Search results for: sequential pattern mining

Authors: Artur Cichowicz

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The last active mine in the Central Rand Goldfields area (50 km x 15 km) ceased operations in 2008. This resulted in the closure of the pumping stations, which previously maintained the underground water level in the mining voids. As a direct consequence of the water being allowed to flood the mine voids, seismic activity has increased directly beneath the populated area of Johannesburg. Monitoring of seismicity in the area has been on-going for over five years using the network of 17 strong ground motion sensors. The objective of the project is to improve strategies for mine closure. The evolution of the seismicity pattern was investigated in detail. Special attention was given to seismic source parameters such as magnitude, scalar seismic moment and static stress drop. Most events are located within historical mine boundaries. The seismicity pattern shows a strong relationship between the presence of the mining void and high levels of seismicity; no seismicity migration patterns were observed outside the areas of old mining. Seven years after the pumping stopped, the evolution of the seismicity has indicated that the area is not yet in equilibrium. The level of seismicity in the area appears to not be decreasing over time since the number of strong events, with Mw magnitudes above 2, is still as high as it was when monitoring began over five years ago. The average rate of seismic deformation is 1.6x1013 Nm/year. Constant seismic deformation was not observed over the last 5 years. The deviation from the average is in the order of 6x10^13 Nm/year, which is a significant deviation. The variation of cumulative seismic moment indicates that a constant deformation rate model is not suitable. Over the most recent five year period, the total cumulative seismic moment released in the Central Rand Basin was 9.0x10^14 Nm. This is equivalent to one earthquake of magnitude 3.9. This is significantly less than what was experienced during the mining operation. Characterization of seismicity triggered by a rising water level in the area can be achieved through the estimation of source parameters. Static stress drop heavily influences ground motion amplitude, which plays an important role in risk assessments of potential seismic hazards in inhabited areas. The observed static stress drop in this study varied from 0.05 MPa to 10 MPa. It was found that large static stress drops could be associated with both small and large events. The temporal evolution of the inter-event time provides an understanding of the physical mechanisms of earthquake interaction. Changes in the characteristics of the inter-event time are produced when a stress change is applied to a group of faults in the region. Results from this study indicate that the fluid-induced source has a shorter inter-event time in comparison to a random distribution. This behaviour corresponds to a clustering of events, in which short recurrence times tend to be close to each other, forming clusters of events.

Keywords: inter-event time, fluid induced seismicity, mine closure, spectral parameters of seismic source

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Authors: Grace Omowunmi Soyebi

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Data Mining is the extraction of information from a large database which helps in predicting a trend or behavior, thereby helping management make knowledge-driven decisions. One principal problem of most hospitals in rural areas is making use of the file management system for keeping records. A lot of time is wasted when a patient visits the hospital, probably in an emergency, and the nurse or attendant has to search through voluminous files before the patient's file can be retrieved; this may cause an unexpected to happen to the patient. This Data Mining application is to be designed using a Structured System Analysis and design method, which will help in a well-articulated analysis of the existing file management system, feasibility study, and proper documentation of the Design and Implementation of a Computerized medical record system. This Computerized system will replace the file management system and help to easily retrieve a patient's record with increased data security, access clinical records for decision-making, and reduce the time range at which a patient gets attended to.

Keywords: data mining, medical record system, systems programming, computing

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Authors: Dim En Nyaung, Thin Lai Lai Thein

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Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: opinion mining, opinion summarization, sentiment analysis, text mining

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Authors: Sarah Werner, Michael J. Pritchard

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From pilots to engineers, the skills development within the aerospace industry is exceptionally broad. Employers often struggle with finding the right mixture of qualified skills to fill their organizational demands. This effort to find qualified talent is further complicated by the industrial delineation between two key areas: aviation and aerospace. In a broad sense, the aerospace industry overlaps with the aviation industry. In turn, the aviation industry is a smaller sector segment within the context of the broader definition of the aerospace industry. Furthermore, it could be conceptually argued that -in practice- there is little distinction between these two sectors (i.e., aviation and aerospace). However, through our unstructured text analysis of over 6,000 job listings captured, our team found a clear delineation between aviation-related jobs and aerospace-related jobs. Using techniques in natural language processing, our research identifies an integrated workforce skill pattern that clearly breaks between these two sectors. While the aviation sector has largely maintained its need for pilots, mechanics, and associated support personnel, the staffing needs of the aerospace industry are being progressively driven by integrative engineering needs. Increasingly, this is leading many aerospace-based organizations towards the acquisition of 'system level' staffing requirements. This research helps to better align higher educational institutions with the current industrial staffing complexities within the broader aerospace sector.

