Reviewerly/exHarmony huggingface dataset:
MalDEX: An Explainable Malware Detection System Based on Ensemble Learning

Ensuring the security of information systems in the modern technology era is a critical requirement due to the increasing complexity and volume of malicious codes and threats. However, traditional signature-based approaches for malware detection suffer from limitations in identifying unknown malware, susceptibility to adversarial samples, and suboptimal performance. To overcome these challenges, leveraging Artificial Intelligence (AI) and Machine Learning (ML) in malware detection has emerged as a promising avenue for enhancing the accuracy and effectiveness of defense systems. This study introduces MalDEX, a novel Explainable black-box malware detection system. MalDEX leverages attribute extraction from Windows Portable Executable (PE) files and employs a range of classifiers, including Single Algorithms, Homogeneous Ensemble Algorithms, and Heterogeneous Ensemble Algorithms, to determine the presence of malware. To evaluate the models’ quality and address interpretability concerns, we adopt the Kernel SHAP method. This method facilitates a comprehensive interpretation of the ML model’s decision-making process by examining the input’s contribution to decoding repetitive expectations. The experimental results demonstrate that the proposed system exhibits robust classification capabilities while providing descriptive visualizations and explanations elucidating the impact of features on prediction outcomes.
Supplemental Material: Is Geology Accreditation Needed? It Is Already Here!

&lt;p&gt; &lt;/p&gt; &lt;p&gt;In the 2000s, geoscience program accreditation was a regular topic in journal articles, opinion pieces, meeting sessions, and committee reports (e.g., Corbett and Corbett, 2001; GSA Ad Hoc Committee on Accreditation, 2008). Geoscience accreditation discussions subsequently subsided for apparent lack of proactive, interactive interest and with no consensus achieved (GSA Ad Hoc Committee on Accreditation, 2008; Bralower et al., 2008). Simultaneously, an increasing emphasis on continuous improvement in higher education has led to regular, formal assessment of student outcome achievement, efforts to align program outcomes to workforce needs, and expansion of competency-based learning. As a result, calls have been made for professional societies to develop certification, accreditation, or badging programs (Wikle, 2018; Mosher and Keane, 2021; Klyce and Ryker, 2022)&lt;/p&gt;
Https Article Testing

The man ate an extravagant meal at a fancy restaurant Ritzy This classy sentence uses three of some of the most commonly used words the a and an However there is more to these words than simply the number of times that we use them These three words belong to a class of words known as articles If you want to become a grammar master it is really important to know how to use articles because of how often they show up in our sentences
The Importance of Digital Literacy in Geography Learning for Geography Education Students at Fish Unima

The formulation of the research problem is how digital literacy ability in geography learning for students majoring in geography education at FISH Unima. The study aimed to determine digital literacy abilities in geography learning for FISH Unima geography education students. In achieving these objectives, this research was carried out using qualitative research methods, and data collection techniques which included: observation, interviews, documentation, and triangulation. The research informants were FISH Unima geography education students. The stages of data analysis include data reduction, data display, and conclusion drawing/verification. The results showed that results of the study showed that there were several digital literacy skills among students of FISH Unima geography education, namely: a) the ability to obtain various information needed in learning, b) the ability to use the internet, c) the ability to recognize computers as a means and technology in learning, d) the ability to use various digital media and e) the ability to understand sources as learning materials.
Japanese Government’s Survey of the Fishery Industry in Joseon Waters during the Port-opening period of Joseon

