Interactive Analysis Approach Research Articles

IntiVisor: A Visual Analytics System for Interaction Log Analysis.

Application developers frequently augment their code to produce event logs of specific operations performed by their users. Subsequent analysis of these event logs can help provide insight about the users' behavior relative to its intended use. The analysis process typically includes both event organization and pattern discovery activities. However, most existing visual analytics systems for interaction log analysis excel at supporting pattern discovery and overlook the importance of flexible event organization. This omission limits the practical application of these systems. Therefore, we developed a novel visual analytics system called IntiVisor that implements the entire end-to-end interaction analysis approach. An evaluation of the system with interaction data from four visualization applications showed the value and importance of supporting event organization in interaction log analysis.

Penerapan prinsip authentic assessment pada pembelajaran matematika di sekolah dasar

<p><em>In the learning process, assessment is crucial since it establishes students' differences from one another and their level of quality. Complete assessment will influence learning and serve as a guide for future policies. The precision with which evaluation principles are used will have a significant impact on validity and objectivity. In order to evaluate math learning in elementary schools, this study will look at how authentic assessment methods are applied. This study is a qualitative descriptive one. The subjects of the study were teachers, administrators, and students. In this study, interviews, observation, and document analysis were employed to obtain data. The Miles and Huberman model of interactive data analysis approaches is used in this study's data analysis method. Techniques for assessing the validity of data rely on a triangulation of sources, methods, and times. The findings of this research indicate that the principles of elementary school mathematics learning assessment are effective in realizing the authentic assessment concept.</em></p><p><em> </em></p><p><em> </em></p>

A case study of young children’s play negotiations in free play

ABSTRACT This study seeks to understand how children express themselves socially and emotionally in play negotiations in early childhood education and care (ECEC) settings. It addresses the following research questions: What strategies do children employ in play negotiations? How do these strategies manifest themselves socially and emotionally? The study was conducted in eight ECEC centers and one preschool located in Swedish-speaking regions of Finland. The target group consisted of children aged 3–6. Data were collected through video observations that captured children’s social interactions and engagement with their peers during free play. A multimodal interaction analysis approach was employed to identify a prominent category termed ”exclusion”, which refers to how children employ strategies (e.g., fantasy and fiction) to limit the participation of other children in play negotiations. The results of this study contribute to our understanding of children’s complex play negotiations and highlight the significance of addressing their social and emotional development in these contexts.

Village Government Accountability and Transparency in Village Financial Management

This study aims to find out the accountability and transparency procedures of the village government in managing village finances (Study in Karangsari Village, Kutowinangun District, Kebumen Regency). This type of research is a qualitative research with an interactive analysis approach. Data was collected through in-depth interviews, observations and document studies which were then analyzed using an interactive analysis model through four stages, namely (1) Data Collection, (2) Data Reduction, (3) Data Presentation, (4) Conclusion Drawing. The results of the study show that (1) Accountability at the planning, implementation, administration, and financial management reporting stages (2) Transparency of village finances in Karangsari Village in its implementation is guided by the Minister of Home Affairs Regulation Number 20 of 2018. The Karangsari Village Government as the executor of village financial management has carried out the Village Financial Accountability and Transparency process quite well. However, there must be improvements in village financial management and financial accountability by seeking new innovations. And in providing information to the public must be optimized

GENDER-RESPONSIVE AND CHILD-FRIENDLY VILLAGES THROUGH SAPA MAMA INNOVATION AND COMMUNITY EMPOWERMENT

Nganjuk District has a high Gender Development Index (IPG) score. “Sapa Mama” was formed as an embodiment of Nganjuk Regency and is child-friendly and gender-responsive. This study aims to examine the implementation of empowering local communities through the Sapa Mama innovation, which focuses on child-friendly and gender-responsive village efforts. The research method used is qualitative research with an interactive analysis approach. The data was obtained through observation, documentation, and interviews with the public and institutions related to the Sapa Mama innovation, which was then evaluated, interpreted, and discussed according to the established theory. The outcomes of research on the advantages of Sapa Mama innovation, there are several activity programs within the Sapa Mama innovation in the form of formal programs specifically for children, women, and marginalized communities that have been put to good use by the community and have had a positive impact. Rejoso Village has attempted to run the Sapa Mama innovation program following the law on village innovation that has been stipulated and seeks to be gender-responsive in the Sapa Mama agenda. The practical implication is that the relevant government must pay more special attention to superior village products to broaden the spectrum of purchasing power and create new jobs, especially for rural women.