Keywords: aerospace industry, job demand, text mining, workforce development

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: Mohamed Hendawy Mousa, Warda Youssef Mohamed Morsy

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Background: Sepsis is a major cause of mortality and morbidity in trauma patients. Body mass index as an indicator of nutritional status was reported as a predictor of injury pattern and complications among critically ill injured patients. Aim: The aim of this study is to investigate the relationship between body mass index and the development of sepsis, systemic inflammatory response syndrome among adult trauma patients at emergency hospital - Cairo University. Research design: Descriptive correlational research design was utilized in the current study. Research questions: Q1. What is the body mass index profile of adult trauma patients admitted to the emergency hospital at Cairo University over a period of 6 months?, Q2. What is the frequency of systemic inflammatory response syndrome and sepsis among adult trauma patients admitted to the emergency hospital at Cairo University over a period of 6 months?, and Q3. What is the relationship between the development of sepsis, systemic inflammatory response syndrome and body mass index among adult trauma patients admitted to the emergency hospital at Cairo University over a period of 6 months?. Sample: A purposive sample of 52 adult male and female trauma patients with revised trauma score 10 to 12. Setting: The Emergency Hospital affiliated to Cairo University. Tools: Four tools were utilized to collect data pertinent to the study: Socio demographic and medical data tool, Systemic inflammatory response syndrome assessment tool, Revised Trauma Score tool, and Sequential organ failure assessment tool. Results: The current study revealed that, (61.5 %) of the studied subjects had normal body mass index, (25 %) were overweight, and (13.5 %) were underweight. 84.6% of the studied subjects had systemic inflammatory response syndrome and 92.3% were suffering from mild sepsis. No significant statistical relationship was found between body mass index and occurrence of Systemic inflammatory response syndrome (2= 2.89 & P = 0.23). However, Sequential organ failure assessment scores were affected significantly by body mass index was found mean of initial and last Sequential organ failure assessment score for underweight, normal and obese where t= 7.24 at p = 0.000, t= 16.49 at p = 0.000 and t= 9.80 at p = 0.000 respectively. Conclusion: Underweight trauma patients showed significantly higher rate of developing sepsis as compared to patients with normal body weight and obese. Recommendations: based on finding of this study the following are recommended: replication of the study on a larger probability sample from different geographical locations in Egypt; Carrying out of further studies in order to assess the other risk factors influencing trauma outcome and incidence of its complications; Establishment of standardized guidelines for managing underweight traumatized patients with sepsis.

Keywords: body mass index, sepsis, systemic inflammatory response syndrome, adult trauma

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Authors: Mir Md. Abdus Salam, Muhammad Mohsin, Pertti Pulkkinen, Paavo Pelkonen, Ari Pappinen

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Soil and water pollution caused by extensive mining practices can adversely affect environmental components, such as humans, animals, and plants. Despite a generally positive contribution to society, mining practices have become a serious threat to biological systems. As metals do not degrade completely, they require immobilization, toxicity reduction, or removal. A greenhouse experiment was conducted to evaluate the effects of lime and N100 (11-amino-1-hydroxyundecylidene) chelate amendment on the growth and phytoextraction potential of the willow variety Klara (S. viminalis × S. schwerinii × S. dasyclados) grown in soils heavily contaminated with copper (Cu). The plants were irrigated with tap or processed water (mine wastewater). The sequential extraction technique and inductively coupled plasma-mass spectrometry (ICP-MS) tool were used to determine the extractable metals and evaluate the fraction of metals in the soil that could be potentially available for plant uptake. The results suggest that the combined effects of the contaminated soil and processed water inhibited growth parameter values. In contrast, the accumulation of Cu in the plant tissues was increased compared to the control. When the soil was supplemented with lime and N100; growth parameter and resistance capacity were significantly higher compared to unamended soil treatments, especially in the contaminated soil treatments. The combined lime- and N100-amended soil treatment produced higher growth rate of biomass, resistance capacity and phytoextraction efficiency levels relative to either the lime-amended or the N100-amended soil treatments. This study provides practical evidence of the efficient chelate-assisted phytoextraction capability of Klara and highlights its potential as a viable and inexpensive novel approach for in-situ remediation of Cu-contaminated soils and mine wastewaters. Abandoned agricultural, industrial and mining sites can also be utilized by a Salix afforestation program without conflict with the production of food crops. This kind of program may create opportunities for bioenergy production and economic development, but contamination levels should be examined before bioenergy products are used.

