Article
Environmental Sciences
Rafael Borge, Daeun Jung, Iciar Lejarraga, David de la Paz, Jose Maria Cordero
Summary: According to the European Air Quality Directive, Madrid has revised its air quality zones using a new methodology based on statistical data and cluster analysis, proposing a new zoning scheme that is verified to be suitable.
ATMOSPHERIC ENVIRONMENT
(2022)
Article
Computer Science, Artificial Intelligence
Mi Li, Eibe Frank, Bernhard Pfahringer
Summary: The paper presents a fast and memory-efficient GPU-based algorithm called ASB k-means for exact k-means clustering. The algorithm can handle large datasets that exceed the GPU memory size, and it outperforms the standard GPU-based k-means implementation in terms of speed and performance.
DATA MINING AND KNOWLEDGE DISCOVERY
(2023)
Article
Computer Science, Hardware & Architecture
Ramzi A. A. Haraty, Ali Assaf
Summary: Clustering is the process of dividing objects into classes based on their similarities. Traditional centralized algorithms cannot handle distributed objects, but distributed clustering algorithms can extract a classification model from objects distributed across different locations. With the increasing storage of data in various sites and the large amount of data on the web, distributed clustering is becoming a prominent field. Despite the challenges such as limited bandwidth and data transfer issues, the DG-means algorithm shows superior performance compared to other algorithms when evaluated on different metrics like runtime, stability, and accuracy.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Merhad Ay, Lale Ozbakir, Sinem Kulluk, Burak Guelmez, Gueney Oztuerk, Sertay Ozer
Summary: Clustering is a data mining method that divides large-sized data into subgroups based on similarities. The FC-Kmeans algorithm, proposed in this paper, allows clustering by fixing some cluster centers while considering real conditions. Experimental results show that although the FC-Kmeans algorithm has more limitations, it performs similarly to the K-means algorithm in terms of performance indicators.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Environmental Sciences
Nelson Gouveia, Josiah L. Kephart, Iryna Dronova, Leslie McClure, Jose Tapia Granados, Ricardo Morales Betancourt, Andrea Cortinez O'Ryan, Jose Luis Texcalac-Sangrador, Kevin Martinez-Folgar, Daniel Rodriguez, Ana Diez-Roux
Summary: The study found that a significant proportion of the population in Latin American cities live in areas with air pollution levels above WHO standards. Larger cities, higher GDP, higher motorization rate, and congestion tend to have higher PM2.5 levels. On the other hand, areas with higher population density tend to have lower levels of PM2.5.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Environmental Sciences
Jennifer L. Ish, Mustapha Abubakar, Shaoqi Fan, Rena R. Jones, Nicole M. Niehoff, Jill E. Henry, Gretchen L. Gierach, Alexandra J. White
Summary: Using machine-learning algorithms, this study found an association between fine particulate matter (PM2.5) and the histologic composition of normal breast tissue. The findings suggest a possible role of PM2.5 in breast cancer etiology and indicate that changes in breast tissue composition may be a potential pathway by which outdoor air pollution impacts breast cancer risk.
ENVIRONMENT INTERNATIONAL
(2023)
Article
Computer Science, Information Systems
Omer N. Kenger, Zulal Diri Kenger, Eren Ozceylan, Beata Mrugalska
Summary: Smart cities are seen as a potential solution to urban problems, and it is important to evaluate their effectiveness. This study uses clustering algorithms to categorize smart cities, and the results suggest that this method is more effective than grouping cities based on indicators.
Article
Environmental Sciences
Kohei Hasegawa, Teruomi Tsukahara, Tetsuo Nomiyama
Summary: There is limited research on the relationship between low levels of daily fine particulate matter (PM2.5) exposure and morbidity or mortality in non-western countries, especially at PM2.5 concentrations below 15 μg/m3, the latest WHO AQG value. This study in Japan found that even at low concentrations, an increase in PM2.5 was associated with an increase in cardiorespiratory hospital admissions. The findings suggest that the current WHO guideline value may be insufficient for protecting public health.
ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY
(2023)
Article
Engineering, Environmental
Yuxin Huang, Shenpeng Wu, Huihuan Luo, Ying Yang, Jihong Xu, Ya Zhang, Qiaomei Wang, Haiping Shen, Yiping Zhang, Donghai Yan, Lifang Jiang, Hongping Zhang, Renjie Chen, Haidong Kan, Jing Cai, Yuan He, Xu Ma
Summary: Prenatal exposure to PM2.5, especially its fuel combustion-related components, is associated with increased risk of macrosomia. This study collected birth records from mainland China and used satellite-based models to estimate concentrations of PM2.5 and its chemical components during pregnancy. The findings show that higher levels of PM2.5 and its components, particularly NO3(-), OC, NH4(+), and BC, are associated with increased risk of macrosomia. Certain subgroups, including boys and women with lower body mass index or irregular folic acid supplementation, are more susceptible to the adverse effects.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Carlo Baldassi
Summary: We introduce an evolutionary algorithm called recombinator-k-means for optimizing the highly nonconvex kmeans problem. Its defining feature is that its crossover step involves all the members of the current generation, stochastically recombining them with a repurposed variant of the k-means++ seeding algorithm. The recombination also uses a reweighting mechanism that realizes a progressively sharper stochastic selection policy and ensures that the population eventually coalesces into a single solution. We compare this scheme with a state-of-the-art alternative, a more standard genetic algorithm with deterministic pairwise-nearest-neighbor crossover and an elitist selection policy, of which we also provide an augmented and efficient implementation. Extensive tests on large and challenging datasets (both synthetic and real word) show that for fixed population sizes recombinator-k-means is generally superior in terms of the optimization objective, at the cost of a more expensive crossover step. When adjusting the population sizes of the two algorithms to match their running times, we find that for short times the (augmented) pairwise-nearest-neighbor method is always superior, while at longer times recombinator-k-means will match it and, on the most difficult examples, take over. We conclude that the reweighted whole-population recombination is more costly but generally better at escaping local minima Moreover, it is algorithmically simpler and more general (it could be applied even to k-medians or k-medoids, for example).
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2022)
Article
Computer Science, Artificial Intelligence
Yi-Cheng Chen, Yen-Liang Chen, Jyun-Yun Lu
Summary: K-Means algorithm is one of the most famous and popular clustering algorithms in the world, known for its simple structure, easy implementation, high efficiency, and fast convergence speed. This article introduces an improvement to past variants of K-Means used in evolutionary clustering, considering both past and future clustering results, and extending K-Means to multiple cycles, resulting in more consistent, stable, and smooth clustering results.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Sami Sieranoja, Pasi Franti
Summary: We propose two new algorithms for clustering graphs and networks: the K-algorithm, derived from the k-means algorithm, and the M-algorithm, which outperforms eight other state-of-the-art methods. A case study analyzing disease co-occurrence network clustering results demonstrates the algorithms' usefulness in important real-life applications.
KNOWLEDGE AND INFORMATION SYSTEMS
(2022)
Article
Automation & Control Systems
Uri Stemmer
Summary: This research presents a new algorithm operating in the local model of differential privacy for solving the Euclidean k-means problem, significantly reducing additive error while maintaining multiplicative error. The study shows that the obtained additive error in handling the k-means objective is almost optimal in terms of its dependency on the database size.
JOURNAL OF MACHINE LEARNING RESEARCH
(2021)
Article
Chemistry, Multidisciplinary
Yushan Su, Uwayemi Sofowote, Anthony Munoz, Michael Noble, Chris Charron, Aaron Todd, Valbona Celo, Ewa Dabek-Zlotorzynska, Alla Kryukova, Teresa Switzer
Summary: The study examined the impact of potential mining activities on air quality in Ontario's Far North. Analysis of monitoring data on particulate matter and trace elements showed minimal influence of primary emissions in the study area, with air quality meeting Ontario's environmental standards.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Interdisciplinary Applications
Ahmed Fahim
Summary: The k-means method divides N objects into k clusters based on mean values, with linear time complexity and dependence on knowing the number of clusters and initial centers. This research introduces a method able to detect near-optimal values for k and initial centers without prior knowledge, resulting in improved final result quality. The proposed method combines DBSCAN and k-means to converge to global minima and has a time complexity of o(n log n).
