Search results for: mining organisation

Authors: Abdelkader T. Ahmed

Abstract:

Phosphate Rocks (PR) are natural sediment rocks. These rocks contain several chemical compositions of heavy metals and radioactive elements. Mining and transportation these rocks beside or through the natural water streams may lead to water contamination. When PR is in contact with water in the field, as a consequence of precipitation events, changes in water table or sinking in water streams, elements such as salts and heavy metals, may be released to the water. In this work, the leaching properties of PR in Nile River water was investigated by experimental lab work. The study focused on evaluating potential environmental impacts of some constituents, including phosphors, cadmium, curium and lead of PR on the water quality of Nile by applying tank leaching tests. In these tests the potential impact of changing conditions, such as phosphate content in PR, liquid to solid ratio (L/S) and pH value, was studied on the long-term release of heavy metals and salts. Experimental results showed that cadmium and lead were released in very low concentrations but curium and phosphors were in high concentrations. Results showed also that the release rate from PR for all constituents was low even in long periods.

Keywords: leaching tests, Nile river, phosphate rocks, water quality

Procedia PDF Downloads 305

Authors: Rizwan Rizwan

Abstract:

This paper provides an overview of Federated Learning (FL) and its application in enhancing data security, privacy, and efficiency. FL utilizes three distinct architectures to ensure privacy is never compromised. It involves training individual edge devices and aggregating their models on a server without sharing raw data. This approach not only provides secure models without data sharing but also offers a highly efficient privacy--preserving solution with improved security and data access. Also we discusses various frameworks used in FL and its integration with machine learning, deep learning, and data mining. In order to address the challenges of multi--party collaborative modeling scenarios, a brief review FL scheme combined with an adaptive gradient descent strategy and differential privacy mechanism. The adaptive learning rate algorithm adjusts the gradient descent process to avoid issues such as model overfitting and fluctuations, thereby enhancing modeling efficiency and performance in multi-party computation scenarios. Additionally, to cater to ultra-large-scale distributed secure computing, the research introduces a differential privacy mechanism that defends against various background knowledge attacks.

Keywords: federated learning, differential privacy, gradient descent strategy, convergence, stability, threats

Procedia PDF Downloads 8

Authors: Mohamed Amine Helali, Walid Oueslati, Ayed Added

Abstract:

Sedimentation rates and total fluxes of heavy metals (Fe, Mn, Pb, Zn and Cu) was measured in three different depths (10m, 20m and 40m) during March and August 2012, offshore of the Mejerda River outlet (Gulf of Tunis, Tunisia). The sedimentation rates are estimated from the fluxes of the suspended particulate matter at 7.32, 5.45 and 4.39 mm y⁻¹ respectively at 10m, 20m and 40m depth. Heavy metals sequestration in sediments was determined by chemical speciation and the total metal contents in each core collected from 10, 20 and 40m depth. Heavy metals intake to the sediment was measured also from the suspended particulate matter, while the fluxes from the sediment to the water column was determined using the benthic chambers technique and from the diffusive fluxes in the pore water. Results shown that iron is the only metal for which the balance transfer between intake/uptake (45 to 117 / 1.8 to 5.8 g m² y⁻¹) and sequestration (277 to 378 g m² y⁻¹) was negative, at the opposite of the Lead which intake fluxes (360 to 480 mg m² y⁻¹) are more than sequestration fluxes (50 to 92 mg m² y⁻¹). The balance transfer is neutral for Mn, Zn, and Cu. These clearly indicate that the contributions of Mejerda have consistently varied over time, probably due to the migration of the River mouth and to the changes in the mining activity in the Mejerda catchment and the recent human activities which affect the delta area.

Keywords: delta, fluxes, heavy metals, sediments, sedimentation rates

Procedia PDF Downloads 192

Authors: Grace Adebo

Abstract:

Rural Farmers-herdsmen conflicts have resulted in a large number of causalities in many parts of Nigeria. Herds of cattle have died, while farmers recorded inestimable losses of their crops and harvests. The overall consequences have impacted negatively on food security across the country. There are divided opinions by scholars, agricultural experts and conflict analysts on the root causes of the conflicts and why traditional institutional interventions are ineffective in resolving the crisis. The study, therefore, aims to investigate the fundamentality of the conflicts’ causes in Southwest Nigeria and the correlates between traditional institutional authorities’ intervention and farmers-herdsmen conflicts in Southwest Nigeria. A structured interview schedule and focus group discussion were employed to elicit information from 180 farmers and 48 herdsmen selected through a multistage sampling procedure from the conflict zones in Southwest Nigeria. Collected data were analyzed using frequency counts, percentages, means and the Relative Importance Index (RII). The study found that climate change effects, farmland encroachment, crop damage, theft, and competition for land and water resources and pollution were the root causes of the violent herders-rural farmer’s clashes. The quest for wealth acquisition by some traditional rulers and some notable individuals in the conflict neighborhoods, occasioned tribal-mix herds possession and, thus undermining local institutional interventions and perverting justice through weak conflict resolution strategies, therefore, fueling further conflicts. Most farmers in the conflict zones have abandoned their farms for fear of death. This coupled with physical, social, economic and psychological consequences have deepened food insecurity and impaired the economic conditions of the herdsmen and the farmers. Currently, there are no mutually established mediation mechanisms as most states are opposed to the enactment of grazing laws to protect territorial encroachments of lands and subsequent multiplication of the herdsmen. It is suggested that government and Non-Governmental Organisation (NGOs) should encourage a functional stakeholder's forum for sustainable conflict resolution and establish a compensation scheme for losses incurred while extension agents are equipped with knowledge on conflict management strategies for peace attainment with the envisioned goal of achieving sustainable livelihoods and food security in Southwest Nigeria.