Keywords: copper, Klara, lime, N100, phytoextraction

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Authors: Lu Si, Jie Yu, Shasha Li, Jun Ma, Lei Luo, Qingbo Wu, Yongqi Ma, Zhengji Liu

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Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rule, we propose a large data sets instance selection method with MapReduce framework. Besides ensuring the prediction accuracy and reduction rate, it has two desirable properties: First, it reduces the work load in the aggregation node; Second and most important, it produces the same result with the sequential version, which other parallel methods cannot achieve. We evaluate the performance of FCNN-MR on one small data set and two large data sets. The experimental results show that it is effective and practical.

Keywords: instance selection, data reduction, MapReduce, kNN

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Authors: Khaleel Saleh Al-Rababah

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Amyloid fibril forming regions, which are known as protein aggregates, in sequences of some protein families are associated with a number of diseases known as amyloidosis. Mutations play a role in forming fibrils by accelerating the fibril formation process. In this paper we want to extract diseases that caused by those mutations as a result of the impact of the mutations on structural and functional properties of the aggregated protein. We propose a text mining system, to automatically extract mutations, diseases and relations between mutations and diseases. We presented an algorithm based on finite state to cluster mutations found in the same sentence as a sentence could contain different mutation cause different diseases. Also, we presented a co reference algorithm that enables cross-link sentences.

Keywords: amyloid, amyloidosis, co reference, protein, text mining

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Authors: O. D. Eniowo

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“Rewashing” as it is commonly called, involves the process of scooping out and washing chunks of mud from a closed alluvial gold mine site with the purpose of extracting any leftover gold deposits in the site. It is usually carried out by illegal miners who infiltrate closed mine sites with the goal of scavenging for any leftover gold deposits. Expectedly, the practice gives little or no regard for environmental protection. This paper examines the process of “rewashing” in a mining community in Nigeria. It then discusses the looming danger it portends for health, safety, and the environment. The study draws lessons from these occurrences to examine and discuss fit-for-purpose mine closure plans that could be adopted by gold mines in Nigeria and other sub-Saharan African countries.

Keywords: mine planning, mine closure, illegal mining, artisanal mining, environmental sustainability

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Authors: P. Satish Kumar, K. Ramakrishna, Ch. Lokeshwar Reddy, G. Sridhar

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This paper presents two different sequential switching hybrid-modulation strategies and implemented for cascaded multilevel inverters. Hybrid modulation strategies represent the combinations of Fundamental-Frequency Pulse Width Modulation (FFPWM) and Multilevel Sinusoidal-Modulation (MSPWM) strategies, and are designed for performance of the well-known Alternative Phase Opposition Disposition (APOD), Phase Shifted Carrier (PSC). The main characteristics of these modulations are the reduction of switching losses with good harmonic performance, balanced power loss dissipation among the devices with in a cell, and among the series-connected cells. The feasibility of these modulations is verified through spectral analysis, power loss analysis and simulation.

Keywords: cascaded multilevel inverters, hybrid modulation, power loss analysis, pulse width modulation

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Authors: Samara A. Testoni, Vander F. Melo, Lorna A. Dawson, Fabio A. S. Salvador

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Soil traces are useful as forensic evidence due to their potential to transfer and adhere to different types of surfaces on a range of objects or persons. The great variability expressed by soil physical, chemical, biological and mineralogical properties show soil traces as complex mixtures. Soils are continuous and variable, no two soil samples being indistinguishable, nevertheless, the complexity of soil characteristics can provide powerful evidence for comparative forensic purposes. This work aimed to establish a Standard Operating Procedure (SOP) for forensic soil analysis in Brazil. We carried out a simulated crime scene with double blind sampling to calibrate the sampling procedures. Samples were collected at a range of locations covering a range of soil types found in South of Brazil: Santa Candida and Boa Vista, neighbourhoods from Curitiba (State of Parana) and in Guarani and Guaraituba, neighbourhoods from Colombo (Curitiba Metropolitan Region). A previously validated sequential analyses of chemical, physical and mineralogical analyses was developed in around 2 g of soil. The suggested SOP and the sequential range of analyses were effective in grouping the samples from the same place and from the same parent material together, as well as successfully discriminated samples from different locations and originated from different rocks. In addition, modifications to the sample treatment and analytical protocol can be made depending on the context of the forensic work.

