Analytics Pub Date : 2024-07-15 DOI: 10.3390/analytics3030017

Hikmat Al-Quhfa, Ali Mothana, Abdussalam Aljbri, Jie Song

{"title":"Enhancing Talent Recruitment in Business Intelligence Systems: A Comparative Analysis of Machine Learning Models","authors":"Hikmat Al-Quhfa, Ali Mothana, Abdussalam Aljbri, Jie Song","doi":"10.3390/analytics3030017","DOIUrl":"https://doi.org/10.3390/analytics3030017","url":null,"abstract":"In the competitive field of business intelligence, optimizing talent recruitment through data-driven methodologies is crucial for better decision-making. This study compares the effectiveness of various machine learning models to improve recruitment accuracy and efficiency. Using the recruitment data from a major Yemeni organization (2019–2022), we evaluated models including K-Nearest Neighbors, Logistic Regression, Support Vector Machine, Naive Bayes, Decision Trees, Random Forest, Gradient Boosting Classifier, AdaBoost Classifier, and Neural Networks. Hyperparameter tuning and cross-validation were used for optimization. The Random Forest model achieved the highest accuracy (92.8%), followed by Neural Networks (92.6%) and Gradient Boosting Classifier (92.5%). These results suggest that advanced machine learning models, particularly Random Forest and Neural Networks, can significantly enhance the recruitment processes in business intelligence systems. This study provides valuable insights for recruiters, advocating for the integration of sophisticated machine learning techniques in talent acquisition strategies.","PeriodicalId":512104,"journal":{"name":"Analytics","volume":"56 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141644478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling Sea Level Rise Using Ensemble Techniques: Impacts on Coastal Adaptation, Freshwater Ecosystems, Agriculture and Infrastructure 利用集合技术模拟海平面上升：对沿海适应、淡水生态系统、农业和基础设施的影响

Analytics Pub Date : 2024-07-05 DOI: 10.3390/analytics3030016

S. Dhal, Rishabh Singh, Tushar Pandey, Sheelabhadra Dey, Stavros Kalafatis, Vivekvardhan Kesireddy

{"title":"Modeling Sea Level Rise Using Ensemble Techniques: Impacts on Coastal Adaptation, Freshwater Ecosystems, Agriculture and Infrastructure","authors":"S. Dhal, Rishabh Singh, Tushar Pandey, Sheelabhadra Dey, Stavros Kalafatis, Vivekvardhan Kesireddy","doi":"10.3390/analytics3030016","DOIUrl":"https://doi.org/10.3390/analytics3030016","url":null,"abstract":"Sea level rise (SLR) is a crucial indicator of climate change, primarily driven by greenhouse gas emissions and the subsequent increase in global temperatures. The impact of SLR, however, varies regionally due to factors such as ocean bathymetry, resulting in distinct shifts across different areas compared to the global average. Understanding the complex factors influencing SLR across diverse spatial scales, along with the associated uncertainties, is essential. This study focuses on the East Coast of the United States and Gulf of Mexico, utilizing historical SLR data from 1993 to 2023. To forecast SLR trends from 2024 to 2103, a weighted ensemble model comprising SARIMAX, LSTM, and exponential smoothing models was employed. Additionally, using historical greenhouse gas data, an ensemble of LSTM models was used to predict real-time SLR values, achieving a testing loss of 0.005. Furthermore, conductance and dissolved oxygen (DO) values were assessed for the entire forecasting period, leveraging forecasted SLR trends to evaluate the impacts on marine life, agriculture, and infrastructure.","PeriodicalId":512104,"journal":{"name":"Analytics","volume":" 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141676008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

TaskFinder: A Semantics-Based Methodology for Visualization Task Recommendation 任务搜索器：基于语义的可视化任务推荐方法

Analytics Pub Date : 2024-07-04 DOI: 10.3390/analytics3030015

Darius Coelho, Bhavya Ghai, Arjun Krishna, Maria C. Velez-Rojas, Steve Greenspan, Serge Mankovski, Klaus Mueller