Keywords: conflict resolution, food security, herdsmen-farmers conflict, sustainable livelihoods, traditional institutions

Procedia PDF Downloads 97

Authors: Emanuel Koseos

Abstract:

Data-Driven Decision Making (DDDM) refers to making decisions that are based on historical data in order to inform practice, develop strategies and implement policies that benefit organizational settings. In educational technology, DDDM facilitates the implementation of differential educational learning approaches such as Educational Data Mining (EDM) and Competency-Based Education (CBE), which commonly target university classrooms. There is a current need for DDDM models applied to middle and secondary schools from a concern for assessing the needs, progress and performance of students and educators with respect to regional standards, policies and evolution of curriculums. To address these concerns, we propose a DDDM reference model developed using educational key process initiatives as inputs to a machine learning framework implemented with statistical software (SAS, R) to provide a best-practices, complex-free and automated approach for educators at their regional level. We assessed the efficiency of the model over a six-year period using data from 45 schools and grades K-12 in the Langley, BC, Canada regional school district. We concluded that the model has wider appeal, such as business learning systems.

Keywords: competency-based learning, data-driven decision making, machine learning, secondary schools

Procedia PDF Downloads 156

Authors: Aya Salama

Abstract:

Digital Twin is an emerging research topic that attracted researchers in the last decade. It is used in many fields, such as smart manufacturing and smart healthcare because it saves time and money. It is usually related to other technologies such as Data Mining, Artificial Intelligence, and Machine Learning. However, Human digital twin (HDT), in specific, is still a novel idea that still needs to prove its feasibility. HDT expands the idea of Digital Twin to human beings, which are living beings and different from the inanimate physical entities. The goal of this research was to create a Human digital twin that is responsible for real-time human replies automation by simulating human behavior. For this reason, clustering, supervised classification, topic extraction, and sentiment analysis were studied in this paper. The feasibility of the HDT for personal replies generation on social messaging applications was proved in this work. The overall accuracy of the proposed approach in this paper was 63% which is a very promising result that can open the way for researchers to expand the idea of HDT. This was achieved by using Random Forest for clustering the question data base and matching new questions. K-nearest neighbor was also applied for sentiment analysis.

Keywords: human digital twin, sentiment analysis, topic extraction, supervised machine learning, unsupervised machine learning, classification, clustering

Procedia PDF Downloads 76

Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

Abstract:

To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: building energy prediction, data mining, demand response, electricity market

Procedia PDF Downloads 297

Authors: Kwang Chun, John Kemeny

Abstract:

Light detection and ranging (LiDAR) has been a prevalent remote-sensing technology applied in the geological fields due to its high precision and ease of use. One of the major applications is to use the detailed geometrical information of underground structures as a basis for the generation of a three-dimensional numerical model that can be used in a geotechnical stability analysis such as FEM or DEM. To date, however, straightforward techniques in reconstructing the numerical model from the scanned data of the underground structures have not been well established or tested. In this paper, we propose a comprehensive approach integrating all the various processes, from LiDAR scanning to finite element numerical analysis. The study focuses on converting LiDAR 3D point clouds of geologic structures containing complex surface geometries into a finite element model. This methodology has been applied to Kartchner Caverns in Arizona, where detailed underground and surface point clouds can be used for the analysis of underground stability. Numerical simulations were performed using the finite element code Abaqus and presented by 3D computing visualization solution, ParaView. The results are useful in studying the stability of all types of underground excavations including underground mining and tunneling.

Keywords: finite element analysis, LiDAR, remote-sensing, scientific visualization, underground stability

Procedia PDF Downloads 150

Authors: Heike Pintor Pirzkall

Abstract:

The positive economic evolution of many countries in the Latin American Continent, mainly in South America, has changed the geopolitical position of the region in the world. It is no longer the Hinterland or backyard of the United States, now it has become the Heartland for Europe and Asia. This position has favored the interest of countries like China or India, who are combining trade agreements with special assistance and aid agreements in many fields like agriculture, alternative energy resources, defense and mining. As many countries in the region are no longer low income countries, a more equal relationship in development aid has been created were the donor and the recipient have become partners and where new actors intervene in a triangular relationship that promotes new alternative aid structures. Triangular co-operation brings together the best of different actors who are providers of development co-operation, partners in SouthSouth co-operation and international organizations. The objective is to share knowledge and implement projects that support the common goal of reducing poverty and promoting development. The intention of this paper is to explain the reasons for Latin America´s “virage” to the east and to give examples of projects and agreements between Latin American countries, China and India which will help to understand the intensification of south-east relations in recent years.

