Search results for: open cast coal mining

Authors: S.V. Kleyn, S.Yu. Zagorodnov, А.А. Kokoulina

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Technogenic emissions of the mining and processing complex are characterized by a high content of chemical components and solid dust particles. However, each industrial enterprise and the surrounding area have features that require refinement and parameterization. Numerous studies have shown the negative impact of fine dust PM10 and PM2.5 on the health, as well as the possibility of toxic components absorption, including heavy metals by dust particles. The target of the study was the quantitative assessment of the fractional and particle size composition of ambient air dust in the area of impact by primary magnesium production complex. Also, we tried to describe the morphology features of dust particles. Study methods. To identify the dust emission sources, the analysis of the production process has been carried out. The particulate composition of the emissions was measured using laser particle analyzer Microtrac S3500 (covered range of particle size is 20 nm to 2000 km). Particle morphology and the component composition were established by electron microscopy by scanning microscope of high resolution (magnification rate - 5 to 300 000 times) with X-ray fluorescence device S3400N ‘HITACHI’. The chemical composition was identified by X-ray analysis of the samples using an X-ray diffractometer XRD-700 ‘Shimadzu’. Determination of the dust pollution level was carried out using model calculations of emissions in the atmosphere dispersion. The calculations were verified by instrumental studies. Results of the study. The results demonstrated that the dust emissions of different technical processes are heterogeneous and fractional structure is complicated. The percentage of particle sizes up to 2.5 micrometres inclusive was ranged from 0.00 to 56.70%; particle sizes less than 10 microns inclusive – 0.00 - 85.60%; particle sizes greater than 10 microns - 14.40% -100.00%. During microscopy, the presence of nanoscale size particles has been detected. Studied dust particles are round, irregular, cubic and integral shapes. The composition of the dust includes magnesium, sodium, potassium, calcium, iron, chlorine. On the base of obtained results, it was performed the model calculations of dust emissions dispersion and establishment of the areas of fine dust РМ 10 and РМ 2.5 distribution. It was found that the dust emissions of fine powder fractions PM10 and PM2.5 are dispersed over large distances and beyond the border of the industrial site of the enterprise. The population living near the enterprise is exposed to the risk of diseases associated with dust exposure. Data are transferred to the economic entity to make decisions on the measures to minimize the risks. Exposure and risks indicators on the health are used to provide named patient health and preventive care to the citizens living in the area of negative impact of the facility.

Keywords: dust emissions, еxposure assessment, PM 10, PM 2.5

Procedia PDF Downloads 261

Authors: Nidesh Sapkota, Garima Pudasaini, Dikshya Agrawal, Binav Baral, Umesh Bhagat, Dharanidhar Baral

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Background: Medical and Dental students are vulnerable to higher levels of Psychological distress than other age matched peers. Many studies reveals that there is high prevalence of psychoactive substance use and Psychiatric co-morbidities among them. Objectives: -To study the prevalence of substance use among medical and dental students of a Medical University. -To study the prevalence of depression and anxiety in medical and dental students of a Medical University. Materials and Method: A cross-sectional descriptive study in which simple random sampling was done. Semi-structured questionnaire, AUDIT for alcohol use, Fagerstrom test for Nicotine dependence, Cannabis screening test (CAST), Beck’s Depression Inventory (BDI), Beck’s Anxiety Inventory (BAI) were used for the assessment. Results: Total sample size was 588 in which the mean age of participants was 22±2years. Among them the prevalence of alcohol users was 47.75%(281) in which 32%(90) were harmful users. Among 19.55%(115) nicotine users 56.5%(65), 37.4%(43), 6.1%(7) had low, low to moderate and moderate dependence respectively. The prevalence of cannabis users was 9%(53) with 45.3%(24), 18.9%(10) having low and high addiction respectively. Depressive symptoms were recorded in 25.3%(149) out of which 12.6%(74), 6.5%(38), 5.3%(31), 0.5%(3), 0.5%(3) had mild, borderline, moderate, severe and extreme depressive symptoms respectively. Similarly anxiety was recorded among 7.8%(46) students with 42 having moderate and 4 having severe anxiety symptoms. Among them 6.3%(37) had suicidal thoughts and 4(0.7%) of them had suicide attempt in last one year. Statistically significant association was noted with harmful alcohol users, Depression and suicidal attempts. Similar association was noted between Depression and suicide with moderate use of nicotine. Conclusion: There is high prevalence of Psychoactive substance use and psychiatric co-morbidities noted in the studies sample. Statistically significant association was noted with Psychiatric co-morbidities and substance use.

Keywords: alcohol, cannabis, dependence, depression, medical students

Procedia PDF Downloads 469

Authors: Yogesh Kumar Singh, T. S. Murugesh Prabhu, Upasana Dutta, Girishchandra Yendargaye, Rahul Yadav, Rohini Gopinath Kale, Binay Kumar, Manoj Khare

