. This review applies semi exploratory strategies whose subjects are trial and control classes. The example is class IV A 30 understudies and class B 30 understudies, so the populace is 60 understudies. This analysis test takes the form of a normality test (Liliefor test) and a homogeneity test (Fisher test). The final result of the t-test is thitung = 3,23&gt;ttabel = 2,00 then H0 is rejected while H1 is accepted. Thus, it implies that there is an influence of the learning cycle on social studies learning outcomes.&#x0D; Penelitian ini menerapkan metode kuantitatif eksperimen. Tujuannya untuk melihat ada tidaknya pengaruh learning cycle terhadap hasil belajar IPS. Penelitian ini mengaplikasikan metode quasi eksperimen yang subjeknya kelas eksperimen dan kontrol. Sampelnya kelas IV A 30 siswa dan kelas B 30 siswa, sehingga populasinya 60 siswa. Pengujian analisis ini berbentuk uji normalitas (uji Liliefors) dan uji homogenitas (uji Fisher). Hasil akhir uji-t yakni thitung = 3,23 &gt; ttabel = 2,00, maka H0 ditolak sementara H1 diterima. Dengan ini, memiliki implikasi bahwa ada pengaruh Learning Cycle terhadap hasil belajar IPS.&#x0D;
Unambiguous Identification of Objects in Different Environments and Conditions Based on Holographic Machine Learning Algorithms

Unambiguous provision of results in different environments and conditions by machine learning algorithms is an unresolved problem until now. Solving the problem of machine learning with unambiguous provision of results in different environments and conditions can be approached by focusing on the psychophysical holographic process of human learning. A person, with a mental concentration of attention, experimentally teaches vision, hearing, psyche and mind in a holographic way and in a resonant way to perceive, recognize and recognize phenomena, processes, objects, subjects, meanings, music and other entities in various environments and conditions. A person experimentally teaches the psyche and feelings to rationally navigate in various environments and conditions. Holographic algorithms of experienced machine learning will help neural network ensembles to unambiguously recognize objects, subjects, music, texts in various environments and conditions using a model of recognizing their own or someone else's. Machine learning simulates holographic processes of human communication memorization of entities. Searching for objects in different environments in different conditions based on experienced machine learning simulates resonant associative processes of human entity detection. By simulating holographic processes of the human psyche based on artificial intelligence of machine learning with Fourier transformation, using full parametric sequences of necessary and sufficient data of holograms of target objects, it is possible to solve the problem of their unambiguous detection in different environments and in different conditions.
Demonstration of alignment of the Pan-European Cybersecurity Incidents Information Sharing Platform to Cybersecurity policy, regulatory and legislative advancements

The path to the Digital Decade in Europe is realized by various governance and regulatory frameworks that aim to materialize this core European strategy. The EU cybersecurity strategy projects to safeguard this path and enable a swift but smooth transition. Arguably, EU is constantly taking actions to address cybersecurity challenges and promote cyber resilience, focusing primarily in critical sectors such as energy. This imposes significant challenges for the cybersecurity technology providers and requires a flexible, adaptive and agile design and development approach. The presented work is an evolution of the ARES2021 paper “Pan-European Cybersecurity Incidents Information Sharing Platform to support NIS Directive” that further aligns with advancements in the European Cybersecurity policy and regulations landscape. This is feasible since the development of the Incidents Information Sharing Platform (I2SP) is agile, adaptive and has continuously been driven by the advancements observed and imposed by the European cybersecurity regulatory framework. The current work showcases the I2SP design enhancements to address the latest EU cybersecurity regulatory framework updates relating to the Network Code on Cybersecurity (NCCS), NIS2 and the Cyber Resilience Act, highlighting the stringent alignment between I2SP and the EU cybersecurity strategy.
Authentication for Operators of Critical Medical Devices: A Contribution to Analysis of Design Trade-offs