Examined in this article is the Japanese government’s survey of Joseon coastal fishery, since the year 1876 when the Joseon ports were open, and through 1910 when Korea lost its sovereignty to Japanese Imperialism. After it became possible for Japanese fishermen to operate in Joseon seas according to the Joseon-Japanese Commerce Treaty of 1883, the Japanese government felt the need to conduct some surveys of the Joseon coastal situation, in order to aid and support its own fishing industry. The Japanese government dispatched a fishery expert named Sekijawa Akekiyo(關澤明淸) to Korean shores in 1892, and had him examine the situation of Korean fishing industry. Based on his observations and information he collected, Sekijawa published a book entitled Joseon Tong’eo Sajeon (Joseon Language Dictionary) and shared it with the Japanese fishermen community.BR In 1897 the Japanese government declared ‘Promotion of Deep-sea Fishery Act,’ and provided Japanese fishermen with subsidiaries encouraging them to expand their operations in the coastal areas of Joseon, the Yeonhaeju(沿海州) area, and today’s Taiwanese region. Japanese fishery operations in those regions showed a sharp increase after that, and the Japanese central government and local authorities continued to survey Joseon coastal fishery and then also published more books to deliver such information to Japanese fishermen.BR After 1905, the Japanese government considered the previous approach of encouraging Japanese fishermen to merely operate in Joseon seas as a flawed one, because such approach was not delivering intended results. So it began to encourage their relocation to Joseon entirely, and Joseon coastal survey reports of the time even suggested how to aid Japanese fishermen’s relocation to Joseon. Based on those suggestions, the Tonggam-bu office’s Department of Agriculture and Commerce embarked on a task of publishing a culmination of prior survey results under the title Korean Fishery Industry Manual, which took total of five years since 1907. Eventually, the Tonggam-bu office declared the ‘Fishery Act’ in 1908, and laid out the foundation for the Japanese fishermen to take over the industry in Joseon coastal areas.
ENHANCING STUDENTS’ READING COMPREHENSION THROUGH DISCOVERY LEARNING METHOD AT THE SEVENTH GRADE OF SMP HARAPAN 3 DELI SERDANG

The objective of this study was to enhance the reading comprehension of seventh-grade junior high school students through the implementation of the discovery learning method. The research engaged English teachers, school principals, and seventh-grade students from SMP Harapan 3 Deli Serdang. The study encompassed a total of 30 participants, comprising 10 boys and 20 girls. Employing a classroom action research approach, the investigation was executed in two distinct cycles following a pre-test. Collaborating closely with English teachers, the researchers conducted the Pedagogical Action (PTK) with a student population of 30. Analysis of the data from both Cycle I and Cycle II led to the following findings: during the pre-test, 10 students achieved a success rate of 33.5%, while 20 students scored a lower rate of 66.5%. In Cycle 1, the success rate increased to 43.5% for 13 students, with a corresponding failure rate of 56.5% among 17 students. In Cycle II, the success rate further improved, as 22 students attained a rate of 73.5%, whereas 8 students encountered a failure rate of 26.5%. In conclusion, this study demonstrates a consistent elevation in student scores, underscoring the effectiveness of the discovery learning method in enhancing reading comprehension among seventh-grade students at SMP Harapan 3 Deli Serdang. The findings indicate that this method holds substantial promise for educators dedicated to nurturing the reading proficiency of their students.
RESEARCH ACTIVITIES OF STUDENTS IN THE CONTEXT OF DIGITAL TRANSFORMATION OF EDUCATION IN THE INTERESTS OF SUSTAINABLE DEVELOPMENT

The article offers a rationale for the relevant interpretation of the concepts of “sustainable development” and “education for sustainable development” in the context of the development of risk-oriented and practice-oriented approaches, which are reflected, first, in considering ESG-risks in investment activities and the appearance of a significant number of training programs for specialists with ESG-competences. The article presents a conceptual model of the education content for sustainable development in a higher education institution, which is based on the digital library on sustainable development of MGIMO University and considers the most relevant trends in the agenda of sustainable development: focus on the Sustainable Development Goals, climate risk prevention, low-carbon economic development, responsible financing, ESG-transformation. The article also presents results of content analysis of the key elements (in Russian and English) of the conceptual model of education for sustainable development in the most popular among students Internet resources of scientific literature: Google scholar, Science Direct, CyberLeninka, repository of preprints and articles on economics and finance IDEAS RePEc. As the results of the study show currently there is a significant base of information and analytical materials on sustainable development in the Internet. Each element of the proposed conceptual model is provided with a significant number of Internet sources in the form of scientific publications, which is one of the necessary conditions for students to study ways in achieving sustainable development and conduct research work herein
Virtual Experiments in Forensic Sciences

