Reviewerly/exHarmony huggingface dataset:
Problems of semantic reconstruction of the sociological narrative

A sociological narrative is a human’s storytelling in which another human is not always able to trace semantic connections in a relevant way. Such uncertainty has a detrimental effect in key cases of verbal description of social processes such as theory building, drafting laws and maintaining of document flow. Based on research in the areas of qualitative data analysis and knowledge management, the article expresses the conviction that a significant reason for the semantic uncertainty of the narrative is its construction by the author in the form of a text flow. The necessity and possibility of a natural language description of social processes in the form of a structural narrative is substantiated. Analytical coding is proposed as a tool for constructing such a narrative. In contrast to the approaches used today, analytical coding allows the researcher in a single instrumental procedure, on the one hand, to adhere to the habitual practice of verbal description of something; on the other hand, to structure their natural language wordings with the help of ontological methods of knowledge management. Specific analytical coding techniques are considered in detail within methodological cases in which a researcher finds him/herself when deciding to construct a narrative using analytical methods. Among such cases, the initial epistemological attitudes of the author of the narrative; localization of the meaning of a verbal statement by indicating the context; linking contextsensitive wordings; construction and generation of narrative semantic chains; instrumental control of narrative connectivity are mentioned. In conclusion, it is noted that the improvement of methods for constructing a structural narrative allows us reckoning on solving the problems of decomposition of verbal knowledge about social processes and on creating opportunities for interdisciplinary teamwork of specialists with different competencies
Supplemental Material: Dolomite cement microstratigraphy: A record of brine evolution and ore precipitation mechanisms, upper Knox Group, Tennessee and Kentucky, USA

&lt;p&gt;Sample descriptions and locations; detailed methodology; and high-resolution X-ray computed tomography animation of sample CA167-2483. &lt;/p&gt;
A Hybrid Filtering Technique of Digital Images in Multimedia Data Warehouses

The similarity search approach used for image Data Warehouse (DW) can provide better insights into discovering the most similar images compared to the input query.Due to the later innovation improvement, the mixed media complexity is discernibly expanded and modern inquires about regions are opened depending on comparable mixed media substance recovery.Content-Based Image Retrieval (CBIR) algorithms are utilized for the retrieval of images related to the inquiry image from gigantic databases or DW.The queries that are used for DW are complex, take a lot of time to process and many give less accurate results.For these reasons, this paper needs to have an effective technique to improve the similarity search query process that reflects a more positive result.In this paper, show how to extract features from a set of images (color, shape, and texture features) by using CBIR algorithm with Color Edge Detection (CED) method.Once these features are extracted, the proposed method will minimize the distance between these features vectors and the query image one using a Genetic Algorithm (GA).This paper illustrates the extraction of endless strong and imperative features from the database of the images, therefore, the capacity of these features in storing within the frame of features vectors.Accordingly, an imaginative closeness assessment with a metaheuristic algorithm (Genetic Algorithm (GA) with Simulating Annealing (SA)) has been attained between the query image features and those having a place in the database image.This paper introduces a new algorithm CEDF (Color Edge Detection with Gaussian Blur Filter) that applies the Gaussian Blur Filter after using CED method for feature detection of the image.Experimental results show that CEDF method gives better result than the other already-known methods.
An Evaluation of a Teacher's Guidance Services in Secondary Schools in Karachi

Today, the educational process is characterized by many features, but it also suffers from many problems, especially in developing countries. The process of mentoring can be traced back to when man began to exist, Kochhar (2011). Systematic career guidance was started between 1890 and 1905 by Frank Parsons, who is known as the father of career guidance. Most of the students in secondary level schools face such problems so these problems can be solved easily with the guidance of teachers. The purpose of this research is to identify the main issue teacher training needs in secondary schools and the role of management in this. The study was limited by limited time, expertise, resources and respondents. This research is inspired by developmental theory and the design we have used in our research is descriptive with qualitative paradigm. Data were collected through a structured interview protocol of a prescribed questionnaire. A face-to-face interview protocol was used as a data collection tool. Data were analyzed through a thematic approach. Findings from this study suggested that since the teacher is in direct and omnidirectional contact with the students, if he is used directly for the purpose of guidance, it will be better for the students.
Evaluasi Pemahaman dan Kinerja Pengguna Data iSIKHNAS

