Search results for: mining operation

Authors: Shiji Hu, Lei Li, Wanting Zhou, DaoHong Yang

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The data encryption, is the foundation of today’s communication. On this basis, how to improve the speed of data encryption and decryption is always a problem that scholars work for. In this paper, we proposed an elliptic curve crypto processor architecture based on SM2 prime field. In terms of hardware implementation, we optimized the algorithms in different stages of the structure. In finite field modulo operation, we proposed an optimized improvement of Karatsuba-Ofman multiplication algorithm, and shorten the critical path through pipeline structure in the algorithm implementation. Based on SM2 recommended prime field, a fast modular reduction algorithm is used to reduce 512-bit wide data obtained from the multiplication unit. The radix-4 extended Euclidean algorithm was used to realize the conversion between affine coordinate system and Jacobi projective coordinate system. In the parallel scheduling of point operations on elliptic curves, we proposed a three-level parallel structure of point addition and point double based on the Jacobian projective coordinate system. Combined with the scalar multiplication algorithm, we added mutual pre-operation to the point addition and double point operation to improve the efficiency of the scalar point multiplication. The proposed ECC hardware architecture was verified and implemented on Xilinx Virtex-7 and ZYNQ-7 platforms, and each 256-bit scalar multiplication operation took 0.275ms. The performance for handling scalar multiplication is 32 times that of CPU(dual-core ARM Cortex-A9).

Keywords: Elliptic curve cryptosystems, SM2, modular multiplication, point multiplication.

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Authors: Ahmad. A. Kardan, Amir Narimani, Foozhan Ataiefard

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Recommender Systems have been developed to provide contents and services compatible to users based on their behaviors and interests. Due to information overload in online discussion forums and users diverse interests, recommending relative topics and threads is considered to be helpful for improving the ease of forum usage. In order to lead learners to find relevant information in educational forums, recommendations are even more needed. We present a hybrid thread recommender system for MOOC forums by applying social network analysis and association rule mining techniques. Initial results indicate that the proposed recommender system performs comparatively well with regard to limited available data from users' previous posts in the forum.

Keywords: association rule mining, hybrid recommender system, massive open online courses, MOOCs, social network analysis

Procedia PDF Downloads 294

Authors: Sheikh Shams Azam, Manoj Raju, Venkatesh Pagidimarri, Vamsi Kasivajjala

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Over the past decade, there has been a steep rise in the data-driven analysis in major areas of medicine, such as clinical decision support system, survival analysis, patient similarity analysis, image analytics etc. Most of the data in the field are well-structured and available in numerical or categorical formats which can be used for experiments directly. But on the opposite end of the spectrum, there exists a wide expanse of data that is intractable for direct analysis owing to its unstructured nature which can be found in the form of discharge summaries, clinical notes, procedural notes which are in human written narrative format and neither have any relational model nor any standard grammatical structure. An important step in the utilization of these texts for such studies is to transform and process the data to retrieve structured information from the haystack of irrelevant data using information retrieval and data mining techniques. To address this problem, the authors present Q-Map in this paper, which is a simple yet robust system that can sift through massive datasets with unregulated formats to retrieve structured information aggressively and efficiently. It is backed by an effective mining technique which is based on a string matching algorithm that is indexed on curated knowledge sources, that is both fast and configurable. The authors also briefly examine its comparative performance with MetaMap, one of the most reputed tools for medical concepts retrieval and present the advantages the former displays over the latter.

Keywords: information retrieval, unified medical language system, syntax based analysis, natural language processing, medical informatics

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Authors: Jumel Christian P. Nicha, Severino G. Salmo III