Keywords: development cooperation, China, Latin America, triangular cooperation, natural resources, partnership

Procedia PDF Downloads 366

Authors: Arturo Maldonado

Abstract:

In the iron ore mining industry, the intact strength of rock units is defined using the uniaxial compressive strength (UCS). This parameter is very important for the classification of shale materials, allowing the split between rock and cohesive soils based on the magnitude of UCS. For this research, it is assumed that UCS less than or equal to 1 MPa is representative of soils. Several researchers have anticipated that the magnitude of UCS reduces with weathering progression, also since UCS is a directional property, its magnitude depends upon the rock fabric orientation. Thus, the paper presents how the UCS of shales is affected by both weathering grade and bedding orientation. The mineralogy of shales has been defined using Hyper-spectral and chemical assays to define the mineral constituents of shale and other non-shale materials. Geological classification tools have been used to define distinct lithological types, and in this manner, the author uses mineralogical datasets to recognize and isolate shales from other rock types and develop tertiary plots for fresh and weathered shales. The mineralogical classification of shales has reduced the contamination of lithology types and facilitated the study of the physical factors affecting the intact strength of shales, like anisotropic strength due to bedding orientation. The analysis of mineralogical characteristics of shales is perhaps the most important contribution of this paper to other researchers who may wish to explore similar methods.

Keywords: rock mechanics, mineralogy, shales, weathering, anisotropy

Procedia PDF Downloads 29

Authors: Se-Hyuk Park, Hee-Jung Seo

Abstract:

Previous studies have investigated effective coping strategies for excessive stress, positive adaptation, resilience, mental health, and personal growth. However, to the best of the authors' knowledge, little research has been conducted to investigate how Koreans with physical disabilities deal with the COVID-19 pandemic. The purpose of this study was to identify coping strategies and coping resources that Koreans with physical disabilities utilized during the COVID-19 crisis. This study used semi-structured, in-depth interviews with 15 participants. Data were qualitatively analyzed using the constant comparative method with content mapping and content mining questions. We identified three salient themes that were used by participants as coping strategies to deal with various COVID-related challenges: (a) engagement in meaningful activities, (b) improvement of social and emotional support, and (c) experience of resilience. The findings of the present study highlighted that Korean adults with SCI actively engaged in various leisure activities, maintained and developed closer social relationships, and experienced resilience to face COVID-19-related stressors. These coping strategies were noted as a catalyst for physical health as well as psychological well-being of individuals with SCI.

Keywords: spinal cord injury, covid-19 pandemic, coping strategies, coping resources, leisure

Procedia PDF Downloads 18

Authors: Shoumodip Roy, Ankit Singhania, Santanu Mallick, Abhiram Jha, M. K. Agarwal, R. V. Ramna, Uttam Singh

Abstract:

The quality of hot metal at any blast furnace is judged by the silicon content in it. Lower hot metal silicon not only enhances process efficiency at steel melting shops but also reduces hot metal costs. The Hot metal produced at G-Blast furnace Tata Steel Jamshedpur has a significantly higher Si content than Benchmark Blast furnaces. The higher content of hot metal Si is mainly due to inferior raw material quality than those used in benchmark blast furnaces. With minimum control over raw material quality, the only option left to control hot metal Si is via optimizing the furnace parameters. Therefore, in order to identify the levers to reduce hot metal Si, Data mining was carried out, and multiple regression models were developed. The statistical analysis revealed that Slag B3{(CaO+MgO)/SiO2}, Slag Alumina and Hot metal temperature are key controllable parameters affecting hot metal silicon. Contour Plots were used to determine the optimum range of levels identified through statistical analysis. A trial plan was formulated to operate relevant parameters, at G blast furnace, in the identified range to reduce hot metal silicon. This paper details out the process followed and subsequent reduction in hot metal silicon by 15% at G blast furnace.

Keywords: blast furnace, optimization, silicon, statistical tools

Procedia PDF Downloads 205

Authors: Reyhaneh Soltanshah, Hamid R. Zarandi

Abstract:

In order to be more efficient in industries that are related to computer systems, software testing is necessary despite spending time and money. In the embedded system software test, complete knowledge of the embedded system architecture is necessary to avoid significant costs and damages. Software tests increase the price of the final product. The aim of this article is to provide a method to reduce time and cost in tests based on program structure. First, a complete review of eleven white box test methods based on ISO/IEC/IEEE 29119 2015 and 2021 versions has been done. The proposed algorithm is designed using two versions of the 29119 standards, and some white-box testing methods that are expensive or have little coverage have been removed. On each of the functions, white box test methods were applied according to the 29119 standard and then the proposed algorithm was implemented on the functions. To speed up the implementation of the proposed method, the Unity framework has been used with some changes. Unity framework can be used in embedded software testing due to its open source and ability to implement white box test methods. The test items obtained from these two approaches were evaluated using a mathematical ratio, which in various software mining reduced between 50% and 80% of the test cost and reached the desired result with the minimum number of test items.