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The Indian subcontinent is severely affected by floods that cause intense irreversible devastation to crops and livelihoods. With increased incidences of floods and their related catastrophes, an Early Warning System for Flood Prediction and an efficient Flood Management System for the river basins of India is a must. Accurately modeled hydrological conditions and a web-based early warning system may significantly reduce economic losses incurred due to floods and enable end users to issue advisories with better lead time. This study describes the design and development of an EWS-FP using advanced computational tools/methods, viz. High-Performance Computing (HPC), Remote Sensing, GIS technologies, and open-source tools for the Mahanadi River Basin of India. The flood prediction is based on a robust 2D hydrodynamic model, which solves shallow water equations using the finite volume method. Considering the complexity of the hydrological modeling and the size of the basins in India, it is always a tug of war between better forecast lead time and optimal resolution at which the simulations are to be run. High-performance computing technology provides a good computational means to overcome this issue for the construction of national-level or basin-level flash flood warning systems having a high resolution at local-level warning analysis with a better lead time. High-performance computers with capacities at the order of teraflops and petaflops prove useful while running simulations on such big areas at optimum resolutions. In this study, a free and open-source, HPC-based 2-D hydrodynamic model, with the capability to simulate rainfall run-off, river routing, and tidal forcing, is used. The model was tested for a part of the Mahanadi River Basin (Mahanadi Delta) with actual and predicted discharge, rainfall, and tide data. The simulation time was reduced from 8 hrs to 3 hrs by increasing CPU nodes from 45 to 135, which shows good scalability and performance enhancement. The simulated flood inundation spread and stage were compared with SAR data and CWC Observed Gauge data, respectively. The system shows good accuracy and better lead time suitable for flood forecasting in near-real-time. To disseminate warning to the end user, a network-enabled solution is developed using open-source software. The system has query-based flood damage assessment modules with outputs in the form of spatial maps and statistical databases. System effectively facilitates the management of post-disaster activities caused due to floods, like displaying spatial maps of the area affected, inundated roads, etc., and maintains a steady flow of information at all levels with different access rights depending upon the criticality of the information. It is designed to facilitate users in managing information related to flooding during critical flood seasons and analyzing the extent of the damage.

Keywords: flood, modeling, HPC, FOSS

Procedia PDF Downloads 89

Authors: Elham Azimzadeh, Saeedeh Sepehri, Hamidollah Hassanlouei

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Obesity is associated with postural instability, might influence the quality of daily life, and could be considered a potential factor for falling in obese people. The fat body mass especially in the abdominal area may increase body sway. Furthermore, loss of visual feedback may induce a larger postural sway in obese people. Moreover, Muscle fatigue may impair the work capacity of the skeletal muscle and may alter joint proprioception. So, the purpose of this study was to investigate the effect of physical fatigue and visual feedback on body sway and strength of lower extremities in obese people. 12 obese (4 female, 8 male; BMI >30 kg/m2), and 12 normal weight (4 female, 8 male; BMI: 20-25 kg/m2) subjects aged 37- 47 years participated in this study. The postural stability test on the Biodex balance system was used to characterize postural control along the anterior-posterior (AP) and mediolateral (ML) directions in eyes open and eyes closed conditions and maximal voluntary contraction (MVC) of knee extensors and flexors were measured before and after the high-intensity exhausting exercise protocol on the ergometer bike to confirm the presence of fatigue. Results indicated that the obese group demonstrated significantly greater body sway, in all indices (ML, AP, overall) compared with the normal weight group (eyes open). However, when visual feedback was eliminated, fatigue impaired the balance in the overall and AP indicators in both groups; ML sway was higher only in the obese group after exerting the fatigue in the eyes closed condition. Also, maximal voluntary contraction of knee extensors was impaired in the fatigued normal group but, there was no significant impairment in knee flexors MVC in both group. According to the findings, peripheral fatigue was associated with altered postural control in upright standing when eyes were closed, and that mechanoreceptors of the feet may be less able to estimate the position of the body COM over the base of support in the loss of visual feedback. This suggests that the overall capability of the postural control system during upright standing especially in the ML direction could be lower due to fatigue in obese individuals and could be a predictor of future falls.

Keywords: maximal voluntary contraction, obesity, peripheral fatigue, postural control, visual feedback

Procedia PDF Downloads 92

Authors: Mohammad Arshad Ikram

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We report three cases of challenging fractures in children treated by intramedullary fixation using the Metaizeau method and achieved anatomical reduction with excellent clinical results. Jean-Paul Metaizeau described the centromedullary fixation for the radial neck in 1980 using K-wires Radial neck fractures are uncommon in children. Treatment of severely displaced fractures is always challenging. Closed reduction techniques are more popular as compared to open reduction due to the low risk of complications. Metaizeau technique of closed reduction with centromedullary pinning is a commonly preferred method of treatment. We present two cases with a severely displaced radial neck fracture, treated by this method and achieved sound union; anatomical position of the radial head and full function were observed two months after surgery. Proximal humerus fractures are another uncommon injury in children accounting for less than 5% of all pediatric fractures. Most of these injuries occur through the growth plate because of its relative weakness. Salter-Harris type I is commonly seen in the younger age group, whereas type II & III occurs in older children and adolescents. In contrast to adults, traumatic glenohumeral dislocation is an infrequently observed condition among children. A combination of proximal humerus fracture and glenohumeral dislocation is extremely rare and occurs in less than 2% of the pediatric population. The management of this injury is always challenging. Treatment ranged from closed reduction with and without internal fixation and open reduction with internal fixation. The children who had closed reduction with centromedullary fixation by the Metaizeau method showed excellent results with the return of full movements at the shoulder in a short time without any complication. We present the case of a child with anterior dislocation of the shoulder associated with a complete displaced proximal humerus metaphyseal fracture. The fracture was managed by closed reduction and then fixation by two centromedullary K-wires using the Metaizeau method, achieving the anatomical reduction of the fracture and dislocation. This method of treatment enables us to achieve excellent radiological and clinical results in a short time.

Keywords: glenohumeral, Metaizeau method, pediatric fractures, radial neck

Procedia PDF Downloads 105

Authors: J-C. Leneveu, A. Chereau, L. Mansart, T. Mesbah, M. Wyka

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Extracting and interpreting information from Big Data represent a stake for years to come in several sectors such as finance. Currently, numerous methods are used (such as Technical Analysis) to try to understand and to anticipate market behavior, with mixed results because it still seems impossible to exactly predict a financial trend. The increase of available data on Internet and their diversity represent a great opportunity for the financial world. Indeed, it is possible, along with these standard financial data, to focus on exogenous data to take into account more macroeconomic factors. Coupling the interpretation of these data with standard methods could allow obtaining more precise trend predictions. In this paper, in order to observe the influence of exogenous data price independent of other usual effects occurring in classical markets, behaviors of Bitcoin users are introduced in a model reconstituting Bitcoin value, which is elaborated and tested for prediction purposes.