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This study investigated the concentration of heavy metals (HM) in mangrove sediments of Lake Uacon, Zambales, Philippines. The relationship among the studied HM (Cr, Ni, Pb, Cu, Cd, Fe) and the mangrove vegetation and sediment characteristics were assessed. Fourteen sampling plots were designated across the lake (10 vegetated and 4 un-vegetated) based on distance from the mining effluents. In each plot, three sediment cores were collected at 20 cm depth. Among the dominant mangrove species recorded were (in order of dominance): Sonneratia alba, Rhizophora stylosa, Avicennia marina, Excoecaria agallocha and Bruguiera gymnorrhiza. Sediment samples were digested with aqua regia, and the HM concentrations were quantified using Atomic Absorption Spectroscopy (AAS). Results showed that HM concentrations were higher in the vegetated plots as compared to the un-vegetated sites. Vegetated sites had high Ni (mean: 881.71 mg/kg) and Cr (mean: 776.36 mg/kg) that exceeded the threshold values (cf. by the United States Environmental Protection Agency; USEPA). Fe, Pb, Cu and Cd had a mean concentration of 2597.92 mg/kg, 40.94 mg/kg, 36.81 mg/kg and 2.22 mg/kg respectively. Vegetation variables were not significantly correlated with HM concentration. However, the HM concentration was significantly correlated with sediment variables particularly pH, redox, particle size, nitrogen, phosphorus, moisture and organic matter contents. The Pollution Load Index (PLI) indicated moderate to high pollution in the lake. Risk assessment and management should be designed in order to mitigate the ecological risk posed by HM. The need of a regular monitoring scheme for lake and mangrove rehabilitation programs and management should be designed.

Keywords: heavy metals, mangrove vegetation, mining, Philippines, sediment

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Authors: Emil Aliyev

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The main focus of this conference paper is on the aspects of the environmental sustainability of onshore hydrocarbon pipelines. The latter is notorious for being a source of major environmental contamination and a consumer of vast amounts of natural resources such as water, land, steel, etc. Therefore, the environmentally sustainable operation of pipelines is a concern that requires attention and research. The geographical scope of the paper is confined to onshore hydrocarbon pipelines operated in the Middle East region. The research contains elements of originality as it draws on the author’s field experience and practical implementation of environmental and sustainability solutions in a major Middle East-based pipeline organization. The authors describe some of the most common significant environmental aspects of pipeline operations and provide examples of various approaches and technologies that can be successfully utilized to make pipelines more environmentally sustainable. The author concludes that the operation of onshore hydrocarbon pipelines can be made environmentally sustainable. This can be achieved by adopting a systematic framework, focusing limited resources on significant aspects, integrating a circular economy into day-to-day activities, and having strong management support.

Keywords: pipelines, onshore hydrocarbon pipelines, environmental sustainability, significant environmental aspects

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Authors: David L. Knott, Robert Kingsland, Alistair Hitchon

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The proposed Newcastle Light Rail is a key part of the revitalisation of Newcastle, NSW and will provide a frequent and reliable travel option throughout the city centre, running from Newcastle Interchange at Wickham to Pacific Park in Newcastle East, a total of 2.7 kilometers in length. Approximately one-third of the route, along Hunter and Scott Streets, is subject to potential shallow underground mine workings. The extent of mining and seams mined is unclear. Convicts mined the Yard Seam and overlying Dudley (Dirty) Seam in Newcastle sometime between 1800 and 1830. The Australian Agricultural Company mined the Yard Seam from about 1831 to the 1860s in the alignment area. The Yard Seam was about 3 feet (0.9m) thick, and therefore, known as the Yard Seam. Mine maps do not exist for the workings in the area of interest and it was unclear if both or just one seam was mined. Information from 1830s geological mapping and other data showing shaft locations were used along Scott Street and information from the 1908 Royal Commission was used along Hunter Street to develop an investigation program. In addition, mining was encountered for several sites to the south of the alignment at depths of about 7 m to 25 m. Based on the anticipated depths of mining, it was considered prudent to assess the potential for sinkhole development on the proposed alignment and realigned underground utilities and to obtain approval for the work from Subsidence Advisory NSW (SA NSW). The assessment consisted of a desktop study, followed by a subsurface investigation. Four boreholes were drilled along Scott Street and three boreholes were drilled along Hunter Street using HQ coring techniques in the rock. The placement of boreholes was complicated by the presence of utilities in the roadway and traffic constraints. All the boreholes encountered the Yard Seam, with conditions varying from unmined coal to an open void, indicating the presence of mining. The geotechnical information obtained from the boreholes was expanded by using various downhole techniques including; borehole camera, borehole sonar, and downhole geophysical logging. The camera provided views of the rock and helped to explain zones of no recovery. In addition, timber props within the void were observed. Borehole sonar was performed in the void and provided an indication of room size as well as the presence of timber props within the room. Downhole geophysical logging was performed in the boreholes to measure density, natural gamma, and borehole deviation. The data helped confirm that all the mining was in the Yard Seam and that the overlying Dudley Seam had been eroded in the past over much of the alignment. In summary, the assessment allowed the potential for sinkhole subsidence to be assessed and a mitigation approach developed to allow conditional approval by SA NSW. It also confirmed the presence of mining in the Yard Seam, the depth to the seam and mining conditions, and indicated that subsidence did not appear to have occurred in the past.