{"title":"TaskFinder: A Semantics-Based Methodology for Visualization Task Recommendation","authors":"Darius Coelho, Bhavya Ghai, Arjun Krishna, Maria C. Velez-Rojas, Steve Greenspan, Serge Mankovski, Klaus Mueller","doi":"10.3390/analytics3030015","DOIUrl":"https://doi.org/10.3390/analytics3030015","url":null,"abstract":"Data visualization has entered the mainstream, and numerous visualization recommender systems have been proposed to assist visualization novices, as well as busy professionals, in selecting the most appropriate type of chart for their data. Given a dataset and a set of user-defined analytical tasks, these systems can make recommendations based on expert coded visualization design principles or empirical models. However, the need to identify the pertinent analytical tasks beforehand still exists and often requires domain expertise. In this work, we aim to automate this step with TaskFinder, a prototype system that leverages the information available in textual documents to understand domain-specific relations between attributes and tasks. TaskFinder employs word vectors as well as a custom dependency parser along with an expert-defined list of task keywords to extract and rank associations between tasks and attributes. It pairs these associations with a statistical analysis of the dataset to filter out tasks irrelevant given the data. TaskFinder ultimately produces a ranked list of attribute–task pairs. We show that the number of domain articles needed to converge to a recommendation consensus is bounded for our approach. We demonstrate our TaskFinder over multiple domains with varying article types and quantities.","PeriodicalId":512104,"journal":{"name":"Analytics","volume":" 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141678067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving the Giant-Armadillo Optimization Method 改进巨人-阿玛迪略优化方法

Analytics Pub Date : 2024-06-10 DOI: 10.3390/analytics3020013

Glykeria Kyrou, Vasileios Charilogis, Ioannis G. Tsoulos

引用次数: 0

Interconnected Markets: Unveiling Volatility Spillovers in Commodities and Energy Markets through BEKK-GARCH Modelling 相互关联的市场：通过 BEKK-GARCH 模型揭示商品和能源市场的波动溢出效应

Analytics Pub Date : 2024-04-16 DOI: 10.3390/analytics3020011

Tetiana Paientko, Stanley Amakude

{"title":"Interconnected Markets: Unveiling Volatility Spillovers in Commodities and Energy Markets through BEKK-GARCH Modelling","authors":"Tetiana Paientko, Stanley Amakude","doi":"10.3390/analytics3020011","DOIUrl":"https://doi.org/10.3390/analytics3020011","url":null,"abstract":"Food commodities and energy bills have experienced rapid undulating movements and hikes globally in recent times. This spurred this study to examine the possibility that the shocks that arise from fluctuations of one market spill over to the other and to determine how time-varying the spillovers were across a time. Data were daily frequency (prices of grains and energy products) from 1 July 2019 to 31 December 2022, as quoted in markets. The choice of the period was to capture the COVID pandemic and the Russian–Ukrainian war as events that could impact volatility. The returns were duly calculated using spreadsheets and subjected to ADF stationarity, co-integration, and the full BEKK-GARCH estimation. The results revealed a prolonged association between returns in the energy markets and food commodity market returns. Both markets were found to have volatility persistence individually, and time-varying bidirectional transmission of volatility across the markets was found. No lagged-effects spillover was found from one market to the other. The findings confirm that shocks that emanate from fluctuations in energy markets are impactful on the volatility of prices in food commodity markets and vice versa, but this impact occurs immediately after the shocks arise or on the same day such variation occurs.","PeriodicalId":512104,"journal":{"name":"Analytics","volume":"6 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140697819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Learner Engagement and Demographic Influences in Brazilian Massive Open Online Courses: Aprenda Mais Platform Case Study 巴西大规模开放在线课程中的学习者参与度和人口统计学影响因素：Aprenda Mais 平台案例研究

Analytics Pub Date : 2024-04-03 DOI: 10.3390/analytics3020010

Júlia Marques Carvalho da Silva, Gabriela Hahn Pedroso, Augusto Basso Veber, Úrsula Gomes Rosa Maruyama