Reconstruction of The Selodang Mayang Dance at Amantubillah Palace in Mempawah, West Kalimantan Province

This article is the result of research that focuses on the main issue of how the process of reconstructing the Selodang Mayang dance at Amantubillah Palace takes place. The Selodang Mayang dance is a welcoming dance that developed within the Royal Palace of Amantubillah in Mempawah Regency, West Kalimantan Province. The aim of this research was to understand and explain each stage of the reconstruction process of the Selodang Mayang dance, which aimed to revive the Selodang Mayang dance. The forms of the reconstructed Selodang Mayang dance include 1) Movement, 2) Music, 3) Costumes and Makeup, 4) Props, and 5) Floor Patterns. This research employed a qualitative method with an interaction analysis approach. The results of this research revealed a series of movements of the Selodang Mayang dance that use basic graceful steps of lenggang, with arms waving left and right in accordance with the rhythm of the accompanying music. In these movements, there are absolute rules from the palace regarding the motifs of the Selodang Mayang dance, such as graceful steps, arms not lifted beyond 45 degrees, a smiling face, no spinning movements, not turning the back to guests, keeping the legs from spreading wide, and adapting the movements to the lyrics used in the accompanying Selodang Mayang dance. The research findings also include the process conducted by the Selodang Mayang dance reconstruction team in the effort to preserve classical dance art. The objective of this research was to understand, study, and preserve the cultural values existing in Mempawah Regency, so that the Selodang Mayang dance continues to exist and thrive within the palace and the local community.

Backward Design : Strategi Pembelajaran dalam Meningkatkan Keterlibatan Siswa

This research aims to explore the backward design model as a learning strategy to enhance student engagement. This research adopts a descriptive approach with a qualitative method. The participants of this study were high school teachers selected through the snowball sampling technique. The data collection was conducted through interviews and participatory observation, while data analysis follows an interactive model analysis approach, including data reduction, data display, and conclusion drawing/verification. The research findings indicated that the backward design was one of the effective learning design models as it focused on understanding and developing students' thinking skills. The model directed teachers to set learning objectives that wereappropriate to the student's needs and skills, conduct assessments to measure students' understanding and skills and formulate when delivering materials or certain concepts gradually. Implementing concept-checking techniques allows teachers to measure students' understanding periodically, and applying interaction patterns accommodates continuous interactions.

Penggunaan Media Sosial Sebagai Media Komunikasi Dalam Penyebaran Informasi Pada Dinas Kominfo Kota Medan

The emergence of social media has had a significant impact on the way people communicate. This applies not only to individuals but also to government organizations. Most local governments in Indonesia have yet to harness the presence of social media as a means of communication. The objective of this research is to identify the use of social media as a communication medium in the dissemination of information and the barriers to information dissemination from the Office of Communication and Information Services (Kominfo) in the city of Medan. This study utilizes a qualitative descriptive method. Interviews, observations, or in-depth documentation are used as data collection approaches. The snowball sampling method is employed to identify informants. Data triangulation is used to examine the accuracy of the data, with the hope of reducing potential inaccuracies. The main components of the interactive data analysis approach used in this study are data reduction, data display, conclusion drawing, and verification. The output of this study is the utilization of social media by the Office of Communication and Information Services (Kominfo) in the city of Medan as a communication tool.

High-dimensional spatiotemporal visual analysis of the air quality in China

Air quality is a significant environmental issue among the Chinese people and even the global population, and it affects both human health and the Earth’s long-term sustainability. In this study, we proposed a multiperspective, high-dimensional spatiotemporal data visualization and interactive analysis method, and we studied and analyzed the relationship between the air quality and several influencing factors, including meteorology, population, and economics. Six visualization methods were integrated in this study, each specifically designed and improved for visualization analysis purposes. To reveal the spatiotemporal distribution and potential impact of the air quality, we designed a comprehensive coupled visual interactive analysis approach visually express both high-dimensional and spatiotemporal attributes, reveal the overall situation and explain the relationship between attributes. We clarified the current spatiotemporal distribution, development trends, and influencing factors of the air quality in China through interactive visual analysis of a 25-dimensional dataset involving 31 Chinese provinces. We also verified the correctness and effectiveness of relevant policies and demonstrated the advantages of our method.