Increasingly evident safety risks due to attacks on safety-critical devices are causing new requirements for authentication of these devices’ human operators. These requirements have now extended to medical devices. However, authentication may also introduce new safety risks, reduce usability, cause delays, and/or encourage user behaviors that compromise the very security it should protect. Thus, design of authentication mechanisms needs to take on a holistic approach that considers such interrelationships, and the effects not just of the general method chosen (say, passwords vs. fingerprints), but also of its implementation details. We illustrate this problem on a medical case study. We report early steps in a trade-off analysis that captures interactions between safety, security, usability and performance issues, to assist designers in choosing and tuning viable solutions. A qualitative analysis to narrow down the field of possible solutions is followed by a probabilistic analysis. The analyses highlight non-obvious links between system attributes, especially links due to the complex way humans interact with, and adapt to, such devices. The probabilistic analysis systematically describes risk as a function of the authentication method and its design parameters. We show example results quantifying how some key design parameters produce opposite effects on risk due to accidental and malicious causes, requiring a trade-off: the quantitative model allows the designer to manage this trade-off to achieve an acceptable level of overall risk, taking into account environmental factors like the expected prevalence of certain attack types. Both the qualitative and quantitative approaches aim to help device designers make rational decisions about authentication options and the tuning of their design parameters.
Digital almost nets

Digital nets (in base $2$) are the subsets of $[0,1]^d$ that contain the expected number of points in every not-too-small dyadic box. We construct sets that contain almost the expected number of points in every such box, but which are exponentially smaller than the digital nets. We also establish a lower bound on the size of such almost nets.
Application of Image Color Gamut Boundary Judgment Algorithm in Digital Media

Image chromatic aberration evaluation is one of the research hotspots and academic difficulties in the field of color science and imaging technology. Based on the algorithm theory of image color gamut boundary judgment, this paper constructs its application model in digital media. The model uses the threshold color difference image as a reference and applies it to the evaluation experiment of color difference above the threshold based on the quantitative estimation method. During the simulation process, the improved HAD dual-color image digital boundary judgment algorithm is programmed. For small color difference data at the threshold level, the calculated color difference of the boundary judgment algorithm framework is smaller than the visual perception color difference; for the large color difference data above the threshold, the boundary judgment algorithm framework is given. The research results of the threshold color difference experiment show that the perceptible color difference threshold and acceptable color difference threshold of image color gamut observers for image color difference are 1.85 AE and 3.63 AE, respectively, which are basically twice the relationship. The visually perceptible chromatic aberration threshold and acceptable chromatic aberration threshold for lightness parameters are higher than those of chroma and hue, which shows that the boundary judgment algorithm framework has certain advantages for the evaluation performance of color digital image threshold chromatic aberration and effectively improves the algorithm robustness.
Stochastic Matrix Modelling and Scheduling Algorithm of Distributed Intelligent Computing System

Parallel and distributed processing has always been a hot field of scientific and technological research, development, and application. It is an important solution in the fields of scientific computing and data service processing, such as weather prediction, wind tunnel Reynolds numerical calculation, and financial services. Intelligent cloud computing has higher requirements for high-capacity and efficient computing. The ability of existing computing system has been difficult to meet its needs. It is necessary to establish an intelligent computing system with the self-organizing ability and realize efficient task scheduling. Since the coordination of computing and storage resource scheduling becomes the key to scheduling, this study designs scheduling tasks based on a large-scale multi-task distributed system, establishes the model of distributed intelligent computing system and the multi-objective optimization model of the task scheduling problem, and designs the IPSO algorithm combined with improved particle swarm optimization algorithm according to the model. First, the particle swarm optimization algorithm is used to generate the initial scheduling scheme, then the ant colony algorithm is initialized, and the final scheduling results are generated. Simulation results show that the performance of the algorithm has obvious performance advantages compared with the improved particle swarm optimization algorithm and the improved ant colony algorithm. In addition, this study presents the task migration conditions and optimization methods under the dual objectives of makespan and availability. This optimization operation increases the system availability without increasing the scheduling length. In the distributed system with heterogeneous availability, the algorithm is effective in the dual objective performance optimization of task completion time and system availability.
The Diversified Communication Methods of Chinese and Korean Cultural Education Based on New Media Technology

In the current era of multicultural exchange and integration, the Chinese and Korean cultures have shown the ideal effect of cultural deep integration through interaction and exchange to promote cultural exchanges better, to view the diversified communication between Chinese and Korean cultures with correct cultural views, so as to better find the common points of effective integration of the two cultures, understand and respect the differences between Chinese and Korean cultures, and effectively improve the effect of the application of Chinese and Korean cultural integration by selecting appropriate integration perspective. Based on the understanding of cultural connotation and the analysis of the current situation of cultural education in China and South Korea, this study explores the mechanism of cultural and educational diversification exchange in China and South Korea under the cultural background and puts forward relevant optimization suggestions.