{"title":"Learner Engagement and Demographic Influences in Brazilian Massive Open Online Courses: Aprenda Mais Platform Case Study","authors":"Júlia Marques Carvalho da Silva, Gabriela Hahn Pedroso, Augusto Basso Veber, Úrsula Gomes Rosa Maruyama","doi":"10.3390/analytics3020010","DOIUrl":"https://doi.org/10.3390/analytics3020010","url":null,"abstract":"This paper explores the dynamics of student engagement and demographic influences in Massive Open Online Courses (MOOCs). The study analyzes multiple facets of Brazilian MOOC participation, including re-enrollment patterns, course completion rates, and the impact of demographic characteristics on learning outcomes. Using survey data and statistical analyses from the public Aprenda Mais Platform, this study reveals that MOOC learners exhibit a strong tendency toward continuous learning, with a majority re-enrolling in subsequent courses within a short timeframe. The average completion rate across courses is around 42.14%, with learners maintaining consistent academic performance. Demographic factors, notably, race/color and disability, are found to influence enrollment and completion rates, underscoring the importance of inclusive educational practices. Geographical location impacts students’ decision to enroll in and complete courses, highlighting the necessity for region-specific educational strategies. The research concludes that a diverse array of factors, including content interest, personal motivation, and demographic attributes, shape student engagement in MOOCs. These insights are vital for educators and course designers in creating effective, inclusive, and engaging online learning experiences.","PeriodicalId":512104,"journal":{"name":"Analytics","volume":"459 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140749964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal Matching with Matching Priority 具有匹配优先权的最优匹配

Analytics Pub Date : 2024-03-19 DOI: 10.3390/analytics3010009

M. Cannas, E. Sironi

{"title":"Optimal Matching with Matching Priority","authors":"M. Cannas, E. Sironi","doi":"10.3390/analytics3010009","DOIUrl":"https://doi.org/10.3390/analytics3010009","url":null,"abstract":"Matching algorithms are commonly used to build comparable subsets (matchings) in observational studies. When a complete matching is not possible, some units must necessarily be excluded from the final matching. This may bias the final estimates comparing the two populations, and thus it is important to reduce the number of drops to avoid unsatisfactory results. Greedy matching algorithms may not reach the maximum matching size, thus dropping more units than necessary. Optimal matching algorithms do ensure a maximum matching size, but they implicitly assume that all units have the same matching priority. In this paper, we propose a matching strategy which is order optimal in the sense that it finds a maximum matching size which is consistent with a given matching priority. The strategy is based on an order-optimal matching algorithm originally proposed in connection with assignment problems by D. Gale. When a matching priority is given, the algorithm ensures that the discarded units have the lowest possible matching priority. We discuss the algorithm’s complexity and its relation with classic optimal matching. We illustrate its use with a problem in a case study concerning a comparison of female and male executives and a simulation.","PeriodicalId":512104,"journal":{"name":"Analytics","volume":"5 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140229433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Artificial Intelligence and Sustainability—A Review 人工智能与可持续性--回顾

Analytics Pub Date : 2024-03-01 DOI: 10.3390/analytics3010008

Rachit Dhiman, Sofia Miteff, Yuancheng Wang, Shih-Chi Ma, Ramila Amirikas, B. Fabian

引用次数: 0

Visual Analytics for Robust Investigations of Placental Aquaporin Gene Expression in Response to Maternal SARS-CoV-2 Infection 利用可视化分析技术对母体感染 SARS-CoV-2 后的胎盘水蒸发蛋白基因表达进行深入研究

Analytics Pub Date : 2024-02-05 DOI: 10.3390/analytics3010007

Raphael D. Isokpehi, Amos O. Abioye, Rickeisha S. Hamilton, Jasmin C. Fryer, A. Hollman, Antoinette M. Destefano, Kehinde B. Ezekiel, Tyrese L. Taylor, Shawna F. Brooks, Matilda O. Johnson, Olubukola Smile, Shirma Ramroop-Butts, Angela U. Makolo, Albert G. Hayward

