Search results for: Erdenet Mining Corporation

Authors: Marine Reymond, Michael Descostes, Marie Muguet, Clemence Besancon, Martine Leermakers, Catherine Beaucaire, Sophie Billon, Patricia Patrier

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²²⁶Ra is one of the radionuclides resulting from the disintegration of ²³⁸U. Due to its half-life (1600 y) and its high specific activity (3.7 x 1010 Bq/g), ²²⁶Ra is found at the ultra-trace level in the natural environment (usually below 1 Bq/L, i.e. 10-13 mol/L). Because of its decay in ²²²Rn, a radioactive gas with a shorter half-life (3.8 days) which is difficult to control and dangerous for humans when inhaled, ²²⁶Ra is subject to a dedicated monitoring in surface waters especially in the context of uranium mining. In natural waters, radionuclides occur in dissolved, colloidal or particular forms. Due to the size of colloids, generally ranging between 1 nm and 1 µm and their high specific surface areas, the colloidal fraction could be involved in the transport of trace elements, including radionuclides in the environment. The colloidal fraction is not always easy to determine and few existing studies focus on ²²⁶Ra. In the present study, a complete multidisciplinary approach is proposed to assess the colloidal transport of ²²⁶Ra. It includes water sampling by conventional filtration (0.2µm) and the innovative Diffusive Gradient in Thin Films technique to measure the dissolved fraction (<10nm), from which the colloidal fraction could be estimated. Suspended matter in these waters were also sampled and characterized mineralogically by X-Ray Diffraction, infrared spectroscopy and scanning electron microscopy. All of these data, which were acquired on a rehabilitated former uranium mine, allowed to build a geochemical model using the geochemical calculation code PhreeqC to describe, as accurately as possible, the colloidal transport of ²²⁶Ra. Colloidal transport of ²²⁶Ra was found, for some of the sampling points, to account for up to 95% of the total ²²⁶Ra measured in water. Mineralogical characterization and associated geochemical modelling highlight the role of barite, a barium sulfate mineral well known to trap ²²⁶Ra into its structure. Barite was shown to be responsible for the colloidal ²²⁶Ra fraction despite the presence of kaolinite and ferrihydrite, which are also known to retain ²²⁶Ra by sorption.

Keywords: colloids, mining context, radium, transport

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Authors: Carly Madge, Melanie Zurba, Ryan Bullock

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The Boreal Forest has experienced some of the most drastic climate change-induced temperature rises in Canada, with average winter temperatures increasing by 3°C since 1948. One of the main concerns of the province of Saskatchewan, and particularly wildfire managers, is the increased risk of wildfires due to climate change. With these concerns in mind Sakaw Askiy Management Inc., a forestry corporation located in Prince Albert, Saskatchewan with operations in the Boreal Forest biome, is developing wildfire risk reduction strategies that are supported by the shareholders of the corporation as well as the stakeholders of the Prince Albert Forest Management Area (which includes citizens, hunters, trappers, cottage owners, and outfitters). In the past, wildfire management strategies implemented through harvesting have been received with skepticism by some community members of Prince Albert. Engagement of the stakeholders of the Prince Albert Management Area through the development of the wildfire risk reduction strategies aims to reduce this skepticism and rebuild some of the trust that has been lost between industry and community. This research project works with the framework of social learning, which is defined as the learning that occurs when individuals come together to form a group with the purpose of understanding environmental challenges and determining appropriate responses to them. The project evaluates the social learning processes that occur through the development of the risk reduction strategies and how the learning has allowed Sakaw to work towards implementing the strategies into their forest harvesting plans. The incorporation of wildfire risk reduction strategies works to increase the adaptive capacity of Sakaw, which in this case refers to the ability to adjust to climate change, moderate potential damages, take advantage of opportunities, and cope with consequences. Using semi-structured interviews and wildfire workshop meetings shareholders and stakeholders shared their knowledge of wildfire, their main wildfire concerns, and changes they would like to see made in the Prince Albert Forest Management Area. Interviews and topics discussed in the workshops were inductively coded for themes related to learning, adaptive capacity, areas of concern, and preferred methods of wildfire risk reduction strategies. Analysis determined that some of the learning that has occurred has resulted through social interactions and the development of networks oriented towards wildfire and wildfire risk reduction strategies. Participants have learned new knowledge and skills regarding wildfire risk reduction. The formation of wildfire networks increases access to information on wildfire and the social capital (trust and strengthened relations) of wildfire personnel. Both factors can be attributed to increases in adaptive capacity. Interview results were shared with the General Manager of Sakaw, where the areas of concern and preferred strategies of wildfire risk reduction will be considered and accounted for in the implementation of new harvesting plans. This research also augments the growing conceptual and empirical evidence of the important role of learning and networks in regional wildfire risk management efforts.

Keywords: adaptive capacity, community-engagement, social learning, wildfire risk reduction

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Authors: Maulana Ayoub Ali

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Malayan Pilgrims Savings Corporation was introduced in 1963. Six years later, Malaysian Pilgrims Fund Board (Tabung Haji) was formed. The board used to collect funds from pilgrims who expected to perform pilgrimage in the future dates. Money was collected and kept as per given rules and procedures emanated from Islamic sources of law. Twenty years later, the country was ready to run a fully fledged Islamic bank where the Bank Islam Malaysia Berhad (BIMB) came into existence in the year 1983. This paper investigates stages of development of Islamic banking system in Malaysia from 1983 to date. This study discovered that Malaysia had enough time to make Islamic banking system works alongside conventional banking system and for sure, has successfully managed to come up with the comprehensive and workable financial system which accommodates both the conventional and Islamic banking. As a result, Malaysia stands to be the hub of Islamic banking products and services in the world today.

