Reviewerly/exHarmony huggingface dataset:
A New Matching Strategy for SIFT Based Copy-Move Forgery Detection

SIFT-based techniques have achieved satisfying performance in detecting copy-move forgery (CMF).Typically, these techniques find the matched regions of an image and re-examine them using a variety of methods to determine whether CMF has occurred or not.However, these techniques have some shortcomings related to how they handle false matches, which usually occur due to image continuity or self-similarity.First, a spatial distance threshold or segmentation-based methods are commonly utilized to handle image continuity.Second, several external methods along with manually created thresholds are utilized to handle image self-similarity.In this paper, we propose a new matching strategy that is resistant to false matches while reducing reliance on external methods and thus avoiding several thresholds.We model the keypoint as a whole region rather than a single point and employ the intersection over union measure to deal with image continuity.To reduce false matches caused by image selfsimilarity, we combine the cross-matching test with a modified distance ratio test.This combination takes into account the ability to detect multiple cloning.Moreover, we utilize a support vector machine to learn the threshold(s) needed to decide if CMF has occurred or not.The proposed methodology is evaluated over three challenging datasets: MICC-F600, Coverage, and MICC-F220.On MICC-F600 dataset, our proposed methodology outperforms other state-of-art techniques and achieves high precision of 99.38%, recall of 97.5%, and 98.42% of F1 score.Additionally, the comparative evaluation using Coverage, and MICC-F220 datasets proved the effectiveness of the proposed methodology to handle a variety of attacks.
Robustness to Spurious Correlations Improves Semantic Out-of-Distribution Detection

Methods which utilize the outputs or feature representations of predictive models have emerged as promising approaches for out-of-distribution (OOD) detection of image inputs. However, as demonstrated in previous work, these methods struggle to detect OOD inputs that share nuisance values (e.g. background) with in-distribution inputs. The detection of shared-nuisance OOD (SN-OOD) inputs is particularly relevant in real-world applications, as anomalies and in-distribution inputs tend to be captured in the same settings during deployment. In this work, we provide a possible explanation for these failures and propose nuisance-aware OOD detection to address them. Nuisance-aware OOD detection substitutes a classifier trained via Empirical Risk Minimization (ERM) with one that 1. approximates a distribution where the nuisance-label relationship is broken and 2. yields representations that are independent of the nuisance under this distribution, both marginally and conditioned on the label. We can train a classifier to achieve these objectives using Nuisance-Randomized Distillation (NuRD), an algorithm developed for OOD generalization under spurious correlations. Output- and feature-based nuisance-aware OOD detection perform substantially better than their original counterparts, succeeding even when detection based on domain generalization algorithms fails to improve performance.
Evidential Conditional Neural Processes

The Conditional Neural Process (CNP) family of models offer a promising direction to tackle few-shot problems by achieving better scalability and competitive predictive performance. However, the current CNP models only capture the overall uncertainty for the prediction made on a target data point. They lack a systematic fine-grained quantification on the distinct sources of uncertainty that are essential for model training and decision-making under the few-shot setting. We propose Evidential Conditional Neural Processes (ECNP), which replace the standard Gaussian distribution used by CNP with a much richer hierarchical Bayesian structure through evidential learning to achieve epistemic-aleatoric uncertainty decomposition. The evidential hierarchical structure also leads to a theoretically justified robustness over noisy training tasks. Theoretical analysis on the proposed ECNP establishes the relationship with CNP while offering deeper insights on the roles of the evidential parameters. Extensive experiments conducted on both synthetic and real-world data demonstrate the effectiveness of our proposed model in various few-shot settings.
STUDY THE IMPACT OF EMPLOYEE EMPOWERMENT ON JOB SATISFACTION

Purpose: The purpose of this study is to measure the factors affecting the performance of employee by discussing impact of employee empowerment on job satisfaction. Design/methodology/approach: Being descriptive study, survey method was adopted for data collection to find out the factors. The methodology comprised research design, Target population for the study, sampling techniques, sampling Method, sample size determination etc . Data was analyzed by using Cronbach’s Alpha, correlation and regression in SPSS software. Findings: The independent variable empowerment was weakly moderate correlated with dependent variable job satisfaction. Hence it is concluded that employee empowerment has a positive impact on the job satisfaction. Originality/value – The paper reveals there exist relationship between the performance of employee and factors affecting in employee performance and Job satisfaction.
Mobile Point of Sales (Mi-POS) Application for Cashiers Using React Native Framework A Case Study at Fajar Jaya Snack Shop