Keywords: big data, bitcoin, data mining, social network, financial trends, exogenous data, global economy, behavioral finance

Procedia PDF Downloads 355

Authors: Sachin Pawar, Suman Patra, Goutam Mukhopadhyay

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The primary function of a shaft is to transfer power. The shaft can be cast or forged and then machined to the final shape. Manufacturing of ~5 m length and 0.6 m diameter shaft is very critical. More difficult is to maintain its straightness during heat treatment and machining operations, which involve thermal and mechanical loads, respectively. During the machining operation of a such forged mandrel shaft, a deflection of 3-4mm was observed. To remove this deflection shaft was pressed at both ends which led to the development of cracks in it. To investigate the root cause of the deflection and cracking, the sample was cut from the failed shaft. Possible causes were identified with the help of a cause and effect diagram. Chemical composition analysis, microstructural analysis, and hardness measurement were done to confirm whether the shaft meets the required specifications or not. Chemical composition analysis confirmed that the material grade was 42CrMo4. Microstructural analysis revealed the presence of untempered martensite, indicating improper heat treatment. Due to this, ductility and impact toughness values were considerably lower than the specification of the mentioned grade. Residual stress measurement of one more bent shaft manufactured by a similar route was done by portable X-ray diffraction(XRD) technique. For better understanding, measurements were done at twelve different locations along the length of the shaft. The occurrence of a high amount of undesirable tensile residual stresses close to the Ultimate Tensile Strength(UTS) of the material was observed. Untempered martensitic structure, lower ductility, lower impact strength, and presence of a high amount of residual stresses all confirmed the improper tempering heat treatment of the shaft. Tempering relieves the residual stresses. Based on the findings of this study, stress-relieving heat treatment was done to remove the residual stresses and deflection in the shaft successfully.

Keywords: residual stress, mandrel shaft, untempered martensite, portable XRD

Procedia PDF Downloads 112

Authors: Igor A. Podgorny

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TurboTax AnswerXchange is a social Q/A system supporting users working on federal and state tax returns. Content quality and popularity in the AnswerXchange can be predicted with propensity models using attributes of the question and answer. Using uplift modeling, we identify features of questions and answers that can be modified during the question-asking and question-answering experience in order to optimize the AnswerXchange content quality. We demonstrate that adding details to the questions always results in increased question popularity that can be used to promote good quality content. Responding to close-ended questions assertively improve content quality in the AnswerXchange in 90% of cases. Answering knowledge questions with web links increases the likelihood of receiving a negative vote from 60% of the askers. Our findings provide a rationale for employing the uplift modeling approach for AnswerXchange operations.

Keywords: customer relationship management, human-machine interaction, text mining, uplift modeling

Procedia PDF Downloads 244

Authors: Chuang-Hung Lin, Cheng-Yuan Hsu, Jia-Yan Lin

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It is an indispensible strategy to adopt greenery approach on architectural bases so as to improve ecological habitats, decrease heat-island effect, purify air quality, and relieve surface runoff as well as noise pollution, all of which are done in an attempt to achieve sustainable environment. How we can do with plant design to attain the best visual quality and ideal carbon dioxide fixation depends on whether or not we can appropriately make use of greenery according to the nature of architectural bases. To achieve the goal, it is a need that architects and landscape architects should be provided with sufficient local references. Current greenery studies focus mainly on the heat-island effect of urban with large scale. Most of the architects still rely on people with years of expertise regarding the adoption and disposition of plantation in connection with microclimate scale. Therefore, environmental design, which integrates science and aesthetics, requires fundamental research on landscape environment technology divided from building environment technology. By doing so, we can create mutual benefits between green building and the environment. This issue is extremely important for the greening design of the bases of green buildings in cities and various open spaces. The purpose of this study is to establish plant selection and allocation strategies under different building sunshade levels. Initially, with the shading of sunshine on the greening bases as the starting point, the effects of the shades produced by different building types on the greening strategies were analyzed. Then, by measuring the PAR( photosynthetic active radiation), the relative DLI( daily light integral) was calculated, while the DLI Map was established in order to evaluate the effects of the building shading on the established environmental greening, thereby serving as a reference for plant selection and allocation. The discussion results were to be applied in the evaluation of environment greening of greening buildings and establish the “right plant, right place” design strategy of multi-level ecological greening for application in urban design and landscape design development, as well as the greening criteria to feedback to the eco-city greening buildings.

Keywords: daily light integral, plant design, urban open space

Procedia PDF Downloads 510

Authors: Caspar Goeke, Holger Finger, Dorena Diekamp, Peter König

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Online-based research has recently gained increasing attention from various fields of research in the cognitive sciences. Technological advances in the form of online crowdsourcing (Amazon Mechanical Turk), open data repositories (Open Science Framework), and online analysis (Ipython notebook) offer rich possibilities to improve, validate, and speed up research. However, until today there is no cross-platform integration of these subsystems. Furthermore, implementation of online studies still suffers from the complex implementation (server infrastructure, database programming, security considerations etc.). Here we propose and test a new JavaScript framework that enables researchers to conduct any kind of behavioral research in the browser without the need to program a single line of code. In particular our framework offers the possibility to manipulate and combine the experimental stimuli via a graphical editor, directly in the browser. Moreover, we included an action-event system that can be used to handle user interactions, interactively change stimuli properties or store participants’ responses. Besides traditional recordings such as reaction time, mouse and keyboard presses, the tool offers webcam based eye and face-tracking. On top of these features our framework also takes care about the participant recruitment, via crowdsourcing platforms such as Amazon Mechanical Turk. Furthermore, the build in functionality of google translate will ensure automatic text translations of the experimental content. Thereby, thousands of participants from different cultures and nationalities can be recruited literally within hours. Finally, the recorded data can be visualized and cleaned online, and then exported into the desired formats (csv, xls, sav, mat) for statistical analysis. Alternatively, the data can also be analyzed online within our framework using the integrated Ipython notebook. The framework was designed such that studies can be used interchangeably between researchers. This will support not only the idea of open data repositories but also constitutes the possibility to share and reuse the experimental designs and analyses such that the validity of the paradigms will be improved. Particularly, sharing and integrating the experimental designs and analysis will lead to an increased consistency of experimental paradigms. To demonstrate the functionality of the framework we present the results of a pilot study in the field of spatial navigation that was conducted using the framework. Specifically, we recruited over 2000 subjects with various cultural backgrounds and consequently analyzed performance difference in dependence on the factors culture, gender and age. Overall, our results demonstrate a strong influence of cultural factors in spatial cognition. Such an influence has not yet been reported before and would not have been possible to show without the massive amount of data collected via our framework. In fact, these findings shed new lights on cultural differences in spatial navigation. As a consequence we conclude that our new framework constitutes a wide range of advantages for online research and a methodological innovation, by which new insights can be revealed on the basis of massive data collection.