Keywords: downhole investigation techniques, drilling, mine subsidence, yard seam

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Authors: Tigabu Dagne Akal

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While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

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Authors: Mingming Guo, Xiaozan Wang

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Introduction: The purpose of this study is to examine the correlation between the physical fitness of Chinese college students and their daily running habits (RH). Methods: A total of 718 college students from East China Normal University participated in this study (385 boys and 333 girls). Each participant participated in the Chinese Students’ Physical Fitness Test during the 2018-2019 school year. In addition, each student is also required to use the app to record all their running results during each run during the 2018-2019 school year. Researchers can query and export all running records through the app's management platform. Results: (1) The total number of kilometers run by the students showed a significant negative correlation with their vital capacity (VC), sitting body flexion (SBF), and long jump (LJ) (rᵥ

Keywords: college students, physical fitness, running habits, data mining

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Authors: Pawel Pistelok

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The article presents the concept of an electromagnetic circuit of a 3-phase surface-mounted permanent magnet generator designed for a single phase operation. A cross section of electromagnetic circuit and a field-circuit model of generator used for computations are shown. The paper presents comparative analysis of simulation results obtained for two different versions of generator regarding construction of armature winding. In the first version of generator the voltages generated in each of three winding phases have different rms values (different number of turns in each of phases), three winding phases are connected in series and one phase load is connected to the two output terminals of generator. The second version of generator is very similar, i.e. three winding phases are connected in series and one phase load is powered by generator, but in this version the voltages generated in each of winding phases have exactly the same rms values (the same number of turns in each of phases). The time waveforms of voltages, currents and electromagnetic torques in the airgaps of two machine versions for rated power are shown.

Keywords: permanent magnet generator, permanent magnets, synchronous generator, vibration, course of torque, single phase work, unsymmetrical operation point, serial connection of winding phase

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Authors: Linda O. N. Nwabunike

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The role of internal and external efforts in the management of exploration and exploitation has been highlighted in literature. External ties support ambidexterity at different levels with, for instance: business unit ambidexterity, individual ambidexterity, organizational ambidexterity, and alliance ambidexterity. Recently studies have highlighted the combination of organization, alliance, and acquisition strategies for ambidexterity by conceptualizing ambidexterity across modes of operation. Literature still lacks detailed understanding of how these different processes are combined in the management of ambidexterity across modes of operation. This study plans to propose a conceptual model that illustrates the social processes involved in the management of ambidexterity across modes of operation. Main arguments are integrated from social structures, organizational design, and ambidexterity literature. The framework illustrates that how social capital is promoted by hierarchical relations within the organization and business relations across the boundaries of the organization. Whereby such social relations within and outside the organization are supported by the dual structures of the organization in the coordination of multiple efforts. This paper has potential to contribute to the understanding about how ambidexterity is attained.

Keywords: ambidexterity, coordination, external-ties, social-capital

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Authors: M. Kouhirostamkolaei, M. Kouhirostami, M. Sam, J. Woo, A. T. Asutosh, J. Li, C. Kibert

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Construction is one of the most energy consumed activities in the urban environment that results in a significant amount of greenhouse gas emissions around the world. Thus, the impact of the construction industry on global warming is undeniable. Thus, reducing building energy consumption and mitigating carbon production can slow the rate of global warming. The purpose of this study is to determine the amount of energy consumption and carbon dioxide production during the operation phase and the impact of using new shells on energy saving and carbon footprint. Therefore, a residential building with a re-enforced concrete structure is selected in Babolsar, Iran. DesignBuilder software has been used for one year of building operation to calculate the amount of carbon dioxide production and energy consumption in the operation phase of the building. The primary results show the building use 61750 kWh of energy each year. Computer simulation analyzes the effect of changing building shells -using XPS polystyrene and new electrochromic windows- as well as changing the type of lighting on energy consumption reduction and subsequent carbon dioxide production. The results show that the amount of energy and carbon production during building operation has been reduced by approximately 70% by applying the proposed changes. The changes reduce CO₂e to 11345 kg CO₂/yr. The result of this study helps designers and engineers to consider material selection’s process as one of the most important stages of design for improving energy performance of buildings.