JOURNAL OF COMPUTATIONAL SCIENCE
(2021)
Article
Chemistry, Physical
Laura Proano, Edisson Tello, Martha A. Arellano-Trevino, Shuoxun Wang, Robert J. Farrauto, Martha Cobo
APPLIED SURFACE SCIENCE
(2019)
Article
Engineering, Environmental
Nestor Sanchez, Ruth Y. Ruiz, Bernay Cifuentes, Martha Cobo
Article
Chemistry, Physical
Bernay Cifuentes, Felipe Bustamante, Martha Cobo
Article
Chemistry, Physical
Bernay Cifuentes, Felipe Bustamante, Daniel G. Araiza, Gabriela Diaz, Martha Cobo
APPLIED CATALYSIS A-GENERAL
(2020)
Review
Chemistry, Physical
Nestor Sanchez, Ruth Ruiz, Viktor Hacker, Martha Cobo
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2020)
Article
Chemistry, Physical
Eliana Quiroga, Julia Molto, Juan A. Conesa, Manuel F. Valero, Martha Cobo
Article
Chemistry, Multidisciplinary
Nahury Castellanos-Blanco, Gonzalo Taborda, Martha Cobo
Article
Green & Sustainable Science & Technology
Laura Proano, Alfonso T. Sarmiento, Manuel Figueredo, Martha Cobo
JOURNAL OF CLEANER PRODUCTION
(2020)
Article
Biotechnology & Applied Microbiology
Nestor Sanchez, Ruth Ruiz, Andrea Plazas, Juliana Vasquez, Martha Cobo
BIOCHEMICAL ENGINEERING JOURNAL
(2020)
Article
Chemistry, Physical
Bernay Cifuentes, Alejandro Cifuentes, Felipe Bustamante, Lluis Soler, Jordi Llorca, Martha Cobo
Summary: CO removal from syngas was evaluated using structured AuCu/CeO2-SiO2 catalysts in a single catalytic unit. Addition of SiO2 into AuCu/CeO2 increased surface area and reduced cost, but decreased CO conversion. Washcoated AuCu/CeO2-SiO2 catalyst on monolith outperformed powder samples at temperatures above 260°C, showing potential for economic H-2 cleanup processes.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2021)
Article
Green & Sustainable Science & Technology
Nestor Sanchez, Ruth Ruiz, Anne Roedl, Martha Cobo
Summary: The study demonstrates the effective use of sugarcane press-mud as feedstock to produce power in a fuel cell using hydrogen, achieving efficient energy utilization and environmental benefits. Through life cycle assessment, the technology showed high energy efficiency, renewability, and low carbon footprint, contributing positively to the environment.
Article
Energy & Fuels
Nestor Sanchez, David Rodriguez-Fontalvo, Bernay Cifuentes, Nelly M. Cantillo, Miguel Angel Uribe Laverde, Martha Cobo
Summary: The steam-to-ethanol molar ratio (S/E) used in Ethanol Steam Reforming (ESR) has the strongest influence on power production, process efficiency, and energy consumption, followed by other variables such as the inlet ethanol concentration and the ESR temperature. Although the CO-removal reactor does not significantly affect power production, it is crucial for increasing the voltage on the fuel cell and consequently power production. Optimization through response surface methodology (RSM) showed a maximum power of 0.07 kWh kg(-1) of bioethanol with an efficiency of 17% at an ESR temperature of 700 degrees C.
Article
Green & Sustainable Science & Technology
Sara Dominguez, Bernay Cifuentes, Felipe Bustamante, Nelly M. Cantillo, Cesar L. Barraza-Botet, Martha Cobo
Summary: This article discusses the potential role of blue hydrogen production in Colombia as part of its energy transition. While coal could be used as a feedstock for low-emission blue hydrogen production, capture capacities of carbon dioxide and investment costs could limit the potential. Additional studies on carbon capture, utilization, and storage capacity, clear public policy implementation, and a more detailed hydrogen strategy are needed to establish a low-emission hydrogen economy in the country.
Article
Multidisciplinary Sciences
Cristhian Canon, Nestor Sanchez, Martha Cobo
Summary: This data article presents the methodology and data collection process for the Life Cycle Assessment (LCA) of ethyl levulinate (EL) production from Colombian rice straw. It provides meaningful inventories and foreground data for future environmental assessments of sustainable production processes using rice straw as a raw material or biorefinery processes.
Article
Multidisciplinary Sciences
Santiago Ortiz-Laverde, Camilo Rengifo, Martha Cobo, Manuel Figueredo
Summary: This contribution introduces an open-source computational toolbox, consisting of FEniCS and complementary packages, to the field of chemical and process engineering. Two case studies are presented, highlighting the methodology's validity and consistency in solving mathematical models related to chemical reaction engineering. The results of the oxidation reaction and CO2 methanation reaction demonstrate good agreement between FEniCS and complementary packages.