Manajemen Tenaga Kependidikan di Sekolah Dasar Islam Terpadu

This study aims to look at the management of teachers and educational staff in one of the primary schools. The effectiveness of the learning process and the achievement of students is largely dependent on the performance of the education personnel, which includes instructors and other staff members. Teachers, staff, and principals served as the data sources for this qualitative descriptive study. Interviews, observations, and document studies are the methods utilized for gathering data. Triangulation of methods and sources is used to verify the accuracy of the data. The Miles, Huberman, and Saldana interactive analysis approach, which consists of three stages—data condensation, data presentation, and conclusion/verification—is used for data analysis. The findings indicated that the administration of educational people in schools involves six stages, including planning, recruitment, job placement, remuneration, and evaluation. Steps in the recruitment process include receiving cover letters, conducting selection interviews, checking references and applicants' backgrounds, evaluating applicants' health, and interviewing school principals. Through discussions, the division and placement of work is done in accordance with academic credentials and talents. Staff members in the education sector are paid in the form of a salary or an honor based on their performance. Working groups for teachers (KKG) and school principals (KKKS) are used to create competencies, along with ongoing professional development. (PKB). The principal and supervisors conduct evaluations on a regular basis. Administrative monitoring is also conducted, as well as a semesterly evaluation of teacher performance.

Identification of CCR2 as a hub in septic myocardial injury and cardioprotection of silibinin.

Myocardial injury is a serious complication of sepsis associated with high morbidity and mortality. Our previous work has confirmed that silibinin (SIL) alleviates septic myocardial injury, but the specific molecular mechanism has not been fully elucidated. This study aimed to identify its potential targets through network pharmacology combined with experimental verification. Firstly, a total of 29 overlapping genes between sepsis and SIL targets were obtained from RNA-seq analysis and the known databases. Subsequently, KEGG and GO analysis showed that these genes were enriched in immune response and cytokine-cytokine receptor interaction pathways. Notably, CCR2 was identified as an important candidate hub by protein-protein interaction analysis and molecular docking approach. In vivo experiments showed that SIL treatment significantly improved survival rate and cardiac function in septic mice, accompanied by decreased CCR2 expression. Moreover, in vitro experiments obtained the similar results. Especially, CCR2 siRNA attenuated inflammation response. In conclusion, this study systematically elucidated the key target of SIL in the treatment of septic myocardial injury. These findings provide valuable insights into the targets of sepsis and offer new avenues for exploring drug effect systematically.

DivBrowse-interactive visualization and exploratory data analysis of variant call matrices.

The sequencing of whole genomes is becoming increasingly affordable. In this context, large-scale sequencing projects are generating ever larger datasets of species-specific genomic diversity. As a consequence, more and more genomic data need to be made easily accessible and analyzable to the scientific community. We present DivBrowse, a web application for interactive visualization and exploratory analysis of genomic diversity data stored in Variant Call Format (VCF) files of any size. By seamlessly combining BLAST as an entry point together with interactive data analysis features such as principal component analysis in one graphical user interface, DivBrowse provides a novel and unique set of exploratory data analysis capabilities for genomic biodiversity datasets. The capability to integrate DivBrowse into existing web applications supports interoperability between different web applications. Built-in interactive computation of principal component analysis allows users to perform ad hoc analysis of the population structure based on specific genetic elements such as genes and exons. Data interoperability is supported by the ability to export genomic diversity data in VCF and General Feature Format 3 files. DivBrowse offers a novel approach for interactive visualization and analysis of genomic diversity data and optionally also gene annotation data by including features like interactive calculation of variant frequencies and principal component analysis. The use of established standard file formats for data input supports interoperability and seamless deployment of application instances based on the data output of established bioinformatics pipelines.

Two-level Bayesian interaction analysis for survival data incorporating pathway information.

Genetic interactions play an important role in the progression of complex diseases, providing explanation of variations in disease phenotype missed by main genetic effects. Comparatively, there are fewer studies on survival time, given its challenging characteristics such as censoring. In recent biomedical research, two-level analysis of both genes and their involved pathways has received much attention and been demonstrated as more effective than single-level analysis. However, such analysis is usually limited to main effects. Pathways are not isolated, and their interactions have also been suggested to have important contributions to the prognosis of complex diseases. In this paper, we develop a novel two-level Bayesian interaction analysis approach for survival data. This approach is the first to conduct the analysis of lower-level gene-gene interactions and higher-level pathway-pathway interactions simultaneously. Significantly advancing from the existing Bayesian studies based on the Markov Chain Monte Carlo (MCMC) technique, we propose a variational inference framework based on the accelerated failure time model with effective priors to accommodate two-level selection as well as censoring. Its computational efficiency is much desirable for high-dimensional interaction analysis. We examine performance of the proposed approach using extensive simulation. The application to TCGA melanoma and lung adenocarcinoma data leads to biologically sensible findings with satisfactory prediction accuracy and selectionstability.