Keywords: clay mineralogy, forensic soils analysis, sequential analyses, kaolinite, gibbsite

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Authors: Rachida Malaoui, Leila Arabet , Asma Benbouza

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The use of mining waste rock as a material for construction is one of the biggest concerns grabbing the attention of many mining countries. As these materials are abandoned, more effective solutions have been made to offset some of the building materials, and to avoid environmental pollution. The sands of the Djemi Djema deposit mines of the Djebel Onk mines are sedimentary materials of several varieties of layers with varying thicknesses and are worth far more than 300m deep. The sands from the Djemi Djema business area are medium to coarse and are discharged and accumulated, generating a huge estimated quantity of more than 77424250 tonnes. This state of "resource" is of great importance so as to be oriented towards the fields of public works and civil engineering after having reached the acceptable properties of this resource

Keywords: reuse, sands, shear tests, waste rock

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Authors: Diego Mauricio Murillo Gomez, Enney Leon Gonzalez Ramirez, Hugo Piedrahita, Jairo Yate

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This paper proposes a methodology for the management of noise in open mining industries based on an integral concept, which takes into consideration occupational and environmental noise as a whole. The approach relies on the characterization of sources, the combination of several measurements’ techniques and the use of acoustic prediction software. A discussion about the difference between frequently used acoustic indicators such as Leq and LAV is carried out, aiming to establish common ground for homologation. The results show that the correct integration of this data not only allows for a more robust technical analysis but also for a more strategic route of intervention as several departments of the company are working together. Noise control measurements can be designed to provide a healthy acoustic surrounding in which the exposure workers but also the outdoor community is benefited.

Keywords: environmental noise, noise control, occupational noise, open mining

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Authors: Elham Fathi, Seyed Mohammad Kalantarkousheh, Abolfazl Hatami Varzane

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The present study aimed to determine predict capacity of the relationship among attachment styles, humor styles and communication patterns in female married students. Statistical population consisted of female married students from Allameh Tabataba’i University. The research sample consisted of 104 married students selected through convenience sampling. They responded to study instruments that consisted of attachment styles, humor styles and Communication patterns questionnaires. Data was analyzed by means of correlation method. The results indicated significant positive relationship between secure attachment styles with adaptive humor styles, and anxious attachment styles with maladaptive humor styles. Also a negative relationship between avoidant attachment with affiliative humor, and anxious attachment with self-enhancing humor was found. Furthermore, a negative relationship between self- enhancing humor styles with demand – withdraw communication pattern, and between affiliative humor with mutual avoidant communication pattern and a positive relationship between affiliative humor with mutual constructive communication pattern was observed. The relationship between secure attachment with mutual constructive communication pattern was positive, while relationship between avoidant attachment to mutual constructive communication pattern was negative and significant and its relation with mutual avoidant communication pattern was significantly positive. The result of regression analysis indicated that affliative humor style and secure attachment style, positively predicted mutual constructive communication pattern. Avoidant attachment style positively and affliative humor style negatively predicted the mutual avoidant communication pattern. And self-enhancing humor style negatively predicted the demand – withdraw communication pattern style.

Keywords: attachment styles, communication patterns, humor styles, female married students

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Authors: Beata Spilakova, Daniel J. Shaw, Radek Marecek, Milan Brazdil