Article
Environmental Sciences
Youjung Jang, Hyejung Hu, Bomi Kim, Younha Kim, Seung-Jick Yoo, Kyungae Jang, Yoon-Kwan Kim, Hyungah Jin, Jung-Hun Woo
Summary: This study quantitatively analyzed the effects of climate and air pollutant reduction policies in Korea, demonstrating that these policies can lead to reductions in greenhouse gas emissions and atmospheric pollutants. The integrated model used in the study provides advantages for evaluating climate and air quality policies, and the findings offer valuable insights and data for policy development and assessment.
ATMOSPHERIC POLLUTION RESEARCH
(2024)
Article
Environmental Sciences
Giuseppe Piras, Fabrizio Pini, Paolo Di Girolamo
Summary: This study assesses the contribution of tires to atmospheric PM10 pollution and finds that tire emissions of PM10 are larger than those from exhaust gases. It suggests the need for specific strategies to reduce tire emissions, such as producing lighter vehicles, using narrower wheels, and promoting public transportation.
ATMOSPHERIC POLLUTION RESEARCH
(2024)
Article
Environmental Sciences
Laura Vallecillos, Rosa Maria Marce, Francesc Borrull
Summary: This study focuses on the implementation of a gas chromatograph-photoionization detection (GC-PID) analyzer for the continuous monitoring of 1,3-butadiene (1,3-BD) levels in urban and industrial atmospheres. The study found that the concentrations of 1,3-BD recorded by the GC-PID analyzer were comparable to those obtained by active sampling, and the concentration peaks showed consistency in values and time slots. In the test of urban atmospheres, the results showed that the concentrations of 1,3-BD were related to prevailing wind direction and activities in the petrochemical zone, while other factors had minor effects on the distribution of this pollutant.
ATMOSPHERIC POLLUTION RESEARCH
(2024)
Article
Environmental Sciences
Ajay Kumar, Arun K. Attri
Summary: This study investigated the temporal profile and composition of PM10 over a 14-month period, and found significant variations between different seasons. The highest concentrations of PM10 were observed in summer and winter, exceeding the national limits. Water-soluble ionic species and n-alkanes contributed to the PM10 mass, with the highest concentration in winter and the lowest in the monsoon season. The ion balance study revealed a strong correlation between anion and cation charge equivalents, indicating their main contribution to PM10. The main sources of PM10 components were identified using statistical correlation, regression, and principal component analysis.
ATMOSPHERIC POLLUTION RESEARCH
(2024)
Article
Environmental Sciences
Jenny Martinez, Yris Olaya Morales, Prashant Kumar
Summary: The impact of bicycle lane designs on cyclist exposure to air pollution is a significant concern. This study found that in the city of Medellin, Colombia, the sections without dedicated bicycle lanes had the highest PM2.5 exposure and inhaled dose. Cyclists had higher PM2.5 exposure and inhaled dose during morning peak hours compared to evening peak and off-peak hours. Segregated cycling lanes on the sidewalk can considerably lower PM2.5 exposure and inhaled doses for cyclists.
ATMOSPHERIC POLLUTION RESEARCH
(2024)
Article
Environmental Sciences
Ying Xu, Qingyang Liu, James J. Schauer
Summary: In this study, a quantitative method using dual-wavelength ultraviolet-visible spectroscopy and Raman spectroscopy was developed to analyze carbon black with amorphous structures and ordering in a graphene sheet. Water extracts of carbon black showed high oxidative potential, and the presence of water-soluble ions enhanced its oxidative potential. These findings can help mitigate health risks associated with nano-carbon black emissions.
ATMOSPHERIC POLLUTION RESEARCH
(2024)
Article
Environmental Sciences
Zhongmin Zhu, Hui Li, Shumin Fan, Wenfa Xu, Ruimin Fang, Boming Liu, Wei Gong
Summary: This study investigates the relationship between temperature inversions (TI) and aerosol vertical distribution in China. The results show that TI frequency, inversion strength (Delta T), and TI height (TIH) exhibit similar seasonal patterns across different regions in China. NC has a significantly higher TI frequency during summer, possibly due to the heating effect of black carbon aerosol. Aerosol optical depth (AOD) above the TIH is higher in spring and summer, indicating the presence of aerosol high-level transport over mainland China during these seasons. The study also finds that a strong inversion can suppress surface aerosols below the TI, but in regions with strong atmospheric stability, aerosols tend to accumulate above the TIH. These findings are valuable for understanding aerosol transport.
ATMOSPHERIC POLLUTION RESEARCH
(2024)