Keywords: construction materials, green construction, energy simulation, carbon footprint, energy saving, concrete structure, designbuilder

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Authors: Taner Ersoz, Filiz Ersoz, Seyma Ozbilge

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In this study, the clients who applied to a bank branch for loan were analyzed through data mining. The study was composed of the information such as amounts of loans received by personal and SME clients working with the bank branch, installment numbers, number of delays in loan installments, payments available in other banks and number of banks to which they are in debt between 2010 and 2013. The client risk profile was examined through Classification and Regression Tree (CART) analysis, one of the decision tree classification methods. At the end of the study, 5 different types of customers have been determined on the decision tree. The classification of these types of customers has been created with the rating of those posing a risk for the bank branch and the customers have been classified according to the risk ratings.

Keywords: client classification, loan suitability, risk rating, CART analysis

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Authors: Qian Zaijian

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E-government is one of the hot issues in the current academic research of public policy and management. As the organic integration of information and communication technology (ICT) and public administration, e-government is one of the most important areas in contemporary information society. Policy information system is a basic subsystem of public policy system, its operation affects the overall effect of the policy process or even exerts a direct impact on the operation of a public policy and its success or failure. The basic principle of its operation is information collection, processing, analysis and release for a specific purpose. The function of E-government for public policy information system lies in the promotion of public access to the policy information resources, information transmission through e-participation, e-consultation in the process of policy analysis and processing of information and electronic services in policy information stored, to promote the optimization of policy information systems. However, due to many factors, the function of e-government to promote policy information system optimization has its practical limits. In the building of E-government in our country, we should take such path as adhering to the principle of freedom of information, eliminating the information divide (gap), expanding e-consultation, breaking down information silos and other major path, so as to promote the optimization of public policy information systems.

Keywords: China, e-consultation, e-democracy, e-government, e-participation, ICTs, public policy information systems

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Authors: Talha Shafiq

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The traditional electricity operation in solar thermal plants is designed to operate on a single path initiating at power plant and executes at the consumer. Due to lack of energy storage facilities during this operation, a decrease in the efficiency is often observed with the power plant performance. This paper reviews the significance of energy storage in supply design and elaborates various methods that can be adopted in this regard which are equally cost effective and environmental friendly. Moreover, various parameters in thermal storage technique are also critically analyzed to clarify the pros and cons in this facility. Discussing the different thermal storage system, their technical and economical evaluation has also been reviewed.

Keywords: thermal energy storage, sensible heat storage, latent heat storage, thermochemical heat storage

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Authors: Walid Moudani, Ahmad Shahin

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This research presents a study to handle the recruitment services system. It aims to enhance a business intelligence system by embedding data mining in its core engine and to facilitate the link between job searchers and recruiters companies. The purpose of this study is to present an intelligent management system for supporting recruitment services based on data mining methods. It consists to apply segmentation on the extracted job postings offered by the different recruiters. The details of the job postings are associated to a set of relevant features that are extracted from the web and which are based on critical criterion in order to define consistent clusters. Thereafter, we assign the job searchers to the best cluster while providing a ranking according to the job postings of the selected cluster. The performance of the proposed model used is analyzed, based on a real case study, with the clustered job postings dataset and classified job searchers dataset by using some metrics.

Keywords: job postings, job searchers, clustering, genetic algorithms, business intelligence

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Authors: Indranil Bayal, Pradipta Panchadhyayee

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Path-spin hybrid entanglement generated and confined in a single spin-1/2 particle is converted to spin-spin hybrid interparticle entanglement, which finds its important applications in quantum information processing. This protocol uses beam splitter, spin flipper, spin measurement, classical channel, unitary transformations, etc., and requires no collective operation on the pair of particles whose spin variables share complete entanglement after the accomplishment of the protocol. The specialty of the protocol lies in the fact that the path-spin entanglement is transferred between spin degrees of freedom of two separate particles initially possessed by a single party.