Keywords: Tabung Haji, Islamic Banks, conventional law, Malaysia

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Authors: H. Falsafi Falsafizadeh, R. Zeinali Zeinali

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This paper focuses on determination of total Operating Reserve (OR) level, consisting of spinning and non-spinning reserves, in two small real power systems, in such a way that the system reliability indicator would comply with typical industry standards. For this purpose, the standard used by the North American Electric Reliability Corporation (NERC) – i.e., 1 day outage in 10 years or 0.1 days/year is relied. The simulation of system operation for these systems that was used for the determination of total operating reserve level was performed by industry standard production simulation software in this field, named PLEXOS. In this paper, the operating reserve which meets an annual Loss of Load Expectation (LOLE) of approximately 0.1 days per year is determined in the study year. This reserve is the minimum amount of reserve required in a power system and generally defined as a percentage of the annual peak.

Keywords: frequency control, LOLE, operating reserve, system reliability

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Authors: Nkongho Ayuketang Arreyndip, Ebobenow Joseph

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In this paper, temperature extremes are forecast by employing the block maxima method of the generalized extreme value (GEV) distribution to analyse temperature data from the Cameroon Development Corporation (CDC). By considering two sets of data (raw data and simulated data) and two (stationary and non-stationary) models of the GEV distribution, return levels analysis is carried out and it was found that in the stationary model, the return values are constant over time with the raw data, while in the simulated data the return values show an increasing trend with an upper bound. In the non-stationary model, the return levels of both the raw data and simulated data show an increasing trend with an upper bound. This clearly shows that although temperatures in the tropics show a sign of increase in the future, there is a maximum temperature at which there is no exceedance. The results of this paper are very vital in agricultural and environmental research.

Keywords: forecasting, generalized extreme value (GEV), meteorology, return level

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Authors: Heeyeul Kwon, Yongtae Park

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Despite the highly touted benefits, emerging technologies have unleashed pervasive concerns regarding unintended and unforeseen social impacts. Thus, those wishing to create safe and socially acceptable products need to identify such side effects and mitigate them prior to the market proliferation. Various methodologies in the field of technology assessment (TA), namely Delphi, impact assessment, and scenario planning, have been widely incorporated in such a circumstance. However, literatures face a major limitation in terms of sole reliance on participatory workshop activities. They unfortunately missed out the availability of a massive untapped data source of futuristic information flooding through the Internet. This research thus seeks to gain insights into utilization of futuristic data, future-oriented documents from the Internet, as a supplementary method to generate social impact scenarios whilst capturing perspectives of experts from a wide variety of disciplines. To this end, network analysis is conducted based on the social keywords extracted from the futuristic documents by text mining, which is then used as a guide to produce a comprehensive set of detailed scenarios. Our proposed approach facilitates harmonized depictions of possible hazardous consequences of emerging technologies and thereby makes decision makers more aware of, and responsive to, broad qualitative uncertainties.

Keywords: emerging technologies, futuristic data, scenario, text mining

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Authors: Gyoutae Park, Seungho Han, Byungduk Kim, Youngdo Jo, Yongsop Shim, Yeonjae Lee, Sangguk Ahn, Hiesik Kim, Jungil Park

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In this paper, we presented not only development technology of an explosion proof type and portable combustible gas leak detector but also algorithm to improve accuracy for measuring gas concentrations. The presented techniques are to apply the flame-proof enclosure and intrinsic safe explosion proof to an infrared gas leak detector at first in Korea and to improve accuracy using linearization recursion equation and Lagrange interpolation polynomial. Together, we tested sensor characteristics and calibrated suitable input gases and output voltages. Then, we advanced the performances of combustible gaseous detectors through reflecting demands of gas safety management fields. To check performances of two company's detectors, we achieved the measurement tests with eight standard gases made by Korea Gas Safety Corporation. We demonstrated our instruments better in detecting accuracy other than detectors through experimental results.

Keywords: accuracy improvement, IR gas sensor, gas leak, detector

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Authors: Francisca Margarita Ocran

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Underwear, and more particularly bras and panties, are defined as intimate clothing. Strictly speaking, they enhance the place of women in the public or private satchel. Therefore, women's lingerie is a complex garment with a high involvement profile, motivating consumers to buy it not only by its functional utility but also by the multisensory experience it provides them. Customer behavior models are generally based on customer data mining, and each model is designed to answer questions at a specific time. Predicting the customer experience is uncertain and difficult. Thus, knowledge of consumers' tastes in lingerie deserves to be treated as an experiential product, where the dimensions of the experience motivating consumers to buy a lingerie product and to remain faithful to it must be analyzed in detail by the manufacturers and retailers to engage and retain consumers, which is why this research aims to identify the variables that push consumers to choose their lingerie product, based on an in-depth analysis of the types of fabrics used to make lingerie. The data used in this study comes from online purchases. Machine learning approach with the use of Python programming language and Pycaret gives us a precision of 86.34%, 85.98%, and 84.55% for the three algorithms to use concerning the preference of a buyer in front of a range of lingerie. Gradient Boosting, random forest, and K Neighbors were used in this study; they are very promising and rich in the classification of preference in the textile industry.