Keywords: cultural differences, crowdsourcing, JavaScript framework, methodological innovation, online data collection, online study, spatial cognition

Procedia PDF Downloads 257

Authors: Muner M. B. Mohamed, Vipin Varghese, Dustin Chalmers, Khalid M. G. Mohammed, Juan Carlos Q. Velez

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Background: Urinary waxy casts (uWxC) are traditionally described in textbooks as indicative of chronic renal parenchymal disease. However, data supporting this contention is lacking. uWxC can be seen in the context of various renal syndromes, including acute kidney injury, chronic kidney disease, rapidly progressive glomerulonephritis (GN), and nephrotic syndrome. Thus, we investigated the correlation between the identification of uWxC and renal pathological findings. Methods: We prospectively collected data of patients seen in nephrology consultation with a urine specimen subjected to the microscopic examination of the urinary sediment (MicrExUrSed) over a 3-year period. Within this cohort, we identified cases in which a kidney biopsy was concomitantly performed. We assessed the association of uWxC with glomerular or tubular pathology and with chronicity [interstitial fibrosis and tubular atrophy (IFTA) and glomerular obsolescence (GO)]. Results: Among 683 patients with MicrExUrSed,103 (15%) underwent kidney biopsy and were included. The mean age was 55 years, 51% women, 50% white, and 38% self-identified black. Median serum creatinine was 3.2 (0-7-15.6) mg/dL and not significantly different between those with and without uWxC (4.7 vs 3.8 mg/dL, p=0.13). uWxC was identified in 35 (34%) cases. A glomerulopathy was diagnosed in 79 (77%). Among those with uWxC (n=35), a glomerulopathy was more likely to be found with concomitant acute tubular injury (ATI) than without ATI (57% vs. 23%, p=0.0006), whereas among those without uWxC, glomerulopathies were found with or without concomitant ATI with similar frequency (41% vs. 34%, p=0.48). Overall (n=103), more patients with uWxC had ≥ 20% IFTA compared to those without uWxC (74% vs 51%, p=0.03). Among those with glomerulopathy (n=79), more patients with uWxC had ≥ 20% IFTA compared to those without uWxC (89% vs. 56%, p=0.004). uWxC did not correlate with GO. Conclusion: Identification of uWxC denotes a greater likelihood of finding evidence of ATI superimposed with a glomerulopathy rather than finding an isolated glomerular lesion. uWxC is associated with a greater probability of finding ≥ 20% IFTA in a kidney biopsy specimen, particularly in those with a glomerular pathology. This observation may help clinicians weigh on the suitability of a kidney biopsy when chronicity or coexistence of ATI is in question.

Keywords: waxy cast, kidney biopsy, acute tubular injury, glomerulopathy

Procedia PDF Downloads 92

Authors: Abderrazak Bannari

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Acid Mine Drainage (AMD) from mine wastes and contaminations of soils and water with metals are considered as a major environmental problem in mining areas. It is produced by interactions of water, air, and sulphidic mine wastes. This environment problem results from a series of chemical and biochemical oxidation reactions of sulfide minerals e.g. pyrite and pyrrhotite. These reactions lead to acidity as well as the dissolution of toxic and heavy metals (Fe, Mn, Cu, etc.) from tailings waste rock piles, and open pits. Soil and aquatic ecosystems could be contaminated and, consequently, human health and wildlife will be affected. Furthermore, secondary minerals, typically formed during weathering of mine waste storage areas when the concentration of soluble constituents exceeds the corresponding solubility product, are also important. The most common secondary mineral compositions are hydrous iron oxide (goethite, etc.) and hydrated iron sulfate (jarosite, etc.). The objectives of this study focus on the detection and mapping of MIOP in the soil using Hyperion EO-1 (Earth Observing - 1) hyperspectral data and constrained linear spectral mixture analysis (CLSMA) algorithm. The abandoned Kettara mine, located approximately 35 km northwest of Marrakech city (Morocco) was chosen as study area. During 44 years (from 1938 to 1981) this mine was exploited for iron oxide and iron sulphide minerals. Previous studies have shown that Kettara surrounding soils are contaminated by heavy metals (Fe, Cu, etc.) as well as by secondary minerals. To achieve our objectives, several soil samples representing different MIOP classes have been resampled and located using accurate GPS ( ≤ ± 30 cm). Then, endmembers spectra were acquired over each sample using an Analytical Spectral Device (ASD) covering the spectral domain from 350 to 2500 nm. Considering each soil sample separately, the average of forty spectra was resampled and convolved using Gaussian response profiles to match the bandwidths and the band centers of the Hyperion sensor. Moreover, the MIOP content in each sample was estimated by geochemical analyses in the laboratory, and a ground truth map was generated using simple Kriging in GIS environment for validation purposes. The acquired and used Hyperion data were corrected for a spatial shift between the VNIR and SWIR detectors, striping, dead column, noise, and gain and offset errors. Then, atmospherically corrected using the MODTRAN 4.2 radiative transfer code, and transformed to surface reflectance, corrected for sensor smile (1-3 nm shift in VNIR and SWIR), and post-processed to remove residual errors. Finally, geometric distortions and relief displacement effects were corrected using a digital elevation model. The MIOP fraction map was extracted using CLSMA considering the entire spectral range (427-2355 nm), and validated by reference to the ground truth map generated by Kriging. The obtained results show the promising potential of the proposed methodology for the detection and mapping of mine iron oxide pollution in the soil.