{"title":"Visual Analytics for Robust Investigations of Placental Aquaporin Gene Expression in Response to Maternal SARS-CoV-2 Infection","authors":"Raphael D. Isokpehi, Amos O. Abioye, Rickeisha S. Hamilton, Jasmin C. Fryer, A. Hollman, Antoinette M. Destefano, Kehinde B. Ezekiel, Tyrese L. Taylor, Shawna F. Brooks, Matilda O. Johnson, Olubukola Smile, Shirma Ramroop-Butts, Angela U. Makolo, Albert G. Hayward","doi":"10.3390/analytics3010007","DOIUrl":"https://doi.org/10.3390/analytics3010007","url":null,"abstract":"The human placenta is a multifunctional, disc-shaped temporary fetal organ that develops in the uterus during pregnancy, connecting the mother and the fetus. The availability of large-scale datasets on the gene expression of placental cell types and scholarly articles documenting adverse pregnancy outcomes from maternal infection warrants the use of computational resources to aid in knowledge generation from disparate data sources. Using maternal Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection as a case study in microbial infection, we constructed integrated datasets and implemented visual analytics resources to facilitate robust investigations of placental gene expression data in the dimensions of flow, curation, and analytics. The visual analytics resources and associated datasets can support a greater understanding of SARS-CoV-2-induced changes to the human placental expression levels of 18,882 protein-coding genes and at least 1233 human gene groups/families. We focus this report on the human aquaporin gene family that encodes small integral membrane proteins initially studied for their roles in water transport across cell membranes. Aquaporin-9 (AQP9) was the only aquaporin downregulated in term placental villi from SARS-CoV-2-positive mothers. Previous studies have found that (1) oxygen signaling modulates placental development; (2) oxygen tension could modulate AQP9 expression in the human placenta; and (3) SARS-CoV-2 can disrupt the formation of oxygen-carrying red blood cells in the placenta. Thus, future research could be performed on microbial infection-induced changes to (1) the placental hematopoietic stem and progenitor cells; and (2) placental expression of human aquaporin genes, especially AQP9.","PeriodicalId":512104,"journal":{"name":"Analytics","volume":"9 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139865481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Visual Analytics for Robust Investigations of Placental Aquaporin Gene Expression in Response to Maternal SARS-CoV-2 Infection 利用可视化分析技术对母体感染 SARS-CoV-2 后的胎盘水蒸发蛋白基因表达进行深入研究

Analytics Pub Date : 2024-02-05 DOI: 10.3390/analytics3010007

Raphael D. Isokpehi, Amos O. Abioye, Rickeisha S. Hamilton, Jasmin C. Fryer, A. Hollman, Antoinette M. Destefano, Kehinde B. Ezekiel, Tyrese L. Taylor, Shawna F. Brooks, Matilda O. Johnson, Olubukola Smile, Shirma Ramroop-Butts, Angela U. Makolo, Albert G. Hayward

{"title":"Visual Analytics for Robust Investigations of Placental Aquaporin Gene Expression in Response to Maternal SARS-CoV-2 Infection","authors":"Raphael D. Isokpehi, Amos O. Abioye, Rickeisha S. Hamilton, Jasmin C. Fryer, A. Hollman, Antoinette M. Destefano, Kehinde B. Ezekiel, Tyrese L. Taylor, Shawna F. Brooks, Matilda O. Johnson, Olubukola Smile, Shirma Ramroop-Butts, Angela U. Makolo, Albert G. Hayward","doi":"10.3390/analytics3010007","DOIUrl":"https://doi.org/10.3390/analytics3010007","url":null,"abstract":"The human placenta is a multifunctional, disc-shaped temporary fetal organ that develops in the uterus during pregnancy, connecting the mother and the fetus. The availability of large-scale datasets on the gene expression of placental cell types and scholarly articles documenting adverse pregnancy outcomes from maternal infection warrants the use of computational resources to aid in knowledge generation from disparate data sources. Using maternal Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection as a case study in microbial infection, we constructed integrated datasets and implemented visual analytics resources to facilitate robust investigations of placental gene expression data in the dimensions of flow, curation, and analytics. The visual analytics resources and associated datasets can support a greater understanding of SARS-CoV-2-induced changes to the human placental expression levels of 18,882 protein-coding genes and at least 1233 human gene groups/families. We focus this report on the human aquaporin gene family that encodes small integral membrane proteins initially studied for their roles in water transport across cell membranes. Aquaporin-9 (AQP9) was the only aquaporin downregulated in term placental villi from SARS-CoV-2-positive mothers. Previous studies have found that (1) oxygen signaling modulates placental development; (2) oxygen tension could modulate AQP9 expression in the human placenta; and (3) SARS-CoV-2 can disrupt the formation of oxygen-carrying red blood cells in the placenta. Thus, future research could be performed on microbial infection-induced changes to (1) the placental hematopoietic stem and progenitor cells; and (2) placental expression of human aquaporin genes, especially AQP9.","PeriodicalId":512104,"journal":{"name":"Analytics","volume":"13 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139805646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

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