Keywords: consumer behavior, data mining, lingerie, machine learning, preference

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Authors: Majdah Alnefaie

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The ‘netnographic study’ and data mining have been used to monitor the public interaction on Social Media Sites (SMSs) to understand what the motivational factors influence the Saudi intentions regarding allowing women driving in Saudi Arabia in 2018. The netnographic study monitored the publics’ textual and visual communications in Twitter, Snapchat, and YouTube. SMSs users’ communications method is also known as electronic word of mouth (eWOM). Netnography methodology is still in its initial stages as it depends on manual extraction, reading and classification of SMSs users text. On the other hand, data mining is come from the computer and physical sciences background, therefore it is much harder to extract meaning from unstructured qualitative data. In addition, the new development in data mining software does not support the Arabic text, especially local slang in Saudi Arabia. Therefore, collaborations between social and computer scientists such as ‘netnographic study’ and data mining will enhance the efficiency of this study methodology leading to comprehensive research outcome. The eWOM communications between individuals on SMSs can promote a sense that sharing their preferences and experiences regarding politics and social government regulations is a part of their daily life, highlighting the importance of using SMSs as assistance in promoting participation in political and social. Therefore, public interactions on SMSs are important tools to comprehend people’s intentions regarding the new government regulations in the country. This study aims to answer this question, "What factors influence the Saudi Arabians' intentions of Saudi female's car-driving in 2018". The study utilized qualitative method known as netnographic study. The study used R studio to collect and analyses 27000 Saudi users’ comments from 25th May until 25th June 2018. The study has developed data collection model that support importing and analysing the Arabic text in the local slang. The data collection model in this study has been clustered based on different type of social networks, gender and the study main factors. The social network analysis was employed to collect comments from SMSs owned by governments’ originations, celebrities, vloggers, social activist and news SMSs accounts. The comments were collected from both males and females SMSs users. The sentiment analysis shows that the total number of positive comments Saudi females car driving was higher than negative comments. The data have provided the most important factors influenced the Saudi Arabians’ intention of Saudi females car driving including, culture and environment, freedom of choice, equal opportunities, security and safety. The most interesting finding indicted that women driving would play a role in increasing the individual freedom of choice. Saudi female will be able to drive cars to fulfill her daily life and family needs without being stressed due to the lack of transportation. The study outcome will help Saudi government to improve woman quality of life by increasing the ability to find more jobs and studies, increasing income through decreasing the spending on transport means such as taxi and having more freedom of choice in woman daily life needs. The study enhances the importance of using use marketing research to measure the public opinions on the new government regulations in the country. The study has explained the limitations and suggestions for future research.

Keywords: netnographic study, data mining, social media, Saudi Arabia, female driving

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

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Beta-glucosidase, chitinase, leucine-aminopeptidase, acid phosphomonoestearse and acetate-esterase enzyme activities in the soils under the impact of metallurgical industrial activity in Lori marz (district) were investigated. The results of the study showed that the activities of the investigated enzymes in the soils decreased with increasing distance from the Shamlugh copper mine, the Chochkan tailings storage facility and the ore transportation road. Statistical analysis revealed that the activities of the enzymes were positively correlated (significant) to each other according to the observation sites which indicated that enzyme activities were affected by the same anthropogenic factor. The investigations showed that the soils were polluted with heavy metals (Cu, Pb, As, Co, Ni, Zn) due to copper mining activity in this territory. The results of Pearson correlation analysis revealed a significant negative correlation between heavy metal pollution degree (Nemerow integrated pollution index) and soil enzyme activity. All of this indicated that copper mining activity in this territory causing the heavy metal pollution of the soils resulted in the inhabitation of the activities of the enzymes which are considered as biological catalysts to decompose organic materials and facilitate the cycling of nutrients.

Keywords: Armenia, metallurgical industrial activity, heavy metal pollutionl, soil enzyme activity

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Authors: Jegede Oluseye Oladayo

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The study mapped innovation activities in the formal and informal mining sector in Nigeria. Data were collected through primary and secondary sources. Primary data were collected through guided questionnaire administration, guided interviews and personal observation. A purposive sampling method was adopted to select firms that are micro, small and medium enterprises. The study covered 100 (50 in the formal sector and 50 in the informal sector) purposively selected companies in south-western Nigeria. Secondary data were collected from different published sources. Data were analysed using descriptive and inferential statistics. Of the four types of technological innovations sampled, organisational innovation was found to be highest both in the formal (100%) and informal (100%) sectors, followed by process innovation: 60% in the formal sector and 28% in the informal sector, marketing innovation and diffusion based innovation were implemented by 64% and 4% respectively in the formal sector. There were no R&D activities (intramural or extramural) in both sectors, however, innovation activities occur at moderate levels in the formal sector. This is characterised by acquisition of machinery, equipment, hardware (100%), software (56), training (82%) and acquisition of external knowledge (60%) in the formal sector. In the informal sector, innovation activities were characterised by acquisition of external knowledge (100%), training/learning by experience (100%) and acquisition of tools (68%). The impact of innovation on firm’s performance in the formal sector was expressed mainly as increased capacity of production (100%), reduced production cost per unit of labour (88%), compliance with governmental regulatory requirements (72%) and entry on new markets (60%). In the informal sector, the impact of innovation was mainly expressed in improved flexibility of production (70%) and machinery/energy efficiency (70%). The important technological driver of process innovation in the mining sector was acquisition of machinery which accounts for the prevalence of 100% both in the formal and informal sectors. Next to this is training and re-training of technical staff, 74% in both the formal and the informal sector. Other factors influencing organisational innovation are skill of workforce with a prevalence of 80% in both the formal and informal sector. The important technological drivers include educational background of the manager/head of technical department (54%) for organisational innovation and (50%) for process innovation in the formal sector. The study concluded that innovation competence of the firms was mostly organisational changes.