Keywords: embedded software, reduce costs, software testing, white-box testing

Procedia PDF Downloads 25

Authors: Mishell Vaca, Gema Gonzales, Francisco Quiroz

Abstract:

Heavy metals present in wastewater constitute a danger for living beings in general. In Ecuador, one of the sources of contamination is artisanal mining whose liquid effluents, in many of the cases without prior treatment, are discharged to the surrounding rivers. Lead is a pollutant that accumulated in the body causes severe health effects. Nowadays, there are several treatment methods to reduce this pollutant. The aim of this study is to reduce the concentration of lead II through the use of a porous material formed by a matrix of chitosan, in which hydroxyapatite and moringa particles smaller than 53 um are suspended. These materials are not toxic to the environment, and each one adsorbs metals independently, so the synergic effect between them will be evaluated. The synthesized material has a cylindrical design that allows increasing the surface area, which is expected to have greater capacity of adsorption. It has been determined that the best conditions for its preparation are to dissolve the chitosan in 1% v/v acetic acid with a pH = 5, then the hydroxyapatite and moringa are added to the mixture with magnetic stirring. This suspension is frozen, lyophilized and finally dried. In order to evaluate the performance of the synthesized material, synthetic solutions of lead are prepared at different concentrations, and the percentage of removal is evaluated. It is expected to have an effluent whose lead content is less than 0.2 mg/L which is the limit maximum allowable according to established environmental standards.

Keywords: adsorption, chitosan, hydroxyapatite, lead, moringa, water treatment

Procedia PDF Downloads 145

Authors: Ji Min China

Abstract:

The 20th century was the century of globalization. Developed transportation and the progress of information media made the earth into a global village. The differences between regions is increasingly reduced, "cultural convergence" phenomenon intensified, regional specialties and traditional culture has been eroded. In the field of architecture, while experienced orderly rational modernism baptism, it is increasingly recognized that set the expense of cultural differences and forced to follow the universal international-style building has been outdated. At the same time, in the 21st century environmental issues has been paid more and more attention, and the concept of sustainable development and sustainable building have been proposed.This makes the domestic and foreign architects began to explore the possibilities of building and reflect local cultural characteristics of the new vernacular architecture as a viable diversified architectural tendencies by domestic and foreign architects’ favor. The author will use the production and creative process of the new vernacular architecture at home and abroad as the background, and select some outstanding examples of the analysis and discussion, then reinterpret the "new vernacular architecture" in China now. This paper will pay more attention to how to master the true meaning of the here and now "new vernacular" as well as its multiple dimensions of sustainability in the future. It also determines the paper will be a two-way aspect and multi-dimensional understanding and mining of the "new vernacular".

Keywords: new vernacular architecture, regional culture, multi dimension, sustainable

Procedia PDF Downloads 431

Authors: Kisik Song, Sungjoo Lee

Abstract:

Recent years have seen an increasing number of patent disputes due to excessive competition in the global market and a reduced technology life-cycle; this has increased the risk of investment in technology development. While many global companies have started developing a methodology to identify promising technologies and assess for decisions, the existing methodology still has some limitations. Post hoc assessments of the new technology are not being performed, especially to determine whether the suggested technologies turned out to be promising. For example, in existing quantitative patent analysis, a patent’s citation information has served as an important metric for quality assessment, but this analysis cannot be applied to recently registered patents because such information accumulates over time. Therefore, we propose a new technology assessment model that can replace citation information and positively affect technological development based on post hoc analysis of the patents for promising technologies. Additionally, we collect customer reviews on a target technology to extract keywords that show the customers’ needs, and we determine how many keywords are covered in the new technology. Finally, we construct a portfolio (based on a technology assessment from patent information) and a customer-based marketability assessment (based on review data), and we use them to visualize the characteristics of the new technologies.

Keywords: technology assessment, patents, citation information, opinion mining

Procedia PDF Downloads 448

Authors: Nadhiya N. Subramony, Jenifer Vaughan, Lesley E. Scott

Abstract:

In South Africa, the World Health Organisation estimated 454000 new cases of Mycobacterium tuberculosis (M.tb) infection (MTB) in 2015. Disseminated tuberculosis arises from the haematogenous spread and seeding of the bacilli in extrapulmonary sites. The gold standard for the detection of MTB in bone marrow is TB culture which has an average turnaround time of 6 weeks. Histological examinations of trephine biopsies to diagnose MTB also have a time delay owing mainly to the 5-7 day processing period prior to microscopic examination. Adding to the diagnostic delay is the non-specific nature of granulomatous inflammation which is the hallmark of MTB involvement of the bone marrow. A Ziehl-Neelson stain (which highlights acid-fast bacilli) is therefore mandatory to confirm the diagnosis but can take up to 3 days for processing and evaluation. Owing to this delay in diagnosis, many patients are lost to follow up or remain untreated whilst results are awaited, thus encouraging the spread of undiagnosed TB. The Xpert® MTB/RIF (Cepheid, Sunnyvale, CA) is the molecular test used in the South African national TB program as the initial diagnostic test for pulmonary TB. This study investigates the optimisation and performance of the Xpert® MTB/RIF on bone marrow aspirate specimens (BMA), a first since the introduction of the assay in the diagnosis of extrapulmonary TB. BMA received for immunophenotypic analysis as part of the investigation into disseminated MTB or in the evaluation of cytopenias in immunocompromised patients were used. Processing BMA on the Xpert® MTB/RIF was optimised to ensure bone marrow in EDTA and heparin did not inhibit the PCR reaction. Inactivated M.tb was spiked into the clinical bone marrow specimen and distilled water (as a control). A volume of 500mcl and an incubation time of 15 minutes with sample reagent were investigated as the processing protocol. A total of 135 BMA specimens had sufficient residual volume for Xpert® MTB/RIF testing however 22 specimens (16.3%) were not included in the final statistical analysis as an adequate trephine biopsy and/or TB culture was not available. Xpert® MTB/RIF testing was not affected by BMA material in the presence of heparin or EDTA, but the overall detection of MTB in BMA was low compared to histology and culture. Sensitivity of the Xpert® MTB/RIF compared to both histology and culture was 8.7% (95% confidence interval (CI): 1.07-28.04%) and sensitivity compared to histology only was 11.1% (95% CI: 1.38-34.7%). Specificity of the Xpert® MTB/RIF was 98.9% (95% CI: 93.9-99.7%). Although the Xpert® MTB/RIF generates a faster result than histology and TB culture and is less expensive than culture and drug susceptibility testing, the low sensitivity of the Xpert® MTB/RIF precludes its use for the diagnosis of MTB in bone marrow aspirate specimens and warrants alternative/additional testing to optimise the assay.

Keywords: bone marrow aspirate , extrapulmonary TB, low sensitivity, Xpert® MTB/RIF

Procedia PDF Downloads 152

Authors: Martin Hagan

Abstract:

Teacher identity has been recognised as a crucial field of research which supports understanding of the ways in which teachers navigate the complexities of professional life in order to grow in competence, knowledge and practice. As a field of study, teacher identity is concerned with understanding: how identity is defined; how it develops; how teachers make sense of their emerging identity; and how the act of teaching is mediated through the individual teacher’s values, beliefs and sense of professional self. By comparing two particular, socially constructed learning contexts or ‘learning milieu’, one in Northern Ireland and the other in the United States of America, this study aims specifically, to gain better understanding of how teacher identity develops during the initial phase of teacher education. The comparative approach was adopted on the premise that experiences are constructed through interactive, socio-historical and cultural negotiations with others within particular environments, situations and contexts. As such, whilst the common goal is to ‘become’ a teacher, the nuances emerging from the different learning milieu highlight variance in discourse, priorities, practice and influence. A qualitative, interpretative research design was employed to understand the world-constructions of the participants through asking open-ended questions, seeking views and perspectives, examining contexts and eventually deducing meaning. Data were collected using semi structured interviews from a purposive sample of student teachers (n14) in either the first or second year of study in their respective institutions. In addition, a sample of teacher educators (n5) responsible for the design, organisation and management of the programmes were also interviewed. Inductive thematic analysis was then conducted, which highlighted issues related to: the participants’ personal dispositions, prior learning experiences and motivation; the influence of the teacher education programme on the participants’ emerging professional identity; and the extent to which the experiences of working with teachers and pupils in schools in the context of the practicum, challenged and changed perspectives on teaching as a professional activity. The study also highlights the varying degrees of influence exercised by the different roles (tutor, host teacher/mentor, student) within the teacher-learning process across the two contexts. The findings of the study contribute to the understanding of teacher identity development in the early stages of professional learning. By so doing, the research makes a valid contribution to the discourse on initial teacher preparation and can help to better inform teacher educators and policy makers in relation to appropriate strategies, approaches and programmes to support professional learning and positive teacher identity formation.

Keywords: initial teacher education, professional learning, professional growth, teacher identity

Procedia PDF Downloads 56

Authors: Mawloud Mosbah, Bachir Boucheham

Abstract:

We present here the results for a comparative study of some techniques, available in the literature, related to the relevance feedback mechanism in the case of a short-term learning. Only one method among those considered here is belonging to the data mining field which is the K-Nearest Neighbours Algorithm (KNN) while the rest of the methods is related purely to the information retrieval field and they fall under the purview of the following three major axes: Shifting query, Feature Weighting and the optimization of the parameters of similarity metric. As a contribution, and in addition to the comparative purpose, we propose a new version of the KNN algorithm referred to as an incremental KNN which is distinct from the original version in the sense that besides the influence of the seeds, the rate of the actual target image is influenced also by the images already rated. The results presented here have been obtained after experiments conducted on the Wang database for one iteration and utilizing colour moments on the RGB space. This compact descriptor, Colour Moments, is adequate for the efficiency purposes needed in the case of interactive systems. The results obtained allow us to claim that the proposed algorithm proves good results; it even outperforms a wide range of techniques available in the literature.