The national animal health information system (iSIKHNAS) aims to provide data related to animal health and present it to relevant stakeholders that can be utilized for the benefit of the community. The iSIKHNAS system can run well if there is an appropriate understanding by its users. This study aims to analyze the understanding of users (animal health officers) in the iSIKHNAS application system to improve the performance of animal health services. The research method used is to collect information or data and conduct an investigation on the data that has been obtained related to the level of understanding of iSIKHNAS users. Based on the information obtained, there is a phenomenon that illustrates that the understanding of officers related to iSIKHNAS has decreased, and the phenomenon of using the iSIKHNAS application is only to report service activities. The decrease in the level of understanding of users of the iSIKHNAS application can be caused by the lack of participation in new training and refresher training to update the knowledge of users.
Visualization of Source Code Similarity Using 2.5D Semantic Software Maps

For various program comprehension tasks, software visualization techniques can be beneficial by displaying aspects related to the behavior, structure, or evolution of software. In many cases, the question is related to the semantics of the source code files, e.g., the localization of files that implement specific features or the detection of files with similar semantics. This work presents a general software visualization technique for source code documents, which uses 3D glyphs placed on a two-dimensional reference plane. The relative positions of the glyphs captures their semantic relatedness. Our layout originates from applying Latent Dirichlet Allocation and Multidimensional Scaling on the comments and identifier names found in the source code files. Though different variants for 3D glyphs can be applied, we focus on cylinders, trees, and avatars. We discuss various mappings of data associated with source code documents to the visual variables of 3D glyphs for selected use cases and provide details on our visualization system.
Metaphor Recognition Method based on Graph Neural Network

This Metaphor is a very common language phenomenon.Human language often uses metaphor to express emotion, and metaphor recognition is also an important research content in the field of NLP.Official documents are a serious style and do not usually use rhetorical sentences.This paper aims to identify rhetorical metaphorical sentences in official documents.The use of metaphors in metaphorical sentences depends on the context.Based on this linguistic feature, this paper proposes a BertGAT model, which uses Bert to extract semantic features of sentences and transform the dependency relationship between Chinese text and sentences into connected graphs.Finally, the graph attention neural network is used to learn semantic features and syntactic structure information to complete sentence metaphor recognition.The proposed model is tested on the constructed domain dataset and the sentiment public dataset respectively.Experimental results show that the method proposed in this paper can effectively improve the recognition ability of metaphorical emotional sentences.
ANALYSIS OF OPINIONS’ RATIONALITY AND OBJECTIFICATION OF THE POLL

The ideological foundation of artificial intelligence as a scientific and applied field is an exact epistemology (EE), which is the study of the interaction of the cognizing subject and the corresponding object of cognition through heuristics and reasoning logics that generate new knowledge and its acceptance. Formal means of exact epistemology – languages of knowledge representation and logic of reasoning – and their practical implementation in computer systems provide constructive imitation and strengthening of some aspects of human intelligent activity. The formalization of cognitive activity is extremely in demand in the humanities, in particular, in the sciences of human and society. From the point of view of exact epistemology, a sociological poll – a traditional form of sociological research – is the interaction of the theoretical intelligence (one of the key concepts of EE) of the researcher and the respondents’ common sense. For a correct description of social reality, the question of the respondents’ rational perception of the elements of the questionnaire and the measure of rationality of individuals and their groups is not the last one. The scientific and constructively implemented apparatus of exact epistemology is the JSM-method of automated research support. The method has logical means for presenting opinions, as well as the formal presentation of a closed sociological poll. The instrumental capabilities of the JSM method provide a reasonable acceptance of new knowledge based on an expanded concept of rationality, including rationality as an argued opinion and argumentation, supported by formalized heuristics and the transformation of unclear ideas into precisely defined concepts.
Perancangan Sistem Pendukung Monitoring Kinerja Program Studi Dengan Metode Balanced Scorecard Studi Kasus: Prodi Di Fakultas Teknik UKDC

The activity of implementing the performance evaluation of study programs in tertiary institutions aims to improve internal quality in a sustainable manner. The performance evaluation process requires a gradual process, namely the performance monitoring process. Evaluation and monitoring of study program performance are generally implemented in the implementation of education, research, and community service to improve study program performance. Therefore, the priority of the main performance indicators of study programs in the Faculty of Engineering is determined by referring to the Chancellor's Regulation No. 03/PR/2022, classifies the main performance indicators of the Faculty of Engineering study program based on the dimensions of the balanced scorecard, and designs a work program monitoring spreadsheet to support KPI achievement. The research also aims to identify KPIs in four stages: customer perspective, financial perspective, business process perspective, and learning and growth perspective. The University has prioritized the 1st, 2nd, 4th, 6th and 7th performance indicators. Regulation of the Dean of the Faculty of Engineering No. 143/UKDC.1/A.01/XI/2022 as a reference in setting KPIs, this document has succeeded in formulating 22 main performance indicators and 5 additional performance indicators. Prioritized performance indicators are then made into a spreadsheet-based performance form which is useful in implementing performance monitoring&#x0D; &#x0D; Keywords: Performance measurement, balanced scorecard, key performance indicators
A Transcontinental Analysis of Account Remediation Protocols of Popular Websites