Keywords: innovation prevalence, innovation activities, innovation performance, innovation drivers

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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: C. -L. Huang, J. -H. Ho

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Social media has become more and more important in our life. Many enterprises promote their services and products to fans via the social media. The positive or negative sentiment of feedbacks from fans is very important for enterprises to improve their products, services, and promotion activities. The purpose of this paper is to understand the sentiment of the fan’s responses by analyzing the responses posted by fans on Facebook. The entity and aspect of fan’s responses were analyzed based on a predefined ontology. The ontology for cell phone sentiment analysis consists of aspect categories on the top level as follows: overall, shape, hardware, brand, price, and service. Each category consists of several sub-categories. All aspects for a fan’s response were found based on the ontology, and their corresponding sentimental terms were found using lexicon-based approach. The sentimental scores for aspects of fan responses were obtained by summarizing the sentimental terms in responses. The frequency of 'like' was also weighted in the sentimental score calculation. Three famous cell phone fan pages on Facebook were selected as demonstration cases to evaluate performances of the proposed methodology. Human judgment by several domain experts was also built for performance comparison. The performances of proposed approach were as good as those of human judgment on precision, recall and F1-measure.

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

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Authors: Alissa Jane S. Mondejar, Florifern C. Paglinawan, Nanette Hope N. Sumaya, Joey Genevieve T. Martinez, Mylah Villacorte-Tabelin

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Mining is associated with increased heavy metals in the environment, and heavy metal contamination disrupts the activities of soil fauna, such as nematodes, causing changes in the function of the soil ecosystem. Previous studies found that nematode community composition and diversity indices were strongly affected by heavy metals (e.g., Pb, Cu, and Zn). In this study, the influence of heavy metals on nematode survivability and reproduction were investigated. Life history analysis of the free-living nematodes, Heterocephalobellus sp. and Cephalobus sp. (Rhabditida: Cephalobidae) were assessed using the hanging drop technique, a technique often used in life history trait experiments. The nematodes were exposed to different temperatures, i.e.,20°C, 25°C, and 30°C, in different groups (control and heavy metal exposed) and fed with the same bacterial density of 1×109 Escherichia coli cells ml-1 for 30 days. Results showed that increasing temperature and exposure to heavy metals had a significant influence on the survivability and egg production of both species. Heterocephalobellus sp. and Cephalobus sp., when exposed to 20°C survived longer and produced few numbers of eggs but without subsequent hatching. Life history parameters of Heterocephalobellus sp. showed that the value of parameters was higher in the control group under net production rate (R0), fecundity (mx) which is also the same value for the total fertility rate (TFR), generation times (G0, G₁, and Gh) and Population doubling time (PDT). However, a lower rate of natural increase (rm) was observed since generation times were higher. Meanwhile, the life history parameters of Cephalobus sp. showed that the value of net production rate (R0) was higher in the exposed group. Fecundity (mx) which is also the same value for the TFR, G0, G1, Gh, and PDT, were higher in the control group. However, a lower rate of natural increase (rm) was observed since generation times were higher. In conclusion, temperature and exposure to heavy metals had a negative influence on the life history of the nematodes, however, further experiments should be considered.

Keywords: artisanal and small-scale gold mining (ASGM), hanging drop method, heavy metals, life history trait.

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Authors: Md. Musfiqur Rahman Bhuiya Nidalia Islam, Hossain Mohiuddin, Md. Kawser Bin Zaman

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Dhaka North City Corporation introduced first area-based bus service on 10 August 2016 to run through Gulshan and Banani area to dilute sufferings of the people which started with the ban on movement of the bus in these areas after Holy Artisan terrorist attack. This study explores service quality performance of Dhaka Chaka on the basis of information provided by its riders on a questionnaire survey. Total thirteen service quality indicators have been ranked on a scale of 1-5, and they have been classified under three latent variables based on their correlation using eigenvalue and rotated factor matrix derived through factor analysis process. Mean, and skewness has been calculated for each indicator. It has been found that ticket price and ticketing system have relatively poor average service quality rank than other factors. All other factors have moderately good performance. The study also suggests some recommendation to improve service quality of Dhaka Chaka based on the interrelation between considered parameters.