Toko Snack Fajar Jaya was a store that sold snacks in both bulk and retail. The store's current system still relied on manual bookkeeping, causing errors and uncertainties in data management and sales reports. To solve these problems, a mobile application called Mi-POS was developed using React Native to facilitate the development process. The application could record transactions, view transaction history, manage product inventory, and print receipts. The SDLC method was used in developing the application, and it was tested using Black-box Testing and the System Usability Scale (SUS) to evaluate its quality and effectiveness. Results from Black-box Testing showed that all features ran smoothly with an error rate of 0%. Meanwhile, SUS testing showed a score of 63.4, which falls in the "OK and usable" category.
75 years of the Volgograd Technical School of Railway Transport — branch of the Rostov State Transport University

The history and present days of the Volgograd Technical School of Railway Transport, a branch of the Rostov State Transport University, are considered. An innovative educational space has been formed in the technical school, within which teachers have developed personal websites with interactive elements, electronic learning modules, electronic laboratories, the idea of creating an educational mini-quantorium is being implemented. From the moment of its formation to the present day, the technical school conducts specialized training of mid-level specialists for railway transport enterprises. Classrooms, laboratories, workshops are equipped with modern training complexes, software that allows students to solve professional problems. The innovative educational space of the technical school not only provides training for a specialist in the railway industry who is competitive in the labor market, versed in related fields of activity, able to improve in professional skills, but also synchronizes training in accordance with the needs of the labor market. Today, the technical school is a modern educational institution that trains railway industry specialists who are in demand on the modern labor market under secondary vocational education programs.
Three-Dimensional Representation and Visualization of High-Grade and Low-Grade Glioma by Nakagami Imaging

Three-dimensional (3D) visualization of the brain tumors reconstructed from the two-dimensional (2D) magnetic resonance imaging (MRI) sequences plays an important role in volumetric calculations. The reconstructions are usually executed using the fluid attenuated inversion recovery (FLAIR) sequences, where the whole tumors appear brighter than the healthy surrounding tissues. Without any processing; however, reconstruction results might be inconclusive; therefore, we propose a mathematical m-parametric Nakagami imaging for highlighting the lesions. The raw 2D FLAIR MRI images are taken from BraTS 2012 dataset and the highlighted images are generated by the Nakagami imaging. The information on the MRI slices is compiled in three-layered Nakagami images for better visualization of the high-grade and low-grade glioma in 3D space. By the flexible m-parametric design, on the other hand, the reconstructed images might easily be adjusted according to the GT images for precise representation.
Improving Master’s Students’ Information Literacy Through Online Instruction

The ability to manage information obtained from the internet for learning purposes represents a difficult task for most students, even in higher education, where this ability takes on major importance for the writing of academic texts. The Information Problem Solving (IPS) model breaks down this ability into five different skills: defining research questions; planning research
Action research of written language instruction methods for elementary English underachievers

This action research aimed to investigate the challenges faced by underachieving English learners in elementary schools and to demonstrate the effectiveness and necessity of phonics in English reading instructions. The study provides case studies of two fifth-grade students who struggled with English learning and had low motivation. Data collection was conducted through 24 instructional sessions involving teaching phonics and sight words. Data from semi-structured interviews and classroom observations were collected inductively based on grounded theory. The findings showed that students faced difficulties in identifying alphabet letters and understanding phonics. These challenges led to a negative perception of learning English, further intensifying their learning difficulties. However, improvements in either the cognitive or affective aspects of learning led to a complementary relationship. This paper concludes by summarizing the two cases and asserting the need for early diagnosis of fundamental reading skills and individualized intensive guidance to teach underachieving students. In addition, continuous observation of the learning process and increasing students' interest and confidence to lower the affective filter are needed. This paper emphasizes the importance of teaching and learning strategies, as well as the roles of teachers and other surrounding environments of students in preventing the proliferation of underachievers in elementary English classes.
Premodification Evidence