Keywords: entanglement, path-spin entanglement, spin-spin entanglement, CNOT operation

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Authors: Ezra Yehuwalashet, Alireza Malehmir

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Blötberget mining area in central Sweden, part of the Bergslagen mineral district, is well known for its various type of mineralization particularly iron-oxide deposits since the 1600. To shed lights on the knowledge of the host rock structures, depth extent and tonnage of the mineral deposits and support deep mineral exploration potential in the study area, new ground gravity and existing aeromagnetic data (from the Geological Survey of Sweden) were used for interpretations and modelling. A major boundary separating a gravity low from a gravity high in the southern part of the study area is noticeable and likely representing a fault boundary separating two different lithological units. Gravity data and modeling offers a possible new target area in the southeast of the known mineralization while suggesting an excess high-density region down to 800 m depth.

Keywords: gravity, magnetics, ore deposit, geophysics

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Authors: Ahmed Mohammed Alsalama

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Recommendation systems are widely used in e-commerce applications. The engine of a current recommendation system recommends items to a particular user based on user preferences and previous high ratings. Various recommendation schemes such as collaborative filtering and content-based approaches are used to build a recommendation system. Most of the current recommendation systems were developed to fit a certain domain such as books, articles, and movies. We propose a hybrid framework recommendation system to be applied on two-dimensional spaces (User x Item) with a large number of Users and a small number of Items. Moreover, our proposed framework makes use of both favorite and non-favorite items of a particular user. The proposed framework is built upon the integration of association rules mining and the content-based approach. The results of experiments show that our proposed framework can provide accurate recommendations to users.

Keywords: data mining, association rules, recommendation systems, hybrid systems

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Authors: Retno Ambarwati Sigit Lestari, Wahyudi Budi Sediawan, Sarto Sarto

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This study focused on the removal of sulfide from liquid solution using biofilm on packed bed of salak fruit seeds. Biofilter operation of 444 hours consists of 6 phases of operation. Each phase lasted for approximately 72 hours to 82 hours and run at various inlet concentration and flow rate. The highest removal efficiency is 92.01%, at the end of phase 7 at the inlet concentration of 60 ppm and the flow rate of 30 mL min-1. Mathematic model of sulfide removal was proposed to describe the operation of biofilter. The model proposed can be applied to describe the removal of sulfide liquid using biofilter in packed bed. The simulation results the value of the parameters in process. The value of the rate maximum spesific growth is 4.15E-8 s-1, Saturation constant is 9.1E-8 g cm-3, mass transfer coefisient of liquid is 0.5 cm s-1, Henry’s constant is 0.007, and mass of microorganisms growth to mass of sulfide comsumed is 30. The value of the rate maximum spesific growth in early process is 0.00000004 s-1.

Keywords: biofilm, packed bed, removal, sulfide, salak fruit seeds.

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Authors: Maria De Albuquerque Bercot, Caio Gustavo Mesquita Angelo, Daniela Maria Moreira Siqueira, Augusto Assucena De Vasconcellos, Rodrigo Studart Correa

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Mining is an important socioeconomic activity in Brazil although it negatively impacts the environment. Mineral operations cause irreversible changes in topography, removal of vegetation and topsoil, habitat destruction, displacement of fauna, loss of biodiversity, soil erosion, siltation of watercourses and have potential to enhance climate change. Due to the impacts and its pollution potential, mining activity in Brazil is legally subjected to environmental licensing. Unlicensed mining operations or operations that not abide to the terms of an obtained license are taken as environmental crimes in the country. This work reports a case analyzed in the Forensic Institute of the Brazilian Federal District Civil Police. The case consisted of detecting illegal aspects of sand exploitation from a licensed mine in Federal District, nearby Brasilia city. The fieldwork covered an area of roughly 6 ha, which was surveyed with an unmanned aerial vehicle (UAV) (PHANTOM 3 ADVANCED). The overflight with UAV took about 20 min, with maximum flight height of 100 m. 592 UAV georeferenced images were obtained and processed in a photogrammetric software (AGISOFT PHOTOSCAN 1.1.4), which generated a mosaic of geo-referenced images and a 3D model in less than six working hours. The 3D model was analyzed in a forensic software for accurate modeling and volumetric analysis. (MAPTEK I-SITE FORENSIC 2.2). To ensure the 3D model was a true representation of the mine site, coordinates of ten control points and reference measures were taken during fieldwork and compared to respective spatial data in the model. Finally, these spatial data were used for measuring mining area, excavation depth and volume of exploited sand. Results showed that mine holder had not complied with some terms and conditions stated in the granted license, such as sand exploration beyond authorized extension, depth and volume. Easiness, the accuracy and expedition of procedures used in this case highlight the employment of UAV imagery and computational photogrammetry as efficient tools for outdoor forensic exams, especially on environmental issues.