Websites are used regularly in our day-today lives, yet research has shown that it is challenging for many users to use them securely, e.g., most prominently due to weak passwords through which they access their accounts. At the same time, many services employ low-security measures, making their users even more prone to account compromises with little to no means of remediating compromised accounts. Additionally, remediating compromised accounts requires users to complete a series of steps, ideally all provided and explained by the service. However, for U.S.-based websites, prior research has shown that the advice provided by many services is often incomplete. To further understand the underlying issue and its implications, this paper reports on a study that analyzes the account remediation procedure covering the 50 most popular websites in 30 countries, 6 each in Africa, the Americas, Asia, Europe, and Oceania. We conducted the first transcontinental analysis on the account remediation protocols of popular websites. The analysis is based on 5 steps websites need to provide advice for: compromise discovery, account recovery, access limitation, service restoration, and prevention. We find that the lack of advice prior work identified for websites from the U.S. also holds across continents, with the presence ranging from 37% to 77% on average. Additionally, we identified considerable differences when comparing countries and continents, with countries in Africa and Oceania significantly more affected by the lack of advice. To address this, we suggest providing publicly available and easy-to-follow remediation advice for users and guidance for website providers so they can provide all the necessary information.
Expanding Louvain Algorithm for Clustering Relationship Formation

Community detection is a method to determine and to discover the existence of cluster or group that share the same interest, hobbies, purposes, projects, lifestyles, location or profession.There are some example of community detection algorithms that have been developed, such as strongly connected components algorithm, weakly connected components, label propagation, triangle count and average clustering coefficient, spectral optimization, Newman and Louvain modularity algorithm.Louvain method is the most efficient algorithm to detect communities in large scale network.Expansion of the Louvain Algorithm is carried out by forming a community based on connections between nodes (users) which are developed by adding weights to nodes to form clusters or referred to as clustering relationships.The next step is to perform weighting based on user relationships using a weighting algorithm that is formed by considering user account activity, such as giving each other recommendation comments, or to decide whether the relationship between the followers and the following is exist or not.The results of this study are the best modularity created with a value of 0.879 and the cluster test is 0.776.
FAPI-Net: A lightweight interpretable network based on feature augmentation and prototype interpretation

&lt;abstract&gt; &lt;p&gt;With the increasing application of deep neural networks, their performance requirements in various fields are increasing. Deep neural network models with higher performance generally have a high number of parameters and computation (FLOPs, Floating Point Operations), and have the black-box characteristic. This hinders the deployment of deep neural network models on low-power platforms, as well as sustainable development in high-risk decision-making fields. However, there is little work to ensure the interpretability of the model in the research on the lightweight of the deep neural network model. This paper proposed FAPI-Net (feature augmentation and prototype interpretation), a lightweight interpretable network. It combined feature augmentation convolution blocks and the prototype dictionary interpretability (PDI) module. The feature augmentation convolution block is composed of lightweight feature-map augmentation (FA) modules and a residual connection stack. The FA module could effectively reduce network parameters and computation without losing network accuracy. The PDI module can realize the visualization of model classification reasoning. FAPI-Net is designed regarding MobileNetV3's structure, and our experiments show that the FAPI-Net is more effective than MobileNetV3 and other advanced lightweight CNNs. Params and FLOPs on the ILSVRC2012 dataset are 2 and 20% lower than that on MobileNetV3, respectively, and FAPI-Net with a trainable PDI module has almost no loss of accuracy compared with baseline models. In addition, the ablation experiment on the CIFAR-10 dataset proved the effectiveness of the FA module used in FAPI-Net. The decision reasoning visualization experiments show that FAPI-Net could make the classification decision process of specific test images transparent.&lt;/p&gt; &lt;/abstract&gt;
Pengaruh Kecerdasan Emosional terhadap Hasil Belajar PKn Siswa SMK IT Al Izhar Pekanbaru