Internalization of Organizational Culture at Sultan Aji Muhammad Idris State Islamic University Samarinda

The purpose of this study is to describe the internalization of organizational culture at UINSI Samarinda. This study uses qualitative research with data collection techniques through observation, interviews and documentation. The data analysis technique is using an interactive data analysis approach data condensation, data presentation and conclusion drawing. The validity of the data was tested using source triangulation and technical triangulation. Sources of data from this study were respondents at the UINSI Samarinda. The results of this study indicate that the internalization of organizational culture at the UINSI Samarinda shows the existence of standard operating procedures, exemplary and motivational as well as advice in the process of implementation. Internalization of organizational culture at Sultan Aji Muhammad Idris Samarinda State Islamic University can be implemented properly by using standard operating procedures as a reference in work, exemplary shown by the leadership as well as motivation and advice from leaders.

Activating ligands of Uncoupling protein 1 identified by rapid membrane protein thermostability shift analysis

ObjectiveUncoupling protein 1 (UCP1) catalyses mitochondrial proton leak in brown adipose tissue to facilitate nutrient oxidation for heat production, and may combat metabolic disease if activated in humans. During the adrenergic stimulation of brown adipocytes, free fatty acids generated from lipolysis activate UCP1 via an unclear interaction. Here, we set out to characterise activator binding to purified UCP1 to clarify the activation process, discern novel activators and the potential to target UCP1. MethodsWe assessed ligand binding to purified UCP1 by protein thermostability shift analysis, which unlike many conventional approaches can inform on the binding of hydrophobic ligands to membrane proteins. A detailed activator interaction analysis and screening approach was carried out, supported by investigations of UCP1 activity in liposomes, isolated brown fat mitochondria and UCP1 expression-controlled cell lines. ResultsWe reveal that fatty acids and other activators influence UCP1 through a specific destabilising interaction, behaving as transport substrates that shift the protein to a less stable conformation of a transport cycle. Through the detection of specific stability shifts in screens, we identify novel activators, including the over-the-counter drug ibuprofen, where ligand analysis indicates that UCP1 has a relatively wide structural specificity for interacting molecules. Ibuprofen successfully induced UCP1 activity in liposomes, isolated brown fat mitochondria and UCP1-expressing HEK293 cells but not in cultured brown adipocytes, suggesting drug delivery differs in each cell type. ConclusionsThese findings clarify the nature of the activator-UCP1 interaction and demonstrate that the targeting of UCP1 in cells by approved drugs is in principle achievable as a therapeutic avenue, but requires variants with more effective delivery in brown adipocytes.

A tree-based gene-environment interaction analysis with rare features.

Gene-environment (G-E) interaction analysis plays a critical role in understanding and modeling complex diseases. Compared to main-effect-only analysis, it is more seriously challenged by higher dimensionality, weaker signals, and the unique "main effects, interactions" variable selection hierarchy. In joint G-E interaction analysis under which a large number of G factors are analysed in a single model, effort tailored to rare features (e.g., SNPs with low minor allele frequencies) has been limited. Existing investigations on rare features have been mostly focused on marginal analysis, where various data aggregation techniques have been developed, and hypothesis testings have been conducted to identify significant aggregated features. However, such techniques cannot be extended to joint G-E interaction analysis. In this study, building on a very recent tree-based data aggregation technique, which has been developed for main-effect-only analysis, we develop a new G-E interaction analysis approach tailored to rare features. The adopted data aggregation technique allows for more efficient information borrowing from neighboring rare features. Similar to some existing state-of-the-art ones, the proposed approach adopts penalization for variable selection, regularized estimation, and respect of the variable selection hierarchy. Simulation shows that it has more accurate identification of important interactions and main effects than several competing alternatives. In the analysis of NFBC1966 study, the proposed approach leads to findings different from the alternatives and with satisfactory prediction and stability performance.

Interactive Visual Cluster Analysis by Contrastive Dimensionality Reduction.