Keywords: computational photogrammetry, environmental monitoring, mining, UAV

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Authors: Assad Maalouf, Lunjin Lu, James Lynott

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We present a taint analysis that can automatically detect when string operations result in a string that is free of taints, where all the tainted patterns have been removed. This is an improvement on the conservative behavior of previous taint analyzers, where a string operation on a tainted string always leads to a tainted string unless the operation is manually marked as a sanitizer. The taint analysis is built on top of a string analysis that uses finite state automata to approximate the sets of values that string variables can take during the execution of a program. The proposed approach has been implemented as an extension of FlowDroid and experimental results show that the resulting taint analyzer is much more precise than the original FlowDroid.

Keywords: android, static analysis, string analysis, taint analysis

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Authors: Eman AbuKhousa, Marwan Z. Bataineh

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The 21^st century higher education and globalization challenge new faculty members to build effective professional networks and partnership with industry in order to accelerate their growth and success. This creates the need for community of practice (CoP)-oriented development approaches that focus on cognitive apprenticeship while considering individual predisposition and future career needs. This work adopts data mining, clustering analysis, and social networking technologies to present the CoP-Network as a virtual space that connects together similar career-aspiration individuals who are socially influenced to join and engage in a process for domain-related knowledge and practice acquisitions. The CoP-Network model can be integrated into higher education to extend traditional graduate and professional development programs.

Keywords: clustering analysis, community of practice, data mining, higher education, new faculty challenges, social network, social influence, professional development

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Authors: Yahya Almurtadha, Mukhtar Ghaleb, Ahmed M. Shamsan Saleh

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The world witnessed a fierce attack from the Covid-19 virus, which affected public life socially, economically, healthily and psychologically. The world's governments tried to confront the pandemic by imposing a number of precautionary measures such as general closure, curfews and social distancing. Scientists have also made strenuous efforts to develop an effective vaccine to train the immune system to develop antibodies to combat the virus, thus reducing its symptoms and limiting its spread. Artificial intelligence, along with researchers and medical authorities, has accelerated the vaccine development process through big data processing and simulation. On the other hand, one of the most important negatives of the impact of Covid 19 was the state of anxiety and fear due to the blowout of rumors through social media, which prompted governments to try to reassure the public with the available means. This study aims to proposed using Sentiment Analysis (AKA Opinion Mining) and deep learning as efficient artificial intelligence techniques to work on retrieving the tweets of the public from Twitter and then analyze it automatically to extract their opinions, expression and feelings, negatively or positively, about the symptoms they may feel after vaccination. Sentiment analysis is characterized by its ability to access what the public post in social media within a record time and at a lower cost than traditional means such as questionnaires and interviews, not to mention the accuracy of the information as it comes from what the public expresses voluntarily.

Keywords: deep learning, opinion mining, natural language processing, sentiment analysis

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Authors: Lintang Putra Sadewa, Ilham Prasetya Budhi

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Slope monitoring program has now become a mandatory campaign for any open pit mines around the world to operate safely. Utilizing various slope monitoring instruments and strategies, miners are now able to deliver precise decisions in mitigating the risk of slope failures which can be catastrophic. Currently, the most sophisticated slope monitoring technology available is the Slope Stability Radar (SSR), whichcan measure wall deformation in submillimeter accuracy. One of its eminent features is that SSRcan provide a timely warning by automatically raise an alarm when a predetermined rate-of-movement threshold is reached. However, establishing proper alarm thresholds is arguably one of the onerous challenges faced in any slope monitoring program. The difficulty mainly lies in the number of considerations that must be taken when generating a threshold becausean alarm must be effectivethat it should limit the occurrences of false alarms while alsobeing able to capture any real wall deformations. In this sense, experience shows that a site-specific alarm thresholdtendsto produce more reliable results because it considers site distinctive variables. This study will attempt to determinealarming thresholds for safety-critical monitoring based on an empirical model of slope deformation behaviour that is defined statistically fromdeformation data captured by the Slope Stability Radar (SSR). The study area comprises of upright-dipping highwall setting in a coal mining area with intense mining activities, andthe deformation data used for the study were recorded by the SSR throughout the year 2022. The model is site-specific in nature thus, valuable information extracted from the model (e.g., time-to-failure, onset-of-acceleration, and velocity) will be applicable in setting up site-specific alarm thresholds and will give a clear understanding of how deformation trends evolve over the area.