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Hyperscanning affords a unique insight into the brain dynamics underlying human interaction by simultaneously scanning two or more individuals’ brain responses while they engage in dyadic exchange. This provides an opportunity to observe dynamic brain activations in all individuals participating in interaction, and possible interbrain effects among them. The present research aims to provide an experimental paradigm for hyperscanning research capable of delineating among different forms of interaction. Specifically, the goal was to distinguish between two dimensions: (1) interaction structure (concurrent vs. turn-based) and (2) goal structure (competition vs cooperation). Dual-fMRI was used to scan 22 pairs of participants - each pair matched on gender, age, education and handedness - as they played the Pattern Game. In this simple interactive task, one player attempts to recreate a pattern of tokens while the second player must either help (cooperation) or prevent the first achieving the pattern (competition). Each pair played the game iteratively, alternating their roles every round. The game was played in two consecutive sessions: first the players took sequential turns (turn-based), but in the second session they placed their tokens concurrently (concurrent). Conventional general linear model (GLM) analyses revealed activations throughout a diffuse collection of brain regions: The cooperative condition engaged medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC); in the competitive condition, significant activations were observed in frontal and prefrontal areas, insula cortices and the thalamus. Comparisons between the turn-based and concurrent conditions revealed greater precuneus engagement in the former. Interestingly, mPFC, PCC and insulae are linked repeatedly to social cognitive processes. Similarly, the thalamus is often associated with a cognitive empathy, thus its activation may reflect the need to predict the opponent’s upcoming moves. Frontal and prefrontal activation most likely represent the higher attentional and executive demands of the concurrent condition, whereby subjects must simultaneously observe their co-player and place his own tokens accordingly. The activation of precuneus in the turn-based condition may be linked to self-other distinction processes. Finally, by performing intra-pair correlations of brain responses we demonstrate condition-specific patterns of brain-to-brain coupling in mPFC and PCC. Moreover, the degree of synchronicity in these neural signals related to performance on the game. The present results, then, show that different types of interaction recruit different brain systems implicated in social cognition, and the degree of inter-player synchrony within these brain systems is related to nature of the social interaction.

Keywords: brain-to-brain coupling, hyperscanning, pattern game, social interaction

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Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng

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Parallel optimization is one of the important research topics of data mining at this stage. Taking Classification and Regression Tree (CART) parallelization as an example, this paper proposes a parallel data mining algorithm based on SSP-OGini-PCCP. Aiming at the problem of choosing the best CART segmentation point, this paper designs an S-SP model without data association; and in order to calculate the Gini index efficiently, a parallel OGini calculation method is designed. In addition, in order to improve the efficiency of the pruning algorithm, a synchronous PCCP pruning strategy is proposed in this paper. In this paper, the optimal segmentation calculation, Gini index calculation, and pruning algorithm are studied in depth. These are important components of parallel data mining. By constructing a distributed cluster simulation system based on SPARK, data mining methods based on SSP-OGini-PCCP are tested. Experimental results show that this method can increase the search efficiency of the best segmentation point by an average of 89%, increase the search efficiency of the Gini segmentation index by 3853%, and increase the pruning efficiency by 146% on average; and as the size of the data set increases, the performance of the algorithm remains stable, which meets the requirements of contemporary massive data processing.

Keywords: classification, Gini index, parallel data mining, pruning ahead

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Authors: Rosendo Mendoza, María Carmen Hidalgo, María José Campos-Suñol, Julián Martínez, Javier Rey

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The impact of mining environmental liabilities and mine drainage on surface water quality has been investigated in the hydrographic basin of the La Carolina mining district (southern Spain). This abandoned mining district is characterized by the existence of important mineralizations of sulfoantimonides of Pb - Ag, and sulfides of Cu - Fe. All surface waters reach the main river of this mining area, the Grande River, which ends its course in the Rumblar reservoir. This waterbody is intended to supply 89,000 inhabitants, as well as irrigation and livestock. Therefore, the analysis and control of the metal(loid) concentration that exists in these surface waters is an important issue because of the potential pollution derived from metallic mining. A hydrogeochemical campaign consisting of 20 water sampling points was carried out in the hydrographic network of the Grande River, as well as two sampling points in the Rumbler reservoir and at the main tailings impoundment draining to the river. Although acid mine drainage (pH below 4) is discharged into the Grande river from some mine adits, the pH values in the river water are always neutral or slightly alkaline. This is mainly the result of a dilution process of the small volumes of mine waters by net alkaline waters of the river. However, during the dry season, the surface waters present high mineralization due to a constant discharge from the abandoned flooded mines and a decrease in the contribution of surface runoff. The concentrations of dissolved Cd and Pb in the water reach values of 2 and 81 µg/l, respectively, exceeding the limit established by the Environmental Quality Standard for surface water. In addition, the concentrations of dissolved As, Cu, and Pb in the waters of the Rumblar reservoir reached values of 10, 20, and 11 µg/l, respectively. These values are higher than the maximum allowable concentration for human consumption, a circumstance that is especially alarming.