We propose a contrastive dimensionality reduction approach (CDR) for interactive visual cluster analysis. Although dimensionality reduction of high-dimensional data is widely used in visual cluster analysis in conjunction with scatterplots, there are several limitations on effective visual cluster analysis. First, it is non-trivial for an embedding to present clear visual cluster separation when keeping neighborhood structures. Second, as cluster analysis is a subjective task, user steering is required. However, it is also non-trivial to enable interactions in dimensionality reduction. To tackle these problems, we introduce contrastive learning into dimensionality reduction for high-quality embedding. We then redefine the gradient of the loss function to the negative pairs to enhance the visual cluster separation of embedding results. Based on the contrastive learning scheme, we employ link-based interactions to steer embeddings. After that, we implement a prototype visual interface that integrates the proposed algorithms and a set of visualizations. Quantitative experiments demonstrate that CDR outperforms existing techniques in terms of preserving correct neighborhood structures and improving visual cluster separation. The ablation experiment demonstrates the effectiveness of gradient redefinition. The user study verifies that CDR outperforms t-SNE and UMAP in the task of cluster identification. We also showcase two use cases on real-world datasets to present the effectiveness of link-based interactions.

Gene-gene interaction analysis incorporating network information via a structured Bayesian approach.

Increasing evidence has shown that gene-gene interactions have important effects in biological processes of human diseases. Due to the high dimensionality of genetic measurements, interaction analysis usually suffers from a lack of sufficient information and has unsatisfactory results. Biological network information has been massively accumulated, allowing researchers to identify biomarkers while taking a system perspective, conducting network selection (of functionally related biomarkers), and accommodating network structures. In main-effect-only analysis, network information has been incorporated. However, effort has been limited in interaction analysis. Recently, link networks that describe the relationships between genetic interactions have been demonstrated as effective for revealing multiscale hierarchical organizations in networks and providing interesting findings beyond node networks. In this study, we develop a novel structured Bayesian interaction analysis approach to effectively incorporate network information. This study is among the first to identify gene-gene interactions with the assistance of network selection, while simultaneously accommodating the underlying network structures of both main effects and interactions. It innovatively respects multiple hierarchies among main effects, interactions, and networks. The Bayesian technique is adopted, which may be more informative for estimation and prediction over some other techniques. An efficient variational Bayesian expectation-maximization algorithm is developed to explore the posterior distribution. Extensive simulation studies demonstrate the practical superiority of the proposed approach. The analysis of TCGA data on melanoma and lung cancer leads to biologically sensible findings with satisfactory prediction accuracy and selection stability.

Performance-based seismic assessment of shield tunnels by incorporating a nonlinear pseudostatic analysis approach for the soil-tunnel interaction

The purpose of this study is to present an efficient and reasonable methodology to evaluate the seismic fragility of shield tunnels based on investigating the seismic performance of segments and joints in detail. The finite element model of segments and joints is established using appropriate constitutive models and elements. A pseudostatic soil-tunnel interaction analysis approach based on the multimodal adaptive pushover of the 1D free-field model is introduced to improve the computational efficiency. The seismic performances of a shield tunnel, including the plastic strain of the segments, joint deformation and bolt yielding, are investigated by pseudostatic analysis, and the entire failure process is summarized. Therefore, a framework for seismic fragility assessment of shield tunnels is proposed. The scaling approach substituting the pseudostatic soil-tunnel analysis for traditional incremental dynamic analysis is adopted to consider the uncertainty of input motion. A Monte Carlo simulation is carried out to consider the uncertainties of soil and tunnel properties. The damage state levels are divided based on the crucial events during the failure process. Finally, the seismic fragility curves are fitted with normal and log-normal cumulative distribution functions. And the effect of the sampling size is discussed. Moreover, the seismic fragility curves taking PGA as IM are also obtained and compared with the existing seismic fragility curves in previous studies.

Visual analysis of droplet dynamics in large-scale multiphase spray simulations

We present a data-driven visual analysis approach for the in-depth exploration of large numbers of droplets. Understanding droplet dynamics in sprays is of interest across many scientific fields for both simulation scientists and engineers. In this paper, we analyze large-scale direct numerical simulation datasets of the two-phase flow of non-Newtonian jets. Our interactive visual analysis approach comprises various dedicated exploration modalities that are supplemented by directly linking to ParaView. This hybrid setup supports a detailed investigation of droplets, both in the spatial domain and in terms of physical quantities . Considering a large variety of extracted physical quantities for each droplet enables investigating different aspects of interest in our data. To get an overview of different types of characteristic behaviors, we cluster massive numbers of droplets to analyze different types of occurring behaviors via domain-specific pre-aggregation, as well as different methods and parameters. Extraordinary temporal patterns are of high interest, especially to investigate edge cases and detect potential simulation issues. For this, we use a neural network-based approach to predict the development of these physical quantities and identify irregularly advected droplets.Graphic