Keywords: safety-critical monitoring, alarming strategy, slope deformation behaviour model, coal mining

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Authors: Sudipto Shanker Dasgupta

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One of the largest mining companies wanted to look at health analytics for their driverless trucks. These trucks were the key to their supply chain logistics. The automated trucks had multi-level sub-assemblies which would send out sensor information. The use case that was worked on was to capture the sensor signal from the truck subcomponents and analyze the health of the trucks from repair and replacement purview. Open source software was used to stream the data into a clustered Hadoop setup in Amazon Web Services cloud and Apache Spark SQL was used to analyze the data. All of this was achieved through a 10 node amazon 32 core, 64 GB RAM setup real-time analytics was achieved on ‘300 million records’. To check the scalability of the system, the cluster was increased to 100 node setup. This talk will highlight how Open Source software was used to achieve the above use case and the insights on the high data throughput on a cloud set up.

Keywords: streaming analytics, data science, big data, Hadoop, high throughput, sensor data

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Authors: Yiea Funk Te, Daniel Mueller, Irena Pletikosa Cvijikj

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Small and medium enterprises (SMEs) play an important role in the economy of many countries. When the overall world economy is considered, SMEs represent 95% of all businesses in the world, accounting for 66% of the total employment. Existing studies show that the current business environment is characterized as highly turbulent and strongly influenced by modern information and communication technologies, thus forcing SMEs to experience more severe challenges in maintaining their existence and expanding their business. To support SMEs at improving their competitiveness, researchers recently turned their focus on applying data mining techniques to build risk and growth prediction models. However, data used to assess risk and growth indicators is primarily obtained via questionnaires, which is very laborious and time-consuming, or is provided by financial institutes, thus highly sensitive to privacy issues. Recently, web mining (WM) has emerged as a new approach towards obtaining valuable insights in the business world. WM enables automatic and large scale collection and analysis of potentially valuable data from various online platforms, including companies’ websites. While WM methods have been frequently studied to anticipate growth of sales volume for e-commerce platforms, their application for assessment of SME risk and growth indicators is still scarce. Considering that a vast proportion of SMEs own a website, WM bears a great potential in revealing valuable information hidden in SME websites, which can further be used to understand SME risk and growth indicators, as well as to enhance current SME risk and growth prediction models. This study aims at developing an automated system to collect business-relevant data from the Web and predict future growth trends of SMEs by means of WM and data mining techniques. The envisioned system should serve as an 'early recognition system' for future growth opportunities. In an initial step, we examine how structured and semi-structured Web data in governmental or SME websites can be used to explain the success of SMEs. WM methods are applied to extract Web data in a form of additional input features for the growth prediction model. The data on SMEs provided by a large Swiss insurance company is used as ground truth data (i.e. growth-labeled data) to train the growth prediction model. Different machine learning classification algorithms such as the Support Vector Machine, Random Forest and Artificial Neural Network are applied and compared, with the goal to optimize the prediction performance. The results are compared to those from previous studies, in order to assess the contribution of growth indicators retrieved from the Web for increasing the predictive power of the model.

Keywords: data mining, SME growth, success factors, web mining

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Authors: A. T. Muruviwa

Abstract:

To-date, the discourse on corporate social responsibility (CSR) has primarily centred on the actions and inactions of corporations; hence, the dominant focus on CSR has been on impacts and outcomes. The obscuring effect of this approach has, arguably, resulted in the emergence of what may be termed a ‘Northern’ agenda on CSR theory and practice, in contrast to an emergency ‘Southern’ discourse, which appears to highlight the crucial issues of poverty reduction, infrastructure development and the broader questions of social provisioning and community empowerment. Some scholars have explicitly called for a CSR research agenda that focuses on the 'reciprocal duties' of the stakeholders in the CSR process rather than fixate on the actions and inactions of business. It is against the backdrop of these contestations that this study assesses the reciprocal relationships amongst CSR stakeholders in a Zimbabwean platinum mining town, with a view to demonstrating how such relationships – and the expectations and obligations embedded in them – impact on the success or failure of CSR initiatives. The existence of mutual relations between the corporation and its stakeholders signifies the successes of CSR processes and hence the outcomes. The company is Zimplats Mining Company; the community is Mhondoro-Ngezi, and the stakeholders are clearly identified in the study. The study utilised a triangulated design, with data collected using a mini survey, focus groups, in-depth interview and observation. The key findings are that the CSR process in the study community is dominated by the mining company. Despite the existence of a CSR framework that recognises government, local leaders and community members as legitimate stakeholders, there is little evidence of concrete contributions made by these stakeholders towards the realisation of CSR objectives. As a result, the community development process – in so far as CSR is concerned – fails to address the developmental concerns of the various stakeholders. On the basis of these findings, the study concludes that there is a crisis of reciprocity in the CSR process in Mhondoro-Ngezi, and that a situation where the conceptualisation of local development needs and the deployment of specific development tools seems to be driven by one stakeholder almost to the exclusion of all others, can only present contradictory development outcomes. The significance of this study is that it allows for the development of a more nuanced and robust CSR discourse. Rather than focusing on the corporate and stakeholder perspectives and outcomes of CSR initiatives, this study examines the CSR- development nexus by interrogating the idea of reciprocal responsibility as a sin qua non to CSR success. This analytical strategy and focus allow the researcher to gain a clear understanding of how stakeholder relationships and duties influence CSR processes and also the overall outcome. At a more practical level, the findings of the study should help to shape the policy on corporate community relationships with a view to enhancing the role of mining in development.

Keywords: community development, processes, reciprocity, stakeholders

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Authors: N. Zerzouri, N. Benalia, N. Bensiali

Abstract:

This work is devoted to an analysis of the operation of a doubly fed induction generator (DFIG) integrated with a wind system. The power transfer between the stator and the network is carried out by acting on the rotor via a bidirectional signal converter. The analysis is devoted to the study of a fault in the converter due to an interruption of the control of a semiconductor. Simulation results obtained by the MATLAB / Simulink software illustrate the quality of the power generated at the default.

Keywords: doubly fed induction generator (DFIG), wind power generation, back to back PWM converter, default switching

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Authors: Julian Wise

Abstract:

Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

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Authors: Anyimc, C. J. Aneke, J. O. Orji, O. Nworie, U. C. C. Egbule

Abstract:

The microbial examination and antimicrobial susceptibility profile of microorganism isolated from the salt mining site in Ebonyi state were evaluated in the present study using a standard microbiological technique. A total of 300 samples were randomly collected in three sample groups (A, B, and C) of 100 each. Isolation, Identification and characterization of organization present on the soil samples were determined by culturing, gram-staining and biochemical technique. The result showed the following organisms were isolated with their frequency as follow: Bacillus species (37.3%) and Staphylococcus species(23.5%) had the highest frequency in the whole Sample group A and B while Klebsiella specie (15.7%), Pseudomonas species(13.7%), and Erwinia species (9.8%) had the least. Rhizopus species (42.0%) and Aspergillus species (26.0%) were the highest fungi isolated, followed by Penicillum species (20.0%) while Mucor species (4.0%), and Fusarium species (8.0%) recorded the least. Sample group C showed high microbial population of all the microbial isolates when compared to sample group A and B. Disc diffusion method was used to determine the susceptibility of isolated bacteria to various antibiotics (oxfloxacin, pefloxacin, ciprorex, augumentin, gentamycin, ciproflox, septrin, ampicillin), while agar well diffusion method was used to determine the susceptibility of isolated fungi to some antifungal drugs (metronidazole, ketoconazole, itraconazole fluconazole). The antibacterial activity of the antibiotics used showed that ciproflux has the best inhibitory effect on all the test bacteria. Ketoconazole showed the highest inhibitory effect on the fungal isolates, followed by itraconazole, while metronidazole and fluconazole showed the least inhibitory effect on the entire test fungal isolates. Hence, the multiple drug resistance of most isolates to appropriate drugs of choice are of great public health concern and cells for periodic monitoring of antibiograms to detect possible changing patterns. Microbes isolated in the salt mining site can also be used as a source of gene(s) that can increase salt tolerance in different crop species through genetic engineering.

Keywords: microorganisms, antibacterial, antifungal, resistance, salt mining site, Ebonyi State

Procedia PDF Downloads 321