Given that it is not practical to collide several vehicles to try to repeat the damage pattern of a damaged vehicle, just as it is not possible to set fire to several industrial warehouses to analyze the pattern of fire behavior inside a warehouse where the origin of the fire, the forensic expert must have contemporary techniques that allow him to carry out non-invasive experimentation with the aim of repeating the conditions in which an event occurred. In this paper, the fundamentals of mathematical modeling of forensic phenomena are presented, as well as some examples of virtual experimentation applications used in judicialized cases.
A. F. Losev on the Neoplatonic Essence of Music in the Context of the Philosophy of Substantial Musical Existence (to the 130th Anniversary of the Birth of Aleksey Fedorovich Losev)

The article is written in connection with the anniversaries of the life of the great Russian thinker Alexey Fedorovich Losev and is devoted to one of the aspects of his aesthetic research related to the interpretation of music in Neoplatonism. This article makes sense to emphasize the substantial ontological essence of music, relying on Losev’s phenomenological-dialectical method, on his commitment to Neoplatonism as the last significant ancient philosophical movement. Losev considered the philosophical foundations of music in the cosmological treatises of such philosophers as Quintilian, Proclus, Sallust. Touching upon the ancient origins of the philosophy of music as an aesthetic field, the author refers to the Pythagorean teaching of the divine number and the musical harmony of the spheres. At the same time, Neoplatonic ancient philosophy demonstrates different types of existence of music, or ancient Greek music. The combination of the logical and the illogical in Losev’s philosophical thinking allows the author to present through the prism of the philosophy of substantial musical existence the closeness of the idea of the existence of the music of the Neoplatonists, proceeding from the ideas of the One, and Losev, the divine unity, where the thought of music goes far beyond the limits of the actual musical art. Music in philosophical knowledge is outside of art as world harmony, substance, becoming in time, divine number, or the life of numbers, the expression of the numerical first principle. In the sources, the author used the works of A. F. Losev: “The History of ancient Aesthetics”, “Dialectics of myth”, “Dialectical foundations of mathematics”, which presents a deep connection between mathematics and music. At the same time, the author relied on his aesthetic research “The Logos of music in the phenomenological-dialectical method of A. F. Losev”, and other chapters of his book “The Value of Music: a philosophical aspect” and his dissertation “The concept of the value of music as a substance and a way of value interaction of a person with the world”. Summarizing, the author moves from the dialectic of musical-substantial being to the philosophical concept of “musical” as an aesthetic category that requires further research.
THEORETICAL ASPECTS OF THE METHODOLOGICAL SYSTEM OF TRAINING MATHEMATICS TEACHERS

This article is devoted to the issues of training modern teachers of mathematics, the development of the ability to apply the knowledge received by a mathematics teacher in the process of professional activity and their role in the process of professional activity is sufficiently disclosed.
Analyzing Potentials and Barriers in Supply Chain Management in The Promise of Blockchain

This study explored the potentials and barriers to the implementation of blockchain technology in supply chain management (SCM). The purpose of the research was to determine the potential of implementing blockchain technology to enhance SCM performance, identify the challenges faced in implementing blockchain in SCM, and understand the constraints and obstacles that needed to be overcome for successful implementation. The research method applied was a Systematic Literature Review (SLR) using the PRISMA Protocol, with 73 papers collected from 2018 to June 2023. Data analysis was conducted through Meta-Synthesis. The findings provided insights into the theoretical, policy, and managerial implications of implementing blockchain technology in SCM, contributing to the advancement of knowledge in this field.
Enhancing EEG-based emotion recognition using PSD-Grouped Deep Echo State Network