Keywords: environmental quality, hydrogeochemistry, metal mining, surface water

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Authors: Saroj Bijarnia, Preety Singh

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We propose a simple and effective biometrics system based on face verification across aging using a new variant of texture feature, Pyramid Binary Pattern. This employs Local Binary Pattern along with its hierarchical information. Dimension reduction of generated texture feature vector is done using Principal Component Analysis. Support Vector Machine is used for classification. Our proposed method achieves an accuracy of 92:24% and can be used in an automated age-invariant face verification system.

Keywords: biometrics, age invariant, verification, support vector machine

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Authors: Ling Chen, Lanyan Peng

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In the new round of institutional reform of the State Council, Ministry of Culture and Ministry of Tourism were formed into a new department, Ministry of Culture and Tourism, which embodied the idea of the fusion development of cultural and tourism industries. At the same time, domestic tourists pay more attention to the tourism experience and tourism quality. The tourism patterns have been changed from the sightseeing mode of the individual scenic spot to the lifestyle mode of feeling the cultural atmosphere of the tourist destination. Therefore, this paper focuses on the tourism pattern based on lifestyle, studies the development status, content, and implementation measures of the tourism pattern. As the tourism pattern based on lifestyle integrating cultural and tourism industries in-depth, tourists can experience the living atmosphere, living conditions and living quality of the tourist destination, and deeply understand the urban cultural connotation during the trip. Suzhou has taken a series of measures to build up a tourism pattern based on lifestyle-'Suzhou life' tourism, including regional planning of tourism, integration of cultural resources, construction of urban atmosphere, and upgrading infrastructure. 'Suzhou life' tourism is based on the Suzhou food (cooked wheaten food, dim sum, specialty snacks), tourist attractions (Suzhou gardens, the ancient city) and characteristic recreational ways (appreciating Kun opera, enjoying Suzhou Pingtan, tea drinking). And the continuous integration of the three components above meet the spiritual, cultural needs of tourists and upgrade the tourism pattern based on lifestyle. Finally, the paper puts forward the tourism pattern planning suggestions.

Keywords: tourism pattern, lifestyle, integration of cultural and tourism industries, Suzhou life

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Authors: Kutub Uddin Chisty, Md. Kamrul Islam, Md. Ashraful Islam

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Growth pattern is an important factor for a city because it can help to predict future growth trend and development of a city. Khagrachari District is one of the three hill tracts districts in Bangladesh. It is bordered by the Indian State of Tripura on the north, Rangamati and Chittagong districts on the south, Rangamati district on the east, Chittagong district and the Indian State of Tripura on the west. Khagrachari Pourashava is surrounded by hills and waterways. The Pourashava area is mostly inhibited by non-tribal population, while tribal population lives in hilly regions within and around the Pourashava area. The hilly area growth is different. Based on questioners and expert opinions survey, growth pattern of Khagrachari is evaluated. Different culture, history, tribal people, non-tribal people enrich the hilly heritages. In our study, we analyse the city growth pattern and identify the prominent factors that influence the city growth. Thus, it can help us to identify growth trend of the city.

Keywords: growth pattern, growth trend, prominent factors, regional development

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Authors: Faisal Muhibuddin, Ani Dijah Rahajoe

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This in-depth exploration, through a systematic literature review, scrutinizes the nuanced role of data mining in the classification of criminal activities. The research focuses on investigating various methodological aspects and recent developments in leveraging data mining techniques to enhance the effectiveness and precision of crime categorization. Commencing with an exposition of the foundational concepts of crime classification and its evolutionary dynamics, this study details the paradigm shift from conventional methods towards approaches supported by data mining, addressing the challenges and complexities inherent in the modern crime landscape. Specifically, the research delves into various data mining techniques, including K-means clustering, Naïve Bayes, K-nearest neighbour, and clustering methods. A comprehensive review of the strengths and limitations of each technique provides insights into their respective contributions to improving crime classification models. The integration of diverse data sources takes centre stage in this research. A detailed analysis explores how the amalgamation of structured data (such as criminal records) and unstructured data (such as social media) can offer a holistic understanding of crime, enriching classification models with more profound insights. Furthermore, the study explores the temporal implications in crime classification, emphasizing the significance of considering temporal factors to comprehend long-term trends and seasonality. The availability of real-time data is also elucidated as a crucial element in enhancing responsiveness and accuracy in crime classification.