Keywords: hyperion eo-1, hyperspectral, mine iron oxide pollution, environmental impact, unmixing

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Authors: Evar C. Umeozor, Experience I. Nduagu, Ian D. Gates

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The energy requirements of carbon dioxide utilization (CDU) technologies/processes are diverse, so also are their environmental footprints. This paper explores the energy and environmental impacts of systems for CO₂ conversion to fuels, chemicals, and materials. Energy needs of the technologies and processes deployable in CO₂ conversion systems are met by one or combinations of hydrogen (chemical), electricity, heat, and light. Likewise, the environmental footprint of any CO₂ utilization pathway depends on the systems involved. So far, evaluation of CDU systems has been constrained to particular energy source/type or a subset of the overall system needed to make CDU possible. This introduces limitations to the general understanding of the energy and environmental implications of CDU, which has led to various pitfalls in past studies. A CDU system has an energy source, CO₂ supply, and conversion units. We apply a holistic approach to consider the impacts of all components in the process, including various sources of energy, CO₂ feedstock, and conversion technologies. The electricity sources include nuclear power, renewables (wind and solar PV), gas turbine, and coal. Heat is supplied from either electricity or natural gas, and hydrogen is produced from either steam methane reforming or electrolysis. The CO₂ capture unit uses either direct air capture or post-combustion capture via amine scrubbing, where applicable, integrated configurations of the CDU system are explored. We demonstrate how the overall energy and environmental impacts of each utilization pathway are obtained by aggregating the values for all components involved. Proper accounting of the energy and emission intensities of CDU must incorporate total balances for the utilization process and differences in timescales between alternative conversion pathways. Our results highlight opportunities for the use of clean energy sources, direct air capture, and a number of promising CO₂ conversion pathways for producing methanol, ethanol, synfuel, urea, and polymer materials.

Keywords: carbon dioxide utilization, processes, energy options, environmental impacts

Procedia PDF Downloads 147

Authors: Radhia Toujani, Jalel Akaichi

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Social Networks generally present a hierarchy of communities. To determine these communities and the relationship between them, detection algorithms should be applied. Most of the existing algorithms, proposed for hierarchical communities identification, are based on either agglomerative clustering or divisive clustering. In this paper, we present a hybrid hierarchical clustering approach for community detection based on both bottom-up and bottom-down clustering. Obviously, our approach provides more relevant community structure than hierarchical method which considers only divisive or agglomerative clustering to identify communities. Moreover, we performed some comparative experiments to enhance the quality of the clustering results and to show the effectiveness of our algorithm.

Keywords: agglomerative hierarchical clustering, community structure, divisive hierarchical clustering, hybrid hierarchical clustering, opinion mining, social network, social network analysis

Procedia PDF Downloads 365

Authors: Sukla Saha, Alok Sinha

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Acid mine drainage (AMD) refers to the production of acidified water from abandoned mines and active mines as well. The reason behind the generation of this kind of acidified water is the oxidation of pyrites present in the rocks in and around mining areas. Thiobacillus ferrooxidans, which is a sulfur oxidizing bacteria, helps in the oxidation process. AMD is extremely acidic in nature, (pH 2-3) with high concentration of several trace and heavy metals such as Fe, Al, Zn, Mn, Cu and Co and anions such as chloride and sulfate. AMD has several detrimental effect on aquatic organism and environment. It can directly or indirectly contaminate the ground water and surface water as well. The present study considered the treatment of AMD with metallurgical slag, which is a waste material. Slag helped to enhance the pH of AMD to 8.62 from 1.5 with 99% removal of trace metals such as Fe, Al, Mn, Cu and Co. Metallurgical slag was proven as efficient neutralizing material for the treatment of AMD.

Keywords: acid mine drainage, Heavy metals, metallurgical slag, Neutralization

Procedia PDF Downloads 187

Authors: Barbara Bialecka, Zdzislaw Adamczyk, Magdalena Cempa

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In the work, the results of investigations into the hydrothermal zeolitization of fly ash from hard coal combustion in one of Polish Power Station have been presented. The chemical composition of the ash was determined by the method of X-ray fluorescence (XRF), whereas the phases of both fly ash and the products after synthesis were identified using microscopic observations, X-ray diffraction analysis (XRD) as well as electron scanning microscopy with measurements of the chemical compositions in micro areas (SEM/EDS). The synthesis was carried out with various concentrations of NaOH solution (3M, 4M and 6M) in the following conditions: synthesis temperature – 80ᵒC, synthesis time – 16 hours, volume of NaOH solution – 350ml, fly ash mass – 14g. The main chemical components of fly ash were SiO₂ and Al₂O₃, the contents of which reached 51.62 and 28.14%mas., respectively. The input ash contained mainly such phases as mullite, quarz, magnetite, and glass. The research results indicate that the phase composition of products after zeolitization was differentiated. The material after synthesis in 3M NaOH solution was found to contain mullite, quarz, magnetite, and Na-LSX zeolite. The products of synthesis in 4M NaOH solution were very similar to those in 3M solution (mullite, quarz, magnetite, Na-LSX zeolite), but they additionally contained hydrosodalite. The material after synthesis in 6M NaOH solution contains mullite, quarz, magnetite (similarly to synthesis in 3M and 4M NaOH solition) and additionally hydrosodalite. Therefore, the products of synthesis contain relic components from the fly ash input sample in the form of mullite, quarz, and magnetite, as well as new phases, which are Na-LSX zeolite and hydrosodalite. It should be noted that the products of synthesis in the case of 4M NaOH solution contained both new phases (Na-LSX zeolite and hydrosodalite), while the products from the extreme concentration of NaOH solutions (3M and 6M) contained only one of them. Observations in the scanning electron microscope revealed the new phases’ morphology. It was found that Na-LSX zeolite formed cubic crystals, whereas hydrosodalite formed characteristic aggregations. The results of investigations into the chemical composition in the micro area of phase grains in the products after synthesis reveal some dependencies, among others a characteristic increase in the content of sodium, related to the increased concentration of NaOH solution.