This study has proposed that [N of a] unit in the evaluative modifier and binominal intensifier, and to some degree the evaluative binominal noun phase, shares formal and functional features with premodifiers. If this is true, this unit should have integrated into the preexisting premodification patterns in front of N2, and evidence of this change can be shown in the distribution of the premodifiers in the six of-binominals. This is tested using a dataset compiled from COCA consisting of 3,433 premodifier of-binominal tokens and Ghesquière’s (2014) zone-based premodifier classification. A Hierarchical Configural Frequency Analysis was conducted to explore the premodification patterns of each construction. The findings show that all six of-binominals demonstrate different premodification patterns and corroborates the findings that each are separate constructions. Furthermore, the evidence substantiates the claim that [N of a] forms a separate unit and is situated in the appropriate place in front of N2. It also demonstrates that these two constructions follow the grammaticalization path of more canonical premodifiers.
The EBNP Family: A Functional Discourse Grammar Analysis

The chapter begins with an introduction to the FDG theory and language model. The discussion includes some of the issues in the classification of premodifiers and compares the distinctions made in FDG with the construction-based model. The second section presents an FDG model of each of-binominal, illustrating how the model captures the differences between these constructions. By doing so, current issues in recent FDG research are addressed, such as the role of CxG like constructions in FDG, interfaces and mismatches between levels, and the distinction between operators and modifiers. One important finding is that FDG predicts the changes of premodification patterns found in Chapter 7. The historical analysis in the FDG frameworks shows that we are looking at the reduction of the internal components of the N-of-N template to a simple NP template, with a reanalyzed chunk [N of (a)], functioning first as a modifier and then as a lexical operator. Therefore, although we are structurally looking at an of-binominal, this term is actually a misnomer
Development of Student Youth’s Social Creativity in Remote Educational Space

The article presents the results of substantiating and implementing the student youth’s social creativity development methodology in remote educational space of a higher education institution. It has been specified that social creativity is characterized by freedom of choice, positive societal direction, motivated personal initiative, interest and high enough quality of innovative, independent organizatio-nal actions. Remote educational space has been described is being defined by interactivity, ability to operatively connect, integrativity of various means and instruments, creativity regarding decision making. Remote education instruments have been characterized. Such instruments allow percei-ving educational content and extracurricular activity as combined types of interaction in a remote space. A point of view, that methodo-logy of contemporary higher education pedago-gy is integrated by considering the combination of professional teaching tasks, has been presented. The methodology is being based on subject-subject approach, dialogue teaching, individual-oriented approach with event metho-dology of presenting information and involving recipients in interaction in online environment. It has been proven that contemporary lecturer is a specialist, who plans and organizes this pro-cess, becomes a provider of educational activi-ties during course provision, who teaches and ensures continuation of extracurricular interac-tion, aimed at realizing students’ social creativity.
Development of the Future Primary School Teachers’ Critical Thinking in the Process of Studying the General Foundations of Pedagogy

The article presents the theoretical and methodological foundations of the development of the future primary school teachers’ critical thinking in the process of studying the general foundations of pedagogy. The article highlights the scientific approaches to the essence of the concept of «critical thinking» in the works of both domestic and foreign researchers, the main features of critical thinking in the context of the current socio-cultural situation. The requirements of the professional standard for the training of the future teachers for critical thinking of educational specialists, the peculiarities of critical thinking of the future primary school teachers are revealed. The barriers to critical thinking of the future primary school teachers, the methods of diagnosing the peculiarities of critical thinking of the students are determined. The directions of development of critical thinking of the future primary school teachers in the process of studying the general foundations of pedagogy are presented: creation and analysis of problem situations that stimulate the development of critical thinking; training in critical analysis of scientific and pedagogical texts; forming skills to understand, build and critically evaluate the arguments in the process of analyzing scientific and pedagogical texts, pedagogical situations.
Rights and Values in Counter-Terrorism Online

Content moderation for counterterrorism purposes is hobbled by the problem of specificity: the difficulty of knowing what content could lead to violence. Online content is generated by terrorists and their supporters for sinister purposes but circulated and consumed by a far wider audience who may be inspired, disgusted or indifferent. The presence or discoverability of terrorism content may serve real and not merely abstract interests of freedom of expression and personal development. However, the traditional approach of identifying fundamental human rights which may or may not be outweighed by the counterterrorism interest is complicated by two factors discussed in this article: firstly, the unsuitability of the human rights framework in the online space; secondly, the difficulty of understanding trade-offs between restrictions on free expression and the capacity of the internet in its current form.
Does Imageable Language Make Your Tweets More Persuasive?