Keywords: data mining, classification algorithm, naïve bayes, k-means clustering, k-nearest neigbhor, crime, data analysis, sistematic literature review

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Authors: Ketan Mahawer, Abeer Mutto, S. K. Gupta

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The mining wastewater contains inorganic metal salts, which makes it saline and additionally contributes to contaminating the surface and underground freshwater reserves that exist nearby mineral processing industries. Therefore, treatment of wastewater and water recovery is obligatory by any available technology before disposing it into the environment. Currently, reverse osmosis (RO) is the commercially acceptable conventional membrane process for saline wastewater treatment, but consumes an enormous amount of energy and makes the process expensive. To solve this industrial problem with minimum energy consumption, we tested the feasibility of forward osmosis-nanofiltration (FO-NF) hybrid process for the mining wastewater treatment. The FO-NF process experimental results for 0.029M concentration of saline wastewater treated by 0.42 M sodium-sulfate based draw solution shows that specific energy consumption of the FO-NF process compared with standalone NF was slightly above (between 0.5-1 kWh/m3) from conventional process. However, average freshwater recovery was 30% more from standalone NF with same feed and operating conditions. Hence, FO-NF process in place of RO/NF offers a huge possibility for treating mining industry wastewater and concentrates the metals as the by-products without consuming an excessive/large amount of energy and in addition, mitigates the fouling in long periods of treatment, which also decreases the maintenance and replacement cost of the separation process.

Keywords: forward osmosis, nanofiltration, mining, draw solution, divalent solute

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Authors: G. A. Gevorgyan, K. A. Ghazaryan, T. H. Derdzyan

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The heavy metal pollution of the soils around the mining area near Shamlugh town and related risks to human health were assessed. The investigations showed that the soils were polluted with heavy metals that can be ranked by anthropogenic pollution degree as follows: Cu>Pb>As>Co>Ni>Zn. The main sources of the anthropogenic metal pollution of the soils were the copper mining area near Shamlugh town, the Chochkan tailings storage facility and the trucks transferring are from the mining area. Copper pollution degree in some observation sites was unallowable for agricultural production. The total non-carcinogenic chronic hazard index (THI) values in some places, including observation sites in Shamlugh town, were above the safe level (THI<1) for children living in this territory. Although the highest heavy metal enrichment degree in the soils was registered in case of copper, the highest health risks to humans especially children were posed by cobalt which is explained by the fact that heavy metals have different toxicity levels and penetration characteristics.

Keywords: Armenia, copper mine, heavy metal pollution of soil, health risks

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Authors: Oussama Hafferssas, Hiba Benyahia, Amina Madani, Nassima Zeriri

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Although data nowadays has multiple forms; from text to images, and from audio to videos, yet text is still the most used one at a public level. At an academical and research level, and unlike other forms, text can be considered as the easiest form to process. Therefore, a brunch of Data Mining researches has been always under its shadow, called "Text Mining". Its concept is just like data mining’s, finding valuable patterns in data, from large collections and tremendous volumes of data, in this case: Text. Named entity recognition (NER) is one of Text Mining’s disciplines, it aims to extract and classify references such as proper names, locations, expressions of time and dates, organizations and more in a given text. Our approach "Octopub" does not aim to find new ways to improve named entity recognition process, rather than that it’s about finding a new, and yet smart way, to use NER in a way that we can extract sentiments of millions of people using Social Networks as a limitless information source, and Marketing for product promotion as the main domain of application.

Keywords: textmining, named entity recognition(NER), sentiment analysis, social media networks (SN, SMN), business intelligence(BI), marketing

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Authors: Erika Ruíz, Luis Amaya, Diego Carreño

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The main objective of this study is to design a mathematical model for the logistics of mining collection centers in the northern region of the department of Boyacá (Colombia), determining the structure that facilitates the flow of products along the supply chain. In order to achieve this, it is necessary to define a suitable design of the distribution network, taking into account the products, customer’s characteristics and the availability of information. Likewise, some other aspects must be defined, such as number and capacity of collection centers to establish, routes that must be taken to deliver products to the customers, among others. This research will use one of the operation research problems, which is used in the design of distribution networks known as Location Routing Problem (LRP).