Keywords: Na-LSX, fly ash, hydrosodalite, zeolite

Procedia PDF Downloads 172

Authors: Ibrahim Abubakar Alkali, Abubakar Sarkile Kawuwa, Ibrahim Sani Khalil

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The concept of space and function forms the bedrock for spatial configuration in architectural design. Thus, the effectiveness and functionality of an architectural product depends their cordial relationship. This applies to all buildings especially to a hospital ward setting designed to accommodate various complex and diverse functions. Health care facilities design, especially an inpatient setting, is governed by many regulations and technical requirements. It is also affected by many less defined needs, particularly, response to culture and the need to provide for patient families’ presence and participation. The spatial configuration of the hospital ward setting in developing countries has no consideration for the patient’s families despite the significant role they play in promoting recovery. Attempts to integrate facilities for patients’ families have always been challenging, especially in developing countries like Nigeria, where accommodation for inpatients is predominantly in an open ward system. In addition, the situation is compounded by culture, which significantly dictates healthcare practices in Africa. Therefore, achieving such a hospital ward setting that is patient and family-centered requires careful assessment of family care actions and transaction spaces so as to arrive at an evidence based solution. Therefore, the aim of this study is to identify how hospital ward spaces can be reconfigured to provide for sustainable family integration. In achieving this aim, a qualitative approach using the principles of behavioral mapping was employed in male and female medical wards of the Federal Teaching Hospital (FTH) Gombe, Nigeria. The data obtained was analysed using classical and comparative content analysis. Patients’ families have been found to be a critical component of hospital ward design that cannot be undermined. Accordingly, bedsides, open yards, corridors and foyers have been identified as patient families’ transaction spaces that require design attention. Arriving at sustainable family integration can be achieved by revisiting the design requirements of the family transaction spaces based on the findings in order to avoid the rowdiness of the wards and uncoordinated sprawl.

Keywords: caregiving, design basics, family integration, hospital ward, sustainability

Procedia PDF Downloads 305

Authors: Haozheng Luo, Ruiyang Qin

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People with visual impairments urgently need assistance, not only on the fundamental tasks such as guiding and retrieving objects but on the advanced like picturing the new environments. More than a guiding dog, they might want such devices that can provide linguistic interaction. Building on this idea, we aim to study the interaction between the robot agent and visually impaired people. In our research, we are going to develop a robot agent that will be able to analyze the test environment and answer the participants’ questions. We also will study the relevant issues regarding the interaction between human beings and the robot agents to figure out which and how the factors will affect the interaction.

Keywords: HRI, video question answering, visual question answering, natural language processing

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Authors: Vaidehi Murarka, Sneha Mehta, Dishant Upadhyay

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Our project topic is “Alphabet Recognition using pixel probability distribution”. The project uses techniques of Image Processing and Machine Learning in Computer Vision. Alphabet recognition is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files etc. Alphabet Recognition based OCR application is sometimes used in signature recognition which is used in bank and other high security buildings. One of the popular mobile applications includes reading a visiting card and directly storing it to the contacts. OCR's are known to be used in radar systems for reading speeders license plates and lots of other things. The implementation of our project has been done using Visual Studio and Open CV (Open Source Computer Vision). Our algorithm is based on Neural Networks (machine learning). The project was implemented in three modules: (1) Training: This module aims “Database Generation”. Database was generated using two methods: (a) Run-time generation included database generation at compilation time using inbuilt fonts of OpenCV library. Human intervention is not necessary for generating this database. (b) Contour–detection: ‘jpeg’ template containing different fonts of an alphabet is converted to the weighted matrix using specialized functions (contour detection and blob detection) of OpenCV. The main advantage of this type of database generation is that the algorithm becomes self-learning and the final database requires little memory to be stored (119kb precisely). (2) Preprocessing: Input image is pre-processed using image processing concepts such as adaptive thresholding, binarizing, dilating etc. and is made ready for segmentation. “Segmentation” includes extraction of lines, words, and letters from the processed text image. (3) Testing and prediction: The extracted letters are classified and predicted using the neural networks algorithm. The algorithm recognizes an alphabet based on certain mathematical parameters calculated using the database and weight matrix of the segmented image.

Keywords: contour-detection, neural networks, pre-processing, recognition coefficient, runtime-template generation, segmentation, weight matrix

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Authors: Radwa Mabrook

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Virtual Reality (VR) content creation is a complex and an expensive process, which requires multi-disciplinary teams of content creators. Grant schemes from technology companies help media organisations to explore the VR potential in journalism and factual storytelling. Media organisations try to do as much as they can in-house, but they may outsource due to time constraints and skill availability. Journalists, game developers, sound designers and creative artists work together and bring in new cultures of work. This study explores the collaborative experimental nature of VR content creation, through tracing every actor involved in the process and examining their perceptions of the VR work. The study builds on Actor Network Theory (ANT), which decomposes phenomena into their basic elements and traces the interrelations among them. Therefore, the researcher conducted 22 semi-structured interviews with VR content creators between November 2017 and April 2018. Purposive and snowball sampling techniques allowed the researcher to recruit fact-based VR content creators from production studios and media organisations, as well as freelancers. Interviews lasted up to three hours, and they were a mix of Skype calls and in-person interviews. Participants consented for their interviews to be recorded, and for their names to be revealed in the study. The researcher coded interviews’ transcripts in Nvivo software, looking for key themes that correspond with the research questions. The study revealed that VR content creators must be adaptive to change, open to learn and comfortable with mistakes. The VR content creation process is very iterative because VR has no established work flow or visual grammar. Multi-disciplinary VR team members often speak different languages making it hard to communicate. However, adaptive content creators perceive VR work as a fun experience and an opportunity to learn. The traditional sense of competition and the strive for information exclusivity are now replaced by a strong drive for knowledge sharing. VR content creators are open to share their methods of work and their experiences. They target to build a collaborative network that aims to harness VR technology for journalism and factual storytelling. Indeed, VR is instilling collaborative and experimental cultures in journalism.