Keywords: area based bus service, eigen value, factor analysis, correlation

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Authors: Sherly M. A., Varsha Vijaykumar, Subhankar Karmakar, Terence Chan, Christian Rau

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This study aims at proposing an indicator-based framework for assessing social vulnerability of any coastal megacity to floods. The final set of indicators of social vulnerability are chosen from a set of feasible and available indicators which are prepared using a Geographic Information System (GIS) framework on a smaller scale considering 1-km grid cell to provide an insight into the spatial variability of vulnerability. The optimal weight for each individual indicator is assigned using data envelopment analysis (DEA) as it avoids subjective weights and improves the confidence on the results obtained. In order to de-correlate and reduce the dimension of multivariate data, principal component analysis (PCA) has been applied. The proposed methodology is demonstrated on twenty four wards of Mumbai under the jurisdiction of Municipal Corporation of Greater Mumbai (MCGM). This framework of vulnerability assessment is not limited to the present study area, and may be applied to other urban damage centers.

Keywords: urban floods, vulnerability, data envelopment analysis, principal component analysis

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Authors: Constâncio Augusto Machanguana

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The world over, resettling communities, for whatever purpose (mining, dams, forestry and wildlife management, roads, or facilitating services delivery), often leads to tensions between those resettled, the investors, and the local and national governments involved in the process. Causes include unclear government legislation and regulations, confusing Corporate Social Responsibility policies and guidelines, and other social-economic policies leading to unrealistic expectations among those being resettled, causing frustrations within the community, shifting them to any imminent conflict against the investors (company). The exploitation of heavy mineral sands along Mozambique’s long coastline and hinterland has not been providing a benefit for the affected communities. A case in point is the exploration, since 2018, of heavy sands in Chibuto District in the Southern Province of Gaza. A likely contributing factor is the standard type of socio-economic surveys and community involvement processes that could smooth the relationship among the parties. This research aims to investigate alternative processes to plan, initiate and guide resettlement processes in such a way that tensions and conflicts are avoided. Based on the process already finished, compared to similar cases along with the country, mixed methods to collect primary data were adopted: three focus groups of 125 people, representing 324 resettled householders; five semi-structured interviews with relevant stakeholders such as the local government, NGO’s and local leaders to understand their role in all stages of the process. The preliminary results show that the community has limited or no understanding of the potential impacts of these large-scale explorations, and the apparent harmony between the parties (community and company) may hide the dissatisfaction of those resettled. So, rather than focusing on negative mining impacts, the research contributes to science by identifying the best resettlement approach that can be replicated in other contexts along with the country in the actual context of the new discovery of mineral resources.

Keywords: conflict mitigation, resettlement, mining, Mozambique

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Authors: Grace O. Akinlade, Danjuma D. Maza, Oluwakemi O. Olawolu, Delight O. Babalola, John A. O. Oyekunle, Joshua O. Ojo

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The Mokuro area of Ile-Ife, South West Nigeria, was well known for gold mining in the past (about twenty years ago). However, the place has since been reclaimed and converted to residential area without any environmental risk assessment of the impact of the mining tailings on the environment. Soil, water, and plant samples were collected from 4 different locations around the mine-turned-residential area. Soil samples were pulverized and sieved into finer particles, while the plant samples were dried and pulverized. All the samples were digested and analyzed for As, Pb, Cd, and Zn using atomic absorption spectroscopy (AAS). From the analysis results, the hazard index (HI) was then calculated for the metals. The soil and plant samples were air dried and pulverized, then weighed, after which the samples were packed into special and properly sealed containers to prevent radon gas leakage. After the sealing, the samples were kept for 28 days to attain secular equilibrium. The concentrations of 40K, 238U, and 232Th in the samples were measured using a cesium iodide (CsI) spectrometer and URSA software. The AAS analysis showed that As, Pb, Cd (Toxic metals), and Zn (essential trace metals) are in concentrations lower than permissible limits in plants and soil samples, while the water samples had concentrations higher than permissible limits. The calculated health indices (HI) show that HI for water is >1 and that of plants and soil is <1. Gamma spectrometry result shows high levels of activity concentrations above the recommended limits for all the soil and plant samples collected from the area. Only the water samples have activity concentrations below the recommended limit. Consequently, the absorbed dose, annual effective dose, and excess lifetime cancer risk are all above the recommended safe limit for all the samples except for water samples. In conclusion, all the samples collected from the area are either contaminated with toxic metals or they pose radiological hazards to the consumers. Further detailed study is therefore recommended in order to be able to advise the residents appropriately.

Keywords: toxic metals, gamma spectrometry, Ile-Ife, radiological hazards, gold mining

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Authors: Ashok Kalagura

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This paper presents a data-mining model for fault-zone identification of flexible AC transmission systems (FACTS)-based transmission line including a thyristor-controlled series compensator (TCSC) and unified power-flow controller (UPFC), using ensemble decision trees. Given the randomness in the ensemble of decision trees stacked inside the random forests model, it provides an effective decision on the fault-zone identification. Half-cycle post-fault current and voltage samples from the fault inception are used as an input vector against target output ‘1’ for the fault after TCSC/UPFC and ‘1’ for the fault before TCSC/UPFC for fault-zone identification. The algorithm is tested on simulated fault data with wide variations in operating parameters of the power system network, including noisy environment providing a reliability measure of 99% with faster response time (3/4th cycle from fault inception). The results of the presented approach using the RF model indicate the reliable identification of the fault zone in FACTS-based transmission lines.