Keywords: location routing problem, logistic, mining collection, model

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Authors: Ebert Brea

Abstract:

We propose a novel direct search algorithm for identifying at least a local minimum of mixed integer nonlinear unconstrained optimization problems. The Mixed Integer Randomized Pattern Search Algorithm (MIRPSA), so-called by the author, is based on a randomized pattern search, which is modified by the MIRPSA for finding at least a local minimum of our problem. The MIRPSA has two main operations over the randomized pattern search: moving operation and shrinking operation. Each operation is carried out by the algorithm when a set of conditions is held. The convergence properties of the MIRPSA is analyzed using a Markov chain approach, which is represented by an infinite countable set of state space λ, where each state d(q) is defined by a measure of the qth randomized pattern search Hq, for all q in N. According to the algorithm, when a moving operation is carried out on the qth randomized pattern search Hq, the MIRPSA holds its state. Meanwhile, if the MIRPSA carries out a shrinking operation over the qth randomized pattern search Hq, the algorithm will visit the next state, this is, a shrinking operation at the qth state causes a changing of the qth state into (q+1)th state. It is worthwhile pointing out that the MIRPSA never goes back to any visited states because the MIRPSA only visits any qth by shrinking operations. In this article, we describe the MIRPSA for mixed integer nonlinear unconstrained optimization problems for doing a deep study of its convergence properties using Markov chain viewpoint. We herein include a low dimension case for showing more details of the MIRPSA, when the algorithm is used for identifying the minimum of a mixed integer quadratic function. Besides, numerical examples are also shown in order to measure the performance of the MIRPSA.

Keywords: direct search, mixed integer optimization, random search, convergence, Markov chain

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Authors: Mais Haj Qasem, Maen M. Al Assaf, Ali Rodan

Abstract:

Parallel hybrid storage systems consist of a hierarchy of different storage devices that vary in terms of data reading speed performance. As we ascend in the hierarchy, data reading speed becomes faster. Thus, migrating the application’ important data that will be accessed in the near future to the uppermost level will reduce the application I/O waiting time; hence, reducing its execution elapsed time. In this research, we implement trace-driven two-levels parallel hybrid storage system prototype that consists of HDDs and SSDs. The prototype uses data mining techniques to classify application’ data in order to determine its near future data accesses in parallel with the its on-demand request. The important data (i.e. the data that the application will access in the near future) are continuously migrated to the uppermost level of the hierarchy. Our simulation results show that our data migration approach integrated with data mining techniques reduces the application execution elapsed time when using variety of traces in at least to 22%.

Keywords: hybrid storage system, data mining, recurrent neural network, support vector machine

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Authors: Nidhin Dani Abraham, T. K. Sri Shilpa

Abstract:

Asset liability management is an important aspect in banking business. Moreover, the today’s banking is based on BASEL III which strictly regulates on the counterparty default. This paper focuses on prediction and analysis of counter party default risk, which is a type of risk occurs when the customers fail to repay the amount back to the lender (bank or any financial institutions). This paper proposes an approach to reduce the counterparty risk occurring in the financial institutions using an appropriate data mining technique and thus predicts the occurrence of NPA. It also helps in asset building and restructuring quality. Liability management is very important to carry out banking business. To know and analyze the depth of liability of bank, a suitable technique is required. For that a data mining technique is being used to predict the dormant behaviour of various deposit bank customers. Various models are implemented and the results are analyzed of saving bank deposit customers. All these data are cleaned using data cleansing approach from the bank data warehouse.

Keywords: data mining, asset liability management, BASEL III, banking

Procedia PDF Downloads 552

Authors: Ahmad Saifullah Mazlan, Hossein Basser, Shatirah Akib

Abstract:

Scouring pattern evaluation and measuring its depth around coastal and offshore structures is very essential issue to assure the safety of the structures as well as providing needed design parameters. Scouring is known as one of the important phenomena which threatens the safety of infrastructures. Several countermeasures have been developed to control scouring by protecting the structures against water flow attack directly or indirectly by changing the water flow pattern. Recently, monitoring methods for estimating water flow pattern and scour depth are studied to track the safety of structures. Since most of studies regarding scouring is related to monitoring scouring around piers in rivers therefore it is necessary to develop researches investigating scouring around piers in coastal and offshore areas. This paper describes a review of monitoring methods may be used for detecting scour depth around piers in coastal and offshore structures.

Keywords: scour, monitoring, pier, coastal, offshore

Procedia PDF Downloads 644