Keywords: collaborative culture, content creation, experimental culture, virtual reality

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Authors: Hugo Lefeuvre, Jerôme Donnard, Michael Descostes, Sophie Billon, Samuel Duval, Tugdual Oger, Herve Toubon, Paul Sardini

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Spectroscopic autoradiography is a method of interest for geological sample analysis. Indeed, researchers may face different issues such as radioelement identification and quantification in the field of environmental studies. Imaging gaseous ionization detectors find their place in geosciences for conducting specific measurements of radioactivity to improve the monitoring of natural processes using naturally-occurring radioactive tracers, but also for the nuclear industry linked to the mining sector. In geological samples, the location and identification of the radioactive-bearing minerals at the thin-section scale remains a major challenge as the detection limit of the usual elementary microprobe techniques is far higher than the concentration of most of the natural radioactive decay products. The spatial distribution of each decay product in the case of uranium in a geomaterial is interesting for relating radionuclides concentration to the mineralogy. The present study aims to provide spectroscopic autoradiography analysis method for measuring the initial energy of alpha particles with a parallel ionization multiplier gaseous detector. The analysis method has been developed thanks to Geant4 modelling of the detector. The track of alpha particles recorded in the gas detector allow the simultaneous measurement of the initial point of emission and the reconstruction of the initial particle energy by a selection based on the linear energy distribution. This spectroscopic autoradiography method was successfully used to reproduce the alpha spectra from a 238U decay chain on a geological sample at the thin-section scale. The characteristics of this measurement are an energy spectrum resolution of 17.2% (FWHM) at 4647 keV and a spatial resolution of at least 50 µm. Even if the efficiency of energy spectrum reconstruction is low (4.4%) compared to the efficiency of a simple autoradiograph (50%), this novel measurement approach offers the opportunity to select areas on an autoradiograph to perform an energy spectrum analysis within that area. This opens up possibilities for the detailed analysis of heterogeneous geological samples containing natural alpha emitters such as uranium-238 and radium-226. This measurement will allow the study of the spatial distribution of uranium and its descendants in geo-materials by coupling scanning electron microscope characterizations. The direct application of this dual modality (energy-position) of analysis will be the subject of future developments. The measurement of the radioactive equilibrium state of heterogeneous geological structures, and the quantitative mapping of 226Ra radioactivity are now being actively studied.

Keywords: alpha spectroscopy, digital autoradiography, mining activities, natural decay products

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Authors: Hasan G. Elmazoghi, Aisha I. Alzayani, Lubna S. Bentaher

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Rainfall is a highly non-linear phenomena, which requires application of powerful supervised data mining techniques for its accurate prediction. In this study the Artificial Neural Network (ANN) technique is used to predict the mean monthly historical rainfall data collected from BENINA station in Benghazi for 31 years, the period of “1977-2006” and the results are compared against the observed values. The specific objective to achieve this goal was to determine the best combination of weather variables to be used as inputs for the ANN model. Several statistical parameters were calculated and an uncertainty analysis for the results is also presented. The best ANN model is then applied to the data of one year (2007) as a case study in order to evaluate the performance of the model. Simulation results reveal that application of ANN technique is promising and can provide reliable estimates of rainfall.

Keywords: neural networks, rainfall, prediction, climatic variables

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Authors: Vikas Kumar

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Portable batteries are reliable source of mobile energy to power smart wearable electronics, medical devices, communications, and others internet of thing (IoT) devices. There is a continuous increase in demand for thinner, more flexible battery with high energy density and reliability to meet the requirement. For a flexible battery, factors that affect these properties are the stability of current collectors, electrode materials and their interfaces with the corrosive electrolytes. State-of-the-art conventional and flexible batteries utilise carbon as an electrode and current collectors which cause high internal resistance (~100 ohms) and limit the peak current to ~1mA. This makes them unsuitable for a wide range of applications. Replacing the carbon parts with metallic components would reduce the internal resistance (and hence reduce parasitic loss), but significantly increases the risk of corrosion due to galvanic interactions within the battery. To overcome these challenges, low cost electroplated nickel (Ni) on copper (Cu) was studied as a potential anode current collector for a zinc-manganese oxide primary battery with different concentration of NH4Cl/ZnCl2 electrolyte. Using electrical impedance spectroscopy (EIS), we monitored the open circuit potential (OCP) of electroplated nickel (different thicknesses) in different concentration of electrolytes to optimise the thickness of Ni coating. Our results show that electroless Ni coating suffer excessive corrosion in these electrolytes. Corrosion rates of Ni coatings for different concentrations of electrolytes have been calculated with Tafel analysis. These results suggest that for electroplated Ni, channelling and/or open porosity is a major issue, which was confirmed by morphological analysis. These channels are an easy pathway for electrolyte to penetrate thorough Ni to corrode the Ni/Cu interface completely. We further investigated the incorporation of a special printed graphene layer on Ni to provide corrosion protection in this corrosive electrolyte medium. We find that the incorporation of printed graphene layer provides the corrosion protection to the Ni and enhances the chemical bonding between the active materials and current collector and also decreases the overall internal resistance of the battery system.

Keywords: corrosion, electrical impedance spectroscopy, flexible battery, graphene, metal current collector

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Authors: Supratman Ahman Maedi

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The construction of knowledge is the goal of learning. The purpose of this research is to know how the role of Piaget theory in allegation via analogy reasoning. This study uses Think out loads when troubleshooting. To explore conjecturing via analogical reasoning is given the question of open analogy. The result: conjecture via analogical reasoning has been done by students in the construction of knowledge, in conjecture there are differences in thinking flow depending on the basic knowledge of the students, in the construction of knowledge occurs assimilation and accommodation problems, strategies and relationships.