Imageability is a psycholinguistic property of words that indicates how quickly and easily a word evokes a mental image or other sensory experience. Highly imageable words are easier to read and comprehend, and, as a result, their use in communications, such as social media, makes messages more memorable, and, potentially, more impactful and influential. In this paper, we explore the relationship between the imageability of messages in social media and their influence on the target audience. We focus on messages surrounding important public events and approximate the influence of a message by the number of retweets the message receives. First, we propose novel ways to determine an imageability score for a text, utilizing combinations of word-level imageability scores from the MRCPD+ lexicon, as well as word embeddings, image caption data, and word frequency data. Next, we compare these new imageability score functions to a variety of simple baseline functions in correlation between tweet imageability and number of retweets in the domain of the 2017 French Presidential Elections. We find that the imageability score of messages is correlated with the number of retweets in general, and also when normalized for topic and novelty; thus, imageable language is potentially more influential. We consider grouping tweets into imageability score ranges, and find that tweets within higher ranges of imageability scores receive more retweets on average compared to tweets within lower ranges. Lastly, we manually annotate a small number of tweets for imageability and show that our imageability score functions agree well with the human annotators when the agreement between human raters is high.
Bringing humans at the core of cybersecurity: Challenges and future research directions

The prompt response to successfully adopt good cybersecurity practices from protecting passwords to security incidents’ responding to activating a disaster recovery or a business continuity plan depends upon the level of operators’ ability in problem solving, resilience, readiness, maturity, observation, and perception. New technologies, such as Artificial Intelligence (AI) can also be helpful to more effectively forecast or respond to serious incidents, especially to massive attacks. However, the cybersecurity operators need to alter their mindsets, adopt new behavioural patterns, and work attitudes to embrace and interact with AI-assistance during cyber defence activities. in addition, when the operators need to assess or mitigate AI socio-technical risks related to bias, transparency and equality, they will base their decisions for estimating or mitigating these risks on their behavioural, social, cultural, and ethical characteristics. In this paper, we are presenting challenges related to human and psychosocial factors of the cybersecurity operators. We also discuss the motives and drivers that impact the cognitive aspects (e.g., focus on operational tasks, attention, objectivity) of the cyber operations. We further identify how the cybersecurity operators’ personality traits impact the success of the cybersecurity practices and estimations and analyse research challenges, regarding the impact of operators’ profiles on their perceptions and interactions, with AI cyber defending tools and management of AI risks. Finally, we consider the impact these human factors may have on successful cybersecurity operations and practices and provide proposals for interdisciplinary research directions requiring the collaboration of cybersecurity experts, psychologists, and behavioural scientists.
Anonymous Collaboration in Metaverse

This paper introduces a method enabling anonymous collaboration in the metaverse. As the Internet is turning to its next revolution in which time and space are incorporated more thoroughly to the everyday communication, visual and aural communication are given more prominent roles. This might lead to more biased interaction since people may possess pre-judgmental attitudes regarding other people’s age, gender, and ethnical attributes, which could impact collaboration. These attributes are rather easy to visually change within the metaverse by simply changing the avatars’ appearance. This research focused on the real-time aural communication in the metaverse, and the risks of harmful profiling based on people’s language use and voice. The research setting was a custom-made metaverse, where two anonymized participants interacted with each other to achieve the goal through collaboration. In the study, their interaction was monitored. Afterwards, they answered to questions in which told about their experiences and tried to de-anonymize the other participant. This preliminary research indicated that via modulating the sound, it was possible to anonymize users to a reasonable range within the custom-made metaverse.
The effects of Virtual Reality from different visual perspectives on empathy.

Virtual Reality (VR), as a modern technology, can embody perspective-taking, making people see the world through the eyes of others. Many research has found that VR can be an effective medium to facilitate empathy; besides, some studies have investigated the underlying mechanism of empathy facilitation through VR devices. The current research examines whether the difference in visual perspective, which are represented as the first or third-person point of view, would affect the empathy facilitation of VR users.We invited forty people, separated into two groups as the first-person perspective group (1PP) and the third-person perspective group (3PP). The subjects were asked to watch the video through VR devices with same contents but from different points of view. The results indicated that there was no significant difference in empathy facilitation between the two groups. However, after dividing empathy into two dimensions, affective and cognitive empathy, the former showed a significant difference. Experiencing from the third-person perspective, the subjects aroused more emotions, such as guilty and compassion, thereby cultivating empathy toward the character of the video. Furthermore, for the feelings of the VR experience, the subjects of 1PP and 3PP displayed great disparity as well. Most of the subjects of 3PP subjectively considered the experience good, while the others felt neutral.