Keywords: distance relaying, fault-zone identification, random forests, RFs, support vector machine, SVM, thyristor-controlled series compensator, TCSC, unified power-flow controller, UPFC

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Authors: Ghodhbani Salah, Jemili Farah

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With the growth of cyber attacks, information safety has become an important issue all over the world. Many firms rely on security technologies such as intrusion detection systems (IDSs) to manage information technology security risks. IDSs are considered to be the last line of defense to secure a network and play a very important role in detecting large number of attacks. However the main problem with today’s most popular commercial IDSs is generating high volume of alerts and huge number of false positives. This drawback has become the main motivation for many research papers in IDS area. Hence, in this paper we present a data mining technique to assist network administrators to analyze and reduce false positive alarms that are produced by an IDS and increase detection accuracy. Our data mining technique is unsupervised clustering method based on hybrid ANT algorithm. This algorithm discovers clusters of intruders’ behavior without prior knowledge of a possible number of classes, then we apply K-means algorithm to improve the convergence of the ANT clustering. Experimental results on real dataset show that our proposed approach is efficient with high detection rate and low false alarm rate.

Keywords: intrusion detection system, alarm filtering, ANT class, ant clustering, intruders’ behaviors, false alarms

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Authors: Haidong Li, Weishou Shen, Guoping Lv, Tao Wang

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Aiming to overcome the limitation of the application of traditional remote sensing (RS) technique in the mine eco-environmental monitoring, in this paper, we first classified the eco-environmental damages caused by mining activities and then introduced the principle, classification and characteristics of the Light Detection and Ranging (LiDAR) technique. The potentiality of LiDAR technique in the mine eco-environmental monitoring was analyzed, particularly in extracting vertical structure parameters of vegetation, through comparing the feasibility and applicability of traditional RS method and LiDAR technique in monitoring different types of indicators. The application situation of LiDAR technique in extracting typical mine indicators, such as land destruction in mining areas, damage of ecological integrity and natural soil erosion. The result showed that the LiDAR technique has the ability to monitor most of the mine eco-environmental indicators, and exhibited higher accuracy comparing with traditional RS technique, specifically speaking, the applicability of LiDAR technique on each indicator depends on the accuracy requirement of mine eco-environmental monitoring. In the item of large mine, LiDAR three-dimensional point cloud data not only could be used as the complementary data source of optical RS, Airborne/Satellite LiDAR could also fulfill the demand of extracting vertical structure parameters of vegetation in large areas.

Keywords: LiDAR, mine, ecological damage, monitoring, traditional remote sensing technique

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Authors: Zohra Mekranfar, Ahmed Saidi, Abdellah Mebrek

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This work aims to develop multi-criteria decision making (MCDM) and spatial data warehouse (SDW) methods, which will be integrated into a GIS according to a ‘GIS dominant’ approach. The GIS operating tools will be operational to operate the SDW. The MCDM methods can provide many solutions to a set of problems with various and multiple criteria. When the problem is so complex, integrating spatial dimension, it makes sense to combine the MCDM process with other approaches like data mining, ascending analyses, we present in this paper an experiment showing a geo-decisional methodology of SWD construction, On-line analytical processing (OLAP) technology which combines both basic multidimensional analysis and the concepts of data mining provides powerful tools to highlight inductions and information not obvious by traditional tools. However, these OLAP tools become more complex in the presence of the spatial dimension. The integration of OLAP with a GIS is the future geographic and spatial information solution. GIS offers advanced functions for the acquisition, storage, analysis, and display of geographic information. However, their effectiveness for complex spatial analysis is questionable due to their determinism and their decisional rigor. A prerequisite for the implementation of any analysis or exploration of spatial data requires the construction and structuring of a spatial data warehouse (SDW). This SDW must be easily usable by the GIS and by the tools offered by an OLAP system.

Keywords: data warehouse, GIS, MCDM, SOLAP

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Authors: Farahnaz Sadat Golestan Hashemi, Mohd Razi Ismail, Mohd Y. Rafii

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A huge revolution has emerged in genome engineering by the discovery of CRISPR (clustered regularly interspaced palindromic repeats) and CRISPR-associated system genes (Cas) in bacteria. The function of type II Streptococcus pyogenes (Sp) CRISPR/Cas9 system has been confirmed in various species. Other S. thermophilus (St) CRISPR-Cas systems, CRISPR1-Cas and CRISPR3-Cas, have been also reported for preventing phage infection. The CRISPR1-Cas system interferes by cleaving foreign dsDNA entering the cell in a length-specific and orientation-dependant manner. The S. thermophilus CRISPR3-Cas system also acts by cleaving phage dsDNA genomes at the same specific position inside the targeted protospacer as observed in the CRISPR1-Cas system. It is worth mentioning, for the effective DNA cleavage activity, RNA-guided Cas9 orthologs require their own specific PAM (protospacer adjacent motif) sequences. Activity levels are based on the sequence of the protospacer and specific combinations of favorable PAM bases. Therefore, based on the specific length and sequence of PAM followed by a constant length of target site for the three orthogonals of Cas9 protein, a well-organized procedure will be required for high-throughput and accurate mining of possible target sites in a large genomic dataset. Consequently, we created a reliable procedure to explore potential gRNA sequences for type I (Streptococcus thermophiles), II (Streptococcus pyogenes), and III (Streptococcus thermophiles) CRISPR/Cas systems. To mine CRISPR target sites, four different searching modes of sgRNA binding to target DNA strand were applied. These searching modes are as follows: i) coding strand searching, ii) anti-coding strand searching, iii) both strand searching, and iv) paired-gRNA searching. The output of such procedure highlights the power of comparative genome mining for different CRISPR/Cas systems. This could yield a repertoire of Cas9 variants with expanded capabilities of gRNA design, and will pave the way for further advance genome and epigenome engineering.