Keywords: CBIR, category search, relevance feedback, query point movement, standard Rocchio’s formula, adaptive shifting query, feature weighting, original KNN, incremental KNN

Procedia PDF Downloads 266

Authors: Olaniyi Awe, Adelana R. Adetunji, Abraham Adeleke

Abstract:

Mining of alluvial gold ore by artisanal miners has been going on for decades at Itagunmodi, Southwestern Nigeria. In order to optimize the traditional panning gravity separation method commonly used in the area, a mineral particle size analysis study is critical. This study analyzed alluvial gold ore samples collected at identified five different locations in the area with a view to determine the ore particle size distributions. 500g measured of as-received alluvial gold ore sample was introduced into the uppermost sieve of an electrical sieve shaker consisting of sieves arranged in the order of decreasing nominal apertures of 5600μm, 3350μm, 2800μm, 355μm, 250μm, 125μm and 90μm, and operated for 20 minutes. The amount of material retained on each sieve was measured and tabulated for analysis. A screen analysis graph using the Gaudin Schuman method was drawn for each of the screen tests on the alluvial samples. The study showed that the percentages of fine particle size -125+90 μm fraction were 45.00%, 36.00%, 39.60%, 43.00% and 36.80% for the selected samples. These primary ore characteristic results provide reference data for the alluvial gold ore processing method selection, process performance measurement and optimization.

Keywords: alluvial gold ore, sieve shaker, particle size, Gaudin Schumann

Procedia PDF Downloads 23

Authors: Adetunji Olusegun Aderigibigbe

Abstract:

Shales, especially black shales, are of great geological significance, in the study of heavy/trace metal contamination. This is due to their abundance in occurrence and high concentration of heavy metals embedded which are released during their weathering. Heavy metals constitute one of the most dangerous pollution known to human because they are toxic (i.e., carcinogenic), non-biodegradable and can enter the global eco-biological circle. In the past, heavy metal contamination in aquatic environment and agricultural top soil has been attributed to industrial wastes, mining extractions and pollution from traffic vehicles; only a few studies have focused on weathering of shale as possible source of heavy metal contamination. Based on the above background, this study attempts to establish weathering of shale as possible source of trace/heavy metal contaminations. This was done by carefully selecting fresh and their corresponding weathered shale samples from selected localities in Bida and Anambra Basins. The samples were analysed in Activation Laboratories Ltd; Ontario, Canada for trace/heavy metal. It was observed that some major and trace metals were released during weathering, i.e., some were depleted and some enriched. By this contamination of water zones and agricultural top soils are not only traceable to biogenic processes but geogenic inputs (weathering of shale) as well.

Keywords: contamination, fresh samples, heavy metals, pollution, shales, trace metals, weathered samples

Procedia PDF Downloads 111

Authors: Leonard Tiong, Sonit Singh, Kevin Ho Shon, Sarah Lewis

Abstract:

Investigation into the use of artificial intelligence in radiology continues to develop at a rapid rate. During the coronavirus pandemic, the combination of an exponential increase in chest x-rays and unpredictable staff shortages resulted in a huge strain on the department's workload. There is a World Health Organisation estimate that two-thirds of the global population does not have access to diagnostic radiology. Therefore, there could be demand for a program that could detect acute changes in imaging compatible with infection to assist with screening. We generated a conventional neural network and tested its efficacy in recognizing changes compatible with coronavirus infection. Following ethics approval, a deidentified set of 77 normal and 77 abnormal chest x-rays in patients with confirmed coronavirus infection were used to generate an algorithm that could train, validate and then test itself. DICOM and PNG image formats were selected due to their lossless file format. The model was trained with 100 images (50 positive, 50 negative), validated against 28 samples (14 positive, 14 negative), and tested against 26 samples (13 positive, 13 negative). The initial training of the model involved training a conventional neural network in what constituted a normal study and changes on the x-rays compatible with coronavirus infection. The weightings were then modified, and the model was executed again. The training samples were in batch sizes of 8 and underwent 25 epochs of training. The results trended towards an 85.71% true positive/true negative detection rate and an area under the curve trending towards 0.95, indicating approximately 95% accuracy in detecting changes on chest X-rays compatible with coronavirus infection. Study limitations include access to only a small dataset and no specificity in the diagnosis. Following a discussion with our programmer, there are areas where modifications in the weighting of the algorithm can be made in order to improve the detection rates. Given the high detection rate of the program, and the potential ease of implementation, this would be effective in assisting staff that is not trained in radiology in detecting otherwise subtle changes that might not be appreciated on imaging. Limitations include the lack of a differential diagnosis and application of the appropriate clinical history, although this may be less of a problem in day-to-day clinical practice. It is nonetheless our belief that implementing this program and widening its scope to detecting multiple pathologies such as lung masses will greatly assist both the radiology department and our colleagues in increasing workflow and detection rate.