This research is motivated by students who are lacking in intellect, but have the ability to manage emotions, understand emotions, motivate themselves, empathy and the ability to build relationships with others. Emotional intelligence is one of the internal factors that affect learning outcomes. This study aims to analyze the effect of emotional intelligence on the learning outcomes of Civics Students of SMK IT Al Izhar Pekanbaru. This type of research is descriptive quantitative using proportional random sampling technique with a population of 136 students of SMK IT Al Izhar Pekanbaru and a sample of 34 people. The results of the research from the documentation obtained the mean or average value of the odd midterm exam scores of students of SMK IT Al Izhar Pekanbaru Civics subject of 84.5 and the questionnaire was analyzed using simple linear regression with the regression equation Y = 9.651 + 0.772X. Based on the results of the F test obtained, namely Fhitung&gt; Ftabel (122.497&gt; 4.15) which means that there is an influence of Emotional Intelligence on Civics Learning Outcomes of Students of SMK IT AL Izhar Pekanbaru with R Square of 0.932. This means that the contribution of the influence between emotional intelligence on learning outcomes is 93.2%, while 6.8% (100-93.2%) is influenced by other variables not examined in this study. So the conclusion that there is a significant influence between emotional intelligence on the learning outcomes of Civics Students of SMK IT Al Izhar Pekanbaru.
Exploring the Prospects of Future School Knowledge in the Socio-Cultural Field

Purpose: This study was conducted for the purpose of predicting future changes in the socio-culturalfield and exploring the direction of future school knowledge based on this.&#x0D; Methods: As future megatrends in the socio-cultural field, ‘changes in demographics and families’,‘increasing social disparities and inequality’, ‘intelligence/networking’, and ‘changes in values’ werederived. In order to draw the aspects and characteristics of future school knowledge for each megatrend,a Delphi survey was conducted twice with 15 experts in the socio-cultural field.&#x0D; Results: As a result of the Delphi survey, it is predicted that the composition of future school knowledgewill be formed between the following two axes in the social and cultural field. One axis is theunderstanding of human nature and human life, which does not change easily. The other axis is theexpectation of predicting the impact of changes in the times and environment on human life, adaptingto such changes, and creating changes to realize a better human life.&#x0D; Conclusion: In the future school knowledge, a phenomenal understanding, which was emphasized byconventional school knowledge, will still form an important axis. However, as well as such phenomenalunderstanding, the discovery and preparation of problems expected in future environmental changes,the devising and practice of solutions to those problems, and the values, attitudes and ethics thatgive direction and consistency to such practices, is expected to be emphasized significantly more thanit is now.
A Study on the Analysis of DISC Behavior Types of National Leaders

This study was conducted to improve the understanding of leaders' leadership in the future by analyzing the behavioral types of the three leaders (Moon Jae In, Kim Jong-un, and Trump), who were the main figures in the period closest to the peace regime on the Korean Peninsula. DISC behavioral type diagnostic tools were used to analyze the characteristics and leadership types of the three leaders. The expert Delphi technique was used as an analysis unit for the language of the three leaders and observable daily behavior. As a result of the analysis, President Moon Jae In was analyzed as an investigator who was careful with the SC type and solved the problem based on principles. Chairman Kim Jong-un was judged to be a delicate but decisive type as an SD type. Trump emphasized behavior and speed as type D, and was analyzed in detail as a result-oriented type. Based on the analysis results, the prediction of similar types of leaders in the future is as follows. First, a leader of a similar type to President Moon Jae In (SC type) forms a complementary partnership with a leader of the same type as Trump (D type). In addition, Moon Jae In and Kim Jong-un share internal motives and community values when the same S-type leader meets. Second, leaders with type D like Kim Jong-un (SD) and Trump (D) have something in common in the speed and way of pursuing goals, but leaders with S like Kim Jong-un tend to value promises and trust very much when pursuing goals. A leader of the same type as Kim Jong-un can take his own steps when he cannot trust his opponent.
A Study on the Current Situation and Improvement of Extracurriculum in College Basic General Mathematics

The purpose of this study is to improve how basic general mathematics extracurricular programs should be managed based on liberal arts education curriculum by comparing and analyzing the operation status according to the types of the liberal arts extracurricular programs operated by the university’s liberal arts education institution. It is necessary to establish a basic mathematics center inside the university to support and manage mathematics education for students of all disciplines. In this regard, professional professors in charge of mathematics extracurricular programs should be assigned, supported, and operated. In addition, to make students aware of the concept of the extracurricular program and the importance of its role, an active public relations system is required. This study will provide data in developing extracurricular programs related to the basic general mathematics and suggest directions for improvement of the basic general mathematics extracurricular programs.