Keywords: CRISPR/Cas systems, gRNA mining, Streptococcus pyogenes, Streptococcus thermophiles

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Authors: Linet Melisa Daubanes, Nhleko Monique Chiloane

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The shovel-truck system is the most prevalent material handling system used in surface mining operations. Material handling entails the loading and hauling of material from production areas to dumping areas. The material handling process has operational delays that have a negative impact on the productivity of the load and haul fleet. Factors that may contribute to operational delays include shovel-truck mismatch, haul routes, machine breakdowns, extreme weather conditions, etc. The aim of this paper is to investigate factors that contribute to operational delays affecting the productivity of the load and haul fleet at the mine. Productivity is the measure of the effectiveness of producing products from a given quantity of units, the ratio of output to inputs. Productivity can be improved by producing more outputs with the same or fewer units and/or introducing better working methods etc. Several key performance indicators (KPI) for the evaluation of productivity will be discussed in this study. These KPIs include but are not limited to hauling conditions, bucket fill factor, cycle time, and utilization. The research methodology of this study is a combination of on-site time studies and observations. Productivity can be optimized by managing the factors that affect the operational performance of the haulage fleet.

Keywords: cycle time, fleet performance, load and haul, surface mining

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Authors: S. R. H. Baqri, T. Shahina, M. T. Hasan

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Pakistan is facing acute shortage of energy and looking for indigenous resources of the energy mix to meet the short fall. After the discovery of huge coal resources in Thar Desert of Sindh province, focus has shifted to coal power generation. The government of Pakistan has planned power generation of 20000 MW on coal by the year 2025. This target will be achieved by mining and power generation in Thar coal Field and on imported coal in different parts of Pakistan. Total indigenous coal production of around 3.0 million tons is being utilized in brick kilns, cement and sugar industry. Coal-based power generation is only limited to three units of 50 MW near Hyderabad from nearby Lakhra Coal field. The purpose of this presentation is to identify and redressal of issues of coal mining and utilization with reference to environmental hazards. Thar coal resource is estimated at 175 billion tons out of a total resource estimate of 184 billion tons in Pakistan. Coal of Pakistan is of Tertiary age (Palaeocene/Eocene) and classified from lignite to sub-bituminous category. Coal characterization has established three main pollutants such as Sulphur, Carbon dioxide and Methane besides some others associated with coal and rock types. The element Sulphur occurs in organic as well as inorganic forms associated with coals as free sulphur and as pyrite, gypsum, respectively. Carbon dioxide, methane and minerals are mostly associated with fractures, joints local faults, seatearth and roof rocks. The abandoned and working coal mines give kerosene odour due to escape of methane in the atmosphere. While the frozen methane/methane ices in organic matter rich sediments have also been reported from the Makran coastal and offshore areas. The Sulphur escapes into the atmosphere during mining and utilization of coal in industry. The natural erosional processes due to rivers, streams, lakes and coastal waves erode over lying sediments allowing pollutants to escape into air and water. Power plants emissions should be controlled through application of appropriate clean coal technology and need to be regularly monitored. Therefore, the systematic and scientific studies will be required to estimate the quantity of methane, carbon dioxide and sulphur at various sites such as abandoned and working coal mines, exploratory wells for coal, oil and gas. Pressure gauges on gas pipes connecting the coal-bearing horizons will be installed on surface to know the quantity of gas. The quality and quantity of gases will be examined according to the defined intervals of times. This will help to design and recommend the methods and procedures to stop the escape of gases into atmosphere. The element of Sulphur can be removed partially by gravity and chemical methods after grinding and before industrial utilization of coal.

Keywords: atmosphere, coal production, energy, pollutants

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Authors: Pei Zhao, Sara Sintonen, Heikki Kynäslahti

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Digital museums and arts galleries have become popular in museum education and management. Museum and arts galleries website is one of the most effective and efficient ways. Google, a corporation specializing in Internet-related services and projects, not only puts high-resolution arts images online, but also uses augmented-reality in digital art gallery. The Google Art Project, Google’s production, provides users a platform in appreciating and learning arts. After Google Art Project, more and more countries released their own museum and arts gallery websites, like British Paining in BBC, and FINNA in Finland. Pedagogical function in these websites is one of the most important functions. In this paper, we use Google Art Project and FINNA as the case studies to investigate what kinds of pedagogical functions exist in these websites. Finally, this paper will give the recommendation to digital museums and websites development, especially the pedagogical functions development, in the future.