Keywords: artificial intelligence, COVID, neural network, machine learning

Procedia PDF Downloads 73

Authors: Yogi Priyo Pradana, Heriansyah Putra, Regina Aprilia Zulfikar, Maulana Rafiq Ramadhan, Devyan Meisnnehr, Zalfa Maulida Insani

Abstract:

This paper studied the effects and mechanisms of fine-grained tailing by Enzyme-Mediated Calcite Precipitation (EMCP). Grouting solution used consists of reagents (CaCl₂ and (CO(NH₂)₂) and urease enzymes which react to produce CaCO₃. In sample preparation, the test tube is used to investigate the precipitation rate of calcite. The grouting solution added is 75 mL for one mold sample. The solution was poured into a mold sample up to as high as 5 mm from the top surface of the tailing to ensure the entire surface is submerged. The sample is left open in a cylinder for up to 3 days for curing. The direct mixing method is conducted so that the cementation process occurs by evenly distributed. The relationship between the results of the UCS test and the calcite precipitation rate likely indicates that the amount of calcite deposited in treated tailing could control the strength of the tailing. The sample results are analyzed using atomic absorption spectroscopy (AAS) to evaluate metal and metalloid content. Calcium carbonate deposited in the tailing is expected to strengthen the bond between tailing granules, which are easily slipped on the banks of the tailing dam. The EMCP method is expected to strengthen tailing in erosion-control surfaces.

Keywords: tailing, EMCP, UCS, AAS

Procedia PDF Downloads 123

Authors: Leonce Dusengemungu

Abstract:

Filamentous fungi indigenous to heavy metals (HMs) contaminated environments have a considerable biosorption potential yet are currently under-investigated in developing countries. In the work presented herein, the biosorption potential of three indigenous filamentous fungi (Aspergillus transmontanensis, Cladosporium cladosporioides, and Geotrichum candidum) isolated from copper and cobalt mining wasteland sites in Zambia's Copperbelt province was investigated. In Cu and Co tolerance tests, all the fungal isolates were shown to be tolerant, with mycelial growth at HMs concentrations of up to 7000 ppm. However, exposure to high Cu and Co concentrations hindered the growth of the three strains to varying degrees, resulting in reduced mycelial biomass (evidenced by loss of the infrared bands at 887 and 930 cm-1 of the 1,3-glucans backbone) as well as morphological alterations, sporulation, and pigment synthesis. In addition, gas chromatography-mass spectrometry characterization of the fungal biomass extracts allowed to detect changes in the chemical constituents upon exposure to HMs, with profiles poorer in maltol, 1,2-cyclopentadione, and n-hexadecanoic acid, and richer in furaldehydes. Biosorption tests showed that A. transmontanensis and G. candidum showed better performance as bioremediators than C. cladosporioides, with biosorption efficiencies of 1645, 1853 and 1253 ppm at pH 3, respectively, and may deserve further research in field conditions.

Keywords: bioremediation, fungi, biosorption, heavy metal

Procedia PDF Downloads 48

Authors: Yeonjeong Lee, Kyoung-jae Kim, Youngtae Kim

Abstract:

This study proposes a novel recommender system that uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user’s preference. The proposed model consists of two steps. In the first step, this study uses logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. Then, this study combines the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. In the second step, this study uses the market basket analysis to extract association rules for co-purchased products. Finally, the system selects customers who have high likelihood to purchase products in each product group and recommends proper products from same or different product groups to them through above two steps. We test the usability of the proposed system by using prototype and real-world transaction and profile data. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The results also show that the proposed system may be useful in real-world online shopping store.

Keywords: product recommender system, ensemble technique, association rules, decision tree, artificial neural networks

Procedia PDF Downloads 276

Authors: Andrii Shalaginov, Katrin Franke, Xiongwei Huang

Abstract:

One of the leading problems in Cyber Security today is the emergence of targeted attacks conducted by adversaries with access to sophisticated tools. These attacks usually steal senior level employee system privileges, in order to gain unauthorized access to confidential knowledge and valuable intellectual property. Malware used for initial compromise of the systems are sophisticated and may target zero-day vulnerabilities. In this work we utilize common behaviour of malware called ”beacon”, which implies that infected hosts communicate to Command and Control servers at regular intervals that have relatively small time variations. By analysing such beacon activity through passive network monitoring, it is possible to detect potential malware infections. So, we focus on time gaps as indicators of possible C2 activity in targeted enterprise networks. We represent DNS log files as a graph, whose vertices are destination domains and edges are timestamps. Then by using four periodicity detection algorithms for each pair of internal-external communications, we check timestamp sequences to identify the beacon activities. Finally, based on the graph structure, we infer the existence of other infected hosts and malicious domains enrolled in the attack activities.