Emotions are a crucial aspect of daily life and play a vital role in shaping human inter-actions. The purpose of this paper is to introduce a novel approach to recognize human emotions through the use of electroencephalogram (EEG) signals. To recognize these signals for emotion prediction, we employ a paradigm of Reservoir Computing (RC), called Echo State Network (ESN). In our analysis, we focus on two specific classes of emotion recognition: H/L Arousal and H/L Valence. We suggest using the Deep ESN model in conjunction with the Welch Power Spectral Density (Wlech PSD) method for emotion classification and feature extraction. Furthermore, we feed the selected features to a grouped ESN for recognizing emotions. Our approach is validated on the well-known DEAP benchmark, which includes the EEG data from 32 participants. The proposed model achieved 89.32% accuracy for H/L Arousal and 91.21% accuracy for H/L Valence on the DEAP dataset. The obtained results demonstrate the effectiveness of our approach, which yields good performance compared to existing models of emotion analysis based on EEG.
Face Plastic Surgery Recognition Model Based on Neural Network and Meta-Learning Model&amp;nbsp;

Facial recognition is a procedure of verifying a person&amp;#39;s identity by using the face, which is considered one of the biometric security methods. However, facial recognition methods face many challenges, such as face aging, wearing a face mask, having a beard, and undergoing plastic surgery, which decreases the accuracy of these methods. This study evaluates the impact of plastic surgery on face recognition models. The motivation for conducting the research in that aspect is because plastic surgery treatments do not only change the shape and texture of any face but also have increased rapidly in this era. This paper proposes a model based on an artificial neural network with model-agnostic meta-learning (ANN-MAML) for plastic surgery face recognition. This study aims to build a framework for face recognition before and after undergoing plastic surgery based on an artificial neural network. Also, the study seeks to clarify the collaboration between facial plastic surgery and facial recognition software to determine the issues. The researchers evaluated the proposed ANN-MAML&amp;#39;s performance using the HDA dataset.&amp;nbsp; The experimental results show that the proposed ANN-MAML learning model attained an accuracy of 90% in facial recognition using Rhinoplasty (Nose surgery) images, 91% on Blepharoplasty surgery (Eyelid surgery) images, 94% on Brow lift (Forehead surgery) images, as well as 92% on Rhytidectomy (Facelift) images. Finally, the results of the proposed model were compared with the baseline methods by the researchers, which showed the superiority of the ANN-MAML over the baselines.&amp;nbsp;
The Effect of Genre-Based Approach on Students' Proficiency in Writing Recount Text at Islamic Boarding Schools

This paper investigates the effectiveness of teaching recount texts using a genre-based approach on Islamic boarding school students. The research adopts a quantitative approach with a pre-experimental method, specifically the One-Group Pre-test-Post-test Design. The sample consists of 10 students from Class VIII of MTs SA Miftahul Huda Pabelan, which was selected based on specific criteria. The data were analyzed using the Paired Sample Test, which resulted in a significance value (Sig.) of 0.000. Based on the predetermined criteria, a significance value below 0.05 leads to the rejection of the null hypothesis (H0) and acceptance of the alternative hypothesis (Ha). In addition, there is a significant difference in the average scores between the Pre-test and Post-test, which were a pre-test mean score of 58.6 and a post-test mean score of 68.6. These findings indicate the effectiveness of the genre-based approach in improving students' skills to write recount texts in the boarding school context. In conclusion, the genre-based approach is effective in enhancing students' writing skills in the recount texts in the boarding school based on the findings.
Critical window of the symmetric perceptron