Keywords: arts education, cultural-heritage education, education with ICTs, pedagogical functions

Procedia PDF Downloads 527

Authors: Eunjung Lee

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This research investigates the intricate connection between cultural differences and online consumer behaviors by integrating Hofstede's Cultural Dimensions theory with analysis methodologies such as text mining, data mining, and topic analysis. Our aim is to provide a comprehensive understanding of how national cultural differences influence individuals' behaviors when engaging with online reviews. To ensure the relevance of our investigation, we systematically analyze and interpret the cultural nuances influencing online consumer behaviors, especially in the context of online reviews. By anchoring our research in Hofstede's Cultural Dimensions theory, we seek to offer valuable insights for marketers to tailor their strategies based on the cultural preferences of diverse global consumer bases. In our methodology, we employ advanced text mining techniques to extract insights from a diverse range of online reviews gathered globally for a specific product or service like Netflix. This approach allows us to reveal hidden cultural cues in the language used by consumers from various backgrounds. Complementing text mining, data mining techniques are applied to extract meaningful patterns from online review datasets collected from different countries, aiming to unveil underlying structures and gain a deeper understanding of the impact of cultural differences on online consumer behaviors. The study also integrates topic analysis to identify recurring subjects, sentiments, and opinions within online reviews. Marketers can leverage these insights to inform the development of culturally sensitive strategies, enhance target audience segmentation, and refine messaging approaches aligned with cultural preferences. Anchored in Hofstede's Cultural Dimensions theory, our research employs sophisticated methodologies to delve into the intricate relationship between cultural differences and online consumer behaviors. Applied to specific cultural dimensions, such as individualism vs. collectivism, masculinity vs. femininity, uncertainty avoidance, and long-term vs. short-term orientation, the study uncovers nuanced insights. For example, in exploring individualism vs. collectivism, we examine how reviewers from individualistic cultures prioritize personal experiences while those from collectivistic cultures emphasize communal opinions. Similarly, within masculinity vs. femininity, we investigate whether distinct topics align with cultural notions, such as robust features in masculine cultures and user-friendliness in feminine cultures. Examining information-seeking behaviors under uncertainty avoidance reveals how cultures differ in seeking detailed information or providing succinct reviews based on their comfort with ambiguity. Additionally, in assessing long-term vs. short-term orientation, the research explores how cultural focus on enduring benefits or immediate gratification influences reviews. These concrete examples contribute to the theoretical enhancement of Hofstede's Cultural Dimensions theory, providing a detailed understanding of cultural impacts on online consumer behaviors. As online reviews become increasingly crucial in decision-making, this research not only contributes to the academic understanding of cultural influences but also proposes practical recommendations for enhancing online review systems. Marketers can leverage these findings to design targeted and culturally relevant strategies, ultimately enhancing their global marketing effectiveness and optimizing online review systems for maximum impact.

Keywords: comparative analysis, cultural dimensions, marketing intelligence, national culture, online consumer behavior, text mining

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Authors: Zahid O. Alibrahim, Craig D. Williams, Clive L. Roberts

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The study area (Ecton mining area) is located in the southern part of the Peak District in Derbyshire, England. It is bounded by the River Manifold from the west. This area has been mined for a long period. As a result, huge amounts of potentially toxic metals were released into the surrounding area and are most likely to be a significant source of heavy metal contamination to the local soil, water and vegetation. In order to appraise the potential heavy metal pollution in this area, 37 topsoil samples (5-20 cm depth) were collected and analysed for their total content of Cu, Pb, Zn, Mn, Cr, Ni and V using ICP (Inductively Coupled Plasma) optical emission spectroscopy. Multivariate Geospatial analyses using the GIS technique were utilised to draw geochemical maps of the metals of interest over the study area. A few hotspot points, areas of elevated concentrations of metals, were specified, which are presumed to be the results of anthropogenic activities. In addition, the soil’s environmental quality was evaluated by calculating the Mullers’ Geoaccumulation index (I geo), which suggests that the degree of contamination of the investigated heavy metals has the following trend: Pb > Zn > Cu > Mn > Ni = Cr = V. Furthermore, the potential ecological risk, using the enrichment factor (EF), was also specified. On the basis of the calculated amount or the EF, the levels of pollution for the studied metals in the study area have the following order: Pb>Zn>Cu>Cr>V>Ni>Mn.

Keywords: enrichment factor, geoaccumulation index, GIS, heavy metals, multivariate analysis

Procedia PDF Downloads 335

Authors: K. Umbleja, M. Ichino

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Symbolic data mining has been developed to analyze data in very large datasets. It is also useful in cases when entry specific details should remain hidden. Symbolic data mining is quickly gaining popularity as datasets in need of analyzing are becoming ever larger. One type of such symbolic data is a histogram, which enables to save huge amounts of information into a single variable with high-level of granularity. Other types of symbolic data can also be described in histograms, therefore making histogram a very important and general symbolic data type - a method developed for histograms - can also be applied to other types of symbolic data. Due to its complex structure, analyzing histograms is complicated. This paper proposes a method, which allows to compare two histogram-valued variables and therefore find a dissimilarity between two histograms. Proposed method uses the Ichino-Yaguchi dissimilarity measure for mixed feature-type data analysis as a base and develops a dissimilarity measure specifically for histogram data, which allows to compare histograms with different number of bins and bin widths (so called general histogram). Proposed dissimilarity measure is then used as a measure for clustering. Furthermore, linkage method based on weighted averages is proposed with the concept of cluster compactness to measure the quality of clustering. The method is then validated with application on real datasets. As a result, the proposed dissimilarity measure is found producing adequate and comparable results with general histograms without the loss of detail or need to transform the data.

Keywords: dissimilarity measure, hierarchical clustering, histograms, symbolic data analysis

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Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

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Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: artificial neural network, data mining, electroencephalogram, epilepsy, feature extraction, seizure detection, signal processing

Procedia PDF Downloads 166