scholarly journals Classification of BOF Slag by Data Mining Techniques According to Chemical Composition

2020 ◽  
Vol 12 (8) ◽  
pp. 3301
Author(s):  
Sara M. Andrés-Vizán ◽  
Joaquín M. Villanueva-Balsera ◽  
J. Valeriano Álvarez-Cabal ◽  
Gemma M. Martínez-Huerta
Keyword(s):  
Data Mining ◽  
Environmental Impact ◽  
Basic Oxygen Furnace ◽  
Added Value ◽  
Data Mining Techniques ◽  
Different Types ◽  
Potential Applications ◽  
Bof Slag ◽  
Slag Valorization

In the process of converting pig iron into steel, some co-products are generated—among which, basic oxygen furnace (BOF) slag is highlighted due to the great amount generated (about 126 kg of BOF slag per ton of steel grade). Great efforts have been made throughout the years toward finding an application to minimize the environmental impact and to increase sustainability while generating added value. Finding BOF slag valorization is difficult due to its heterogeneity, strength, and overall swallowing, which prevents its use in civil engineering projects. This work is focused on trying to resolve the heterogeneity issue. If many different types of steel are manufactured, then different types of slag could also be generated, and for each type of BOF slag, there is an adequate valorization option. Not all of the slag can be valorized, but it can be a tool for reducing the amount that must go to landfill and to minimize the environmental impact. An analysis by means of data mining techniques allows a classification of BOF slag to be obtained, and each one of these types has a better adjustment to certain valorization alternatives. In the plant used as an example of the application of these studies, eight different slag clusters were obtained, which were then linked to their different potential applications with the aim of increasing the amount valorized.

How Sweet and Ripe are the Fruits? Data Mining Techniques for Classifying and Predicting ‘Quick-Wins’ Direct Capital Investment in Indonesia as One Approach to Business intelligence Orientation and Knowledge Management Scenarios of Indonesian Enterprises

2019 ◽  
Vol 1 (1) ◽  
pp. 121-131
Author(s):  
Ali Fauzi
Keyword(s):  
Data Mining ◽  
Business Intelligence ◽  
Direct Investment ◽  
Capital Investment ◽  
Export Market ◽  
Added Value ◽  
Knowledge Generation ◽  
Management Scenarios ◽  
Data Mining Techniques ◽  
Knowledge Based Economy

The existence of big data of Indonesian FDI (foreign direct investment)/ CDI (capital direct investment) has not been exploited somehow to give further ideas and decision making basis. Example of data exploitation by data mining techniques are for clustering/labeling using K-Mean and classification/prediction using Naïve Bayesian of such DCI categories. One of DCI form is the ‘Quick-Wins’, a.k.a. ‘Low-Hanging-Fruits’ Direct Capital Investment (DCI), or named shortly as QWDI. Despite its mentioned unfavorable factors, i.e. exploitation of natural resources, low added-value creation, low skill-low wages employment, environmental impacts, etc., QWDI , to have great contribution for quick and high job creation, export market penetration and advancement of technology potential. By using some basic data mining techniques as complements to usual statistical/query analysis, or analysis by similar studies or researches, this study has been intended to enable government planners, starting-up companies or financial institutions for further CDI development. The idea of business intelligence orientation and knowledge generation scenarios is also one of precious basis. At its turn, Information and Communication Technology (ICT)’s enablement will have strategic role for Indonesian enterprises growth and as a fundamental for ‘knowledge based economy’ in Indonesia.

scholarly journals Time-Dependent Strength Behavior, Expansion, Microstructural Properties, and Environmental Impact of Basic Oxygen Furnace Slag-Treated Marine-Dredged Clay in South Korea

2021 ◽  
Vol 13 (9) ◽  
pp. 5026
Author(s):  
Gyeong-o Kang ◽  
Jung-goo Kang ◽  
Jin-young Kim ◽  
Young-sang Kim
Keyword(s):  
Particle Size ◽  
Environmental Impact ◽  
South Korea ◽  
Mechanical Characteristics ◽  
Basic Oxygen Furnace ◽  
Microstructural Properties ◽  
Compression Tests ◽  
Basic Oxygen ◽  
Strength Behavior ◽  
Bof Slag

The aim of this study was to investigate the mechanical characteristics, microstructural properties, and environmental impact of basic oxygen furnace (BOF) slag-treated clay in South Korea. Mechanical characteristics were determined via the expansion, vane shear, and unconfined compression tests according to various curing times. Scanning electron microscopy was conducted to analyze microstructural properties. Furthermore, environmental impacts were evaluated by the leaching test and pH measurements. According to the results, at the early curing stage (within 15 h), the free lime (F-CaO) content of the BOF slag is a significant factor for developing the strength of the adopted sample. However, the particle size of the BOF slag influences the increase in the strength at subsequent curing times. It was inferred that the strength behavior of the sample exhibits three phases depending on various incremental strength ratios. The expansion magnitude of the adopted samples is influenced by the F-CaO content and also the particle size of the BOF slag. Regarding the microstructural properties, the presence of reticulation structures in the amorphous gels with intergrowths of rod-like ettringite formation was verified inside the sample. Finally, the pH values and heavy metal leachates of the samples were determined within the compatible ranges of the threshold effect levels in the marine sediments of the marine environment standard of the Republic of Korea.

Classification of Intrusion Detection Using Data Mining Techniques

2018 ◽  
pp. 753-764 ◽  
Author(s):  
Roma Sahani ◽  
Shatabdinalini ◽  
Chinmayee Rout ◽  
J. Chandrakanta Badajena ◽  
Ajay Kumar Jena ◽  
...  
Keyword(s):  
Data Mining ◽  
Intrusion Detection ◽  
Data Mining Techniques ◽  
Using Data

Classification of Product Rating Using Data Mining Techniques

2017 ◽  
pp. 27-36 ◽  
Author(s):  
Pinku Deb Nath ◽  
Sowvik Kanti Das ◽  
Fabiha Nazmi Islam ◽  
Kifayat Tahmid ◽  
Raufir Ahmed Shanto ◽  
...  
Keyword(s):  
Data Mining ◽  
Data Mining Techniques ◽  
Using Data ◽  
Product Rating

scholarly journals Application of Data Mining Techniques for Medical Data Classification: A Review

2018 ◽  
Vol 150 ◽  
pp. 06003 ◽  
Author(s):  
Saima Anwar Lashari ◽  
Rosziati Ibrahim ◽  
Norhalina Senan ◽  
N. S. A. M. Taujuddin
Keyword(s):  
Data Mining ◽  
Data Classification ◽  
Past Research ◽  
Medical Data ◽  
Extensive Literature ◽  
Literature Analysis ◽  
Data Mining Techniques ◽  
Medical Data Classification ◽  
Using Data

This paper investigates the existing practices and prospects of medical data classification based on data mining techniques. It highlights major advanced classification approaches used to enhance classification accuracy. Past research has provided literature on medical data classification using data mining techniques. From extensive literature analysis, it is found that data mining techniques are very effective for the task of classification. This paper analysed comparatively the current advancement in the classification of medical data. The findings of the study showed that the existing classification of medical data can be improved further. Nonetheless, there should be more research to ascertain and lessen the ambiguities for classification to gain better precision.

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