Keywords: analogical reasoning, conjecturing, knowledge construction, Piaget's theory

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Authors: Kunal Shah, Swati Patel

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Many real world problems involve data which can be considered as multi-label data streams. Efficient methods exist for multi-label classification in non streaming scenarios. However, learning in evolving streaming scenarios is more challenging, as the learners must be able to adapt to change using limited time and memory. Classification is used to predict class of unseen instance as accurate as possible. Multi label classification is a variant of single label classification where set of labels associated with single instance. Multi label classification is used by modern applications, such as text classification, functional genomics, image classification, music categorization etc. This paper introduces the task of multi-label classification, methods for multi-label classification and evolution measure for multi-label classification. Also, comparative analysis of multi label classification methods on the basis of theoretical study, and then on the basis of simulation was done on various data sets.

Keywords: binary relevance, concept drift, data stream mining, MLSC, multiple window with buffer

Procedia PDF Downloads 584

Authors: Josef Steinberger, Vanni Zavarella, Hristo Tanev

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Natural disasters cause tens of thousands of victims and massive material damages. We refer to all those events caused by natural disasters, such as damage on people, infrastructure, vehicles, services and resource supply, as micro events. This paper addresses the problem of micro - event detection in online media sources. We present a natural language grammar learning algorithm and apply it to online news. The algorithm in question is based on distributional clustering and detection of word collocations. We also explore the extraction of micro-events from social media and describe a Twitter mining robot, who uses combinations of keywords to detect tweets which talk about effects of disasters.

Keywords: online news, natural language processing, machine learning, event extraction, crisis computing, disaster effects, Twitter

Procedia PDF Downloads 478

Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu

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Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.

Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish

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Authors: P. Halder, A. Zaman

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It is estimated that heart disease accounts for one in ten deaths worldwide. United States deaths due to heart disease are among the leading causes of death according to the World Health Organization. Cardiovascular diseases (CVDs) account for one in four U.S. deaths, according to the Centers for Disease Control and Prevention (CDC). According to statistics, women are more likely than men to die from heart disease as a result of strokes. A 50% increase in men's mortality was reported by the World Health Organization in 2009. The consequences of cardiovascular disease are severe. The causes of heart disease include diabetes, high blood pressure, high cholesterol, abnormal pulse rates, etc. Machine learning (ML) can be used to make predictions and decisions in the healthcare industry. Thus, scientists have turned to modern technologies like Machine Learning and Data Mining to predict diseases. The disease prediction is based on four algorithms. Compared to other boosts, the Ada boost is much more accurate.

Keywords: heart disease, cardiovascular disease, coronary artery disease, feature selection, random forest, AdaBoost, SVM, decision tree

Procedia PDF Downloads 153

Authors: Amna Javed, Hisashi Masuda, Youji Kohda

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This study examines the value analysis in Islamic and conventional banking services in Pakistan. Many scholars have focused on co-creation of values in services but mainly economic values not non-economic. As Islamic banking is based on Islamic principles that are more concerned with non-economic values (well-being, partnership, fairness, trust worthy, and justice) than economic values as money in terms of interest. This study is important to know the providers point of view about the co-created values, because, it may be more sustainable and appropriate for today’s unpredictable socioeconomic environment. Data were collected from 4 banks (2 Islamic and 2 conventional banks). Text mining technique is applied for data analysis, and values with 100% occurrences in Islamic banking are chosen. The results reflect that Islamic banking is more centric towards non-economic values than economic values and it promotes team work and partnership concept by applying Islamic spirit and trust worthiness concept.

Keywords: economic values, Islamic banking, non-economic values, value system

Procedia PDF Downloads 462

Authors: Pradip Choudhury, Tapobrata Sanyal

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Effectiveness of Jute Geotextiles (JGT) in hill slope management now stands substantiated. The reasons of its efficacy are attributed to its bio-degradability, hygroscopic property and its thickness. Usually open weave JGT is used for slope management. Thickness of JGT helps in reducing the velocity of surface run-off, thus curbing the extent of migration of soil particles detached as a result of kinetic energy of rain-drops and also of wind effects. Initially JGT acts as cover of the surface of slope thus protect movement of loose soil particles. Hygroscopic property of jute effects overland storage of the flow. JGT acts as mulch and creates a congenial micro-climate that fosters quick growth of vegetation on bio-degradation. In fact JGT plays an important role in bio-remediation of slope-erosion problems. Considering the environmental aftermath, JGT is the preferred option in developed countries for surface soil conservation against erosion. In India JGT has not been tried in low temperature zones at high altitudes where temperature goes below the freezing point (even below - 25° Celsius). The behavior of JGT in such low-temperature zones is not precisely known. The 16th BRTF of Project Himank of Border Roads Organization (BRO) has recently taken the initiative to try two varieties of JGT , ie, 292 gsm and 500 gsm at two different places for hill slope management in Leh, a high altitude place of about 2,660 mtrs and 4900 mtrs above MSL respectively in Jammu & Kashmir where erosion is caused more as a result of rapid movement of sand particles due to high wind (wind erosion. Soil particles of the region formed naturally by weathering of fragile rocks are usually loosely bonded (non-cohesive), undergo dissociation with the rise in wind force and kinetic energy of rain drops and are blown away by wind. Open weave JGT interestingly was observed to contain the dissociated soil particles within its pores and lend stability the affected soil mass to a great extent thus preventing its movement by extraneous agents such as wind. The paper delineates about climatic factors, type of JGT used and the prevailing site conditions with an attempt to analyze the mechanism of functioning of JGT in low temperature zones.

Keywords: climate, erosion, jutegeotextile, stabilize

Procedia PDF Downloads 428