We study the critical window of the symmetric binary perceptron, or equivalently, random combinatorial discrepancy. Consider the problem of finding a ±1-valued vector σ satisfying ‖Aσ‖∞≤K, where A is an αn×n matrix with iid Gaussian entries. For fixed K, at which constraint densities α is this constraint satisfaction problem (CSP) satisfiable? A sharp threshold was recently established by Perkins and Xu [29], and Abbe, Li, and Sly [2], answering this to first order. Namely, for each K there exists an explicit critical density αc so that for any fixed ϵ>0, with high probability the CSP is satisfiable for αn<(αc−ϵ)n and unsatisfiable for αn>(αc+ϵ)n. This corresponds to a bound of o(n) on the size of the critical window. We sharpen these results significantly, as well as provide exponential tail bounds. Our main result is that, perhaps surprisingly, the critical window is actually at most of order log(n). More precisely, for a large constant C, with high probability the CSP is satisfiable for αn<αcn−Clog(n) and unsatisfiable for αn>αcn+C. These results add the the symmetric perceptron to the short list of CSP models for which a critical window is rigorously known, and to the even shorter list for which this window is known to have nearly constant width.
Design Characterization for Black-and-White Textures in Visualization

We investigate the use of 2D black-and-white textures for the visualization of categorical data and contribute a summary of texture attributes, and the results of three experiments that elicited design strategies as well as aesthetic and effectiveness measures. Black-and-white textures are useful, for instance, as a visual channel for categorical data on low-color displays, in 2D/3D print, to achieve the aesthetic of historic visualizations, or to retain the color hue channel for other visual mappings. We specifically study how to use what we call geometric and iconic textures. Geometric textures use patterns of repeated abstract geometric shapes, while iconic textures use repeated icons that may stand for data categories. We parameterized both types of textures and developed a tool for designers to create textures on simple charts by adjusting texture parameters. 30 visualization experts used our tool and designed 66 textured bar charts, pie charts, and maps. We then had 150 participants rate these designs for aesthetics. Finally, with the top-rated geometric and iconic textures, our perceptual assessment experiment with 150 participants revealed that textured charts perform about equally well as non-textured charts, and that there are some differences depending on the type of chart.
Radial Icicle Tree (RIT): Node Separation and Area Constancy

Icicles and sunbursts are two commonly-used visual representations of trees. While icicle trees can map data values faithfully to rectangles of different sizes, often some rectangles are too narrow to be noticed easily. When an icicle tree is transformed into a sunburst tree, the width of each rectangle becomes the length of an annular sector that is usually longer than the original width. While sunburst trees alleviate the problem of narrow rectangles in icicle trees, it no longer maintains the consistency of size encoding. At different tree depths, nodes of the same data values are displayed in annular sections of different sizes in a sunburst tree, though they are represented by rectangles of the same size in an icicle tree. Furthermore, two nodes from different subtrees could sometimes appear as a single node in both icicle trees and sunburst trees. In this paper, we propose a new visual representation, referred to as radial icicle tree (RIT), which transforms the rectangular bounding box of an icicle tree into a circle, circular sector, or annular sector while introducing gaps between nodes and maintaining area constancy for nodes of the same size. We applied the new visual design to several datasets. Both the analytical design process and user-centered evaluation have confirmed that this new design has improved the design of icicles and sunburst trees without introducing any relative demerit.
CommonsenseVIS: Visualizing and Understanding Commonsense Reasoning Capabilities of Natural Language Models.

Recently, large pretrained language models have achieved compelling performance on commonsense benchmarks. Nevertheless, it is unclear what commonsense knowledge the models learn and whether they solely exploit spurious patterns. Feature attributions are popular explainability techniques that identify important input concepts for model outputs. However, commonsense knowledge tends to be implicit and rarely explicitly presented in inputs. These methods cannot infer models' implicit reasoning over mentioned concepts. We present CommonsenseVIS, a visual explanatory system that utilizes external commonsense knowledge bases to contextualize model behavior for commonsense question-answering. Specifically, we extract relevant commonsense knowledge in inputs as references to align model behavior with human knowledge. Our system features multi-level visualization and interactive model probing and editing for different concepts and their underlying relations. Through a user study, we show that CommonsenseVIS helps NLP experts conduct a systematic and scalable visual analysis of models' relational reasoning over concepts in different situations.