Keywords: malware detection, network security, targeted attack, computational intelligence

Procedia PDF Downloads 241

Authors: Md. Shaheen Shah, Abdelsalam Abugharara, Dipesh Maharjan, Syed Imtiaz, Stephen Butt

Abstract:

Drilling performance is an essential goal in petroleum and mining industry. Drilling rate of penetration (ROP), which is inversely proportional to the mechanical specific energy (MSE) is influenced by numerous factors among which are the applied parameter: torque (T), weight on bit (WOB), fluid flow rate, revolution per minute (rpm), rock related parameters: rock type, rock homogeneousness, rock anisotropy orientation, and mechanical parameters: bit type, configuration of the bottom hole assembly (BHA). This paper is focused on studying the drilling performance by implementing a passive vibration assisted rotary drilling tool (pVARD) as part of the BHA through using different bit types: coring bit, roller cone bit, and PDC bit and various rock types: rock-like material, granite, sandstone, etc. The results of this study aim to produce a pVARD index for optimal drilling performance considering the recommendations of the pVARD’s spring compression tests and stress-strain analysis of rock samples conducted prior to drilling experiments, analyzing the cutting size distribution, and evaluating the applied drilling parameters as a function of WOB. These results are compared with those obtained from drilling without pVARD, which represents the typical rigid BHA of the conventional drilling.

Keywords: BHA, drilling performance, MSE, pVARD, rate of penetration, ROP, tensile and shear fractures, unconfined compressive strength

Procedia PDF Downloads 130

Authors: P. Kazymbet, G. Abildinova, K.Makhambetov, M. Bakhtin, D. Rybalkina, K. Zhumadilov

Abstract:

Conducted cytogenetic research in workers Stepnogorsk Mining-Chemical Combine (Akmola region) with the study of 26341 chromosomal metaphase. Using a regression analysis with program DataFit, version 5.0, dependence between exposure dose and the following cytogenetic exponents has been studied: frequency of aberrant cells, frequency of chromosomal aberrations, frequency of the amounts of dicentric chromosomes, and centric rings. Experimental data on calibration curves "dose-effect" enabled the development of a mathematical model, allowing on data of the frequency of aberrant cells, chromosome aberrations, the amounts of dicentric chromosomes and centric rings calculate the absorbed dose at the time of the study. In the dose range of 0.1 Gy to 5.0 Gy dependence cytogenetic parameters on the dose had the following equation: Y = 0,0067е^0,3307х (R2 = 0,8206) – for frequency of chromosomal aberrations; Y = 0,0057е^0,3161х (R2 = 0,8832) –for frequency of cells with chromosomal aberrations; Y =5 Е-0,5е^0,6383 (R2 = 0,6321) – or frequency of the amounts of dicentric chromosomes and centric rings on cells. On the basis of cytogenetic parameters and regression equations calculated absorbed dose in workers of uranium production at the time of the study did not exceed 0.3 Gy.

Keywords: Stepnogorsk, mathematical modeling, cytogenetic, dicentric chromosomes

Procedia PDF Downloads 456

Authors: Ramona Zharfpeykan, Paul Rouse

Abstract:

Organizational sustainability is important to both organizations themselves and their stakeholders. Despite its increasing popularity and increasing numbers of organizations reporting sustainability, research on evaluating and comparing the sustainability performance of companies is limited. The aim of this study was to develop models to measure sustainability performance for both cross-sectional and longitudinal comparisons across companies in the same or different industries. A secondary aim was to see if sustainability reports can be used to evaluate sustainability performance. The study used both a content analysis of Australian sustainability reports in mining and metals and financial services for 2011-2014 and a survey of Australian and New Zealand organizations. Two methods ranging from a composite index using uniform weights to data envelopment analysis (DEA) were employed to analyze the data and develop the models. The results show strong statistically significant relationships between the developed models, which suggests that each model provides a consistent, systematic and reasonably robust analysis. The results of the models show that for both industries, companies that had sustainability scores above or below the industry average stayed almost the same during the study period. These indices and models can be used by companies to evaluate their sustainability performance and compare it with previous years, or with other companies in the same or different industries. These methods can also be used by various stakeholders and sustainability ranking companies such as the Global Reporting Initiative (GRI).

Keywords: data envelopment analysis, sustainability, sustainability performance measurement system, sustainability performance index, global reporting initiative

Procedia PDF Downloads 156

Authors: Patrick May Mukonki

Abstract:

KOV pit (Kamoto Oliveira Virgule) is located 10 km from Kolwezi town, one of the mineral rich town in the Lualaba province of the Democratic Republic of Congo. The KOV pit is currently operating under the Katanga Mining Limited (KML), a Glencore-Gecamines (a State Owned Company) join venture. Recently, the mine optimization process provided a life of mine of approximately 10 years withnice pushbacks using the Datamine NPV Scheduler software. In previous KOV pit studies, we recently outlined the impact of the accuracy of the geological information on a long-term mine plan for a big copper mine such as KOV pit. The approach taken, discussed three main scenarios and outlined some weaknesses on the geological information side, and now, in this paper that we are going to develop here, we are going to highlight, as an overview, those weaknesses, strengths and opportunities, in a global SWOT analysis. The approach we are taking here is essentially descriptive in terms of steps taken to optimize KOV pit and, at every step, we categorized the challenges we faced to have a better tradeoff between what we called strengths and what we called weaknesses. The same logic is applied in terms of the opportunities and threats. The SWOT analysis conducted in this paper demonstrates that, despite a general poor ore body definition, and very rude ground water conditions, there is room for improvement for such high grade ore body.

Keywords: mine planning, mine optimization, mine scheduling, SWOT analysis

Procedia PDF Downloads 210