Search results for: network of tourism actors

Authors: A. Shakoor, M. Arshad

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The utilization of groundwater resources in irrigation has significantly increased during the last two decades due to constrained canal water supplies. More than 70% of the farmers in the Punjab, Pakistan, depend directly or indirectly on groundwater to meet their crop water demands and hence, an unchecked paradigm shift has resulted in aquifer depletion and deterioration. Therefore, a comprehensive research was carried at central Punjab-Pakistan, regarding spatiotemporal variation in groundwater level and quality. Processing MODFLOW for window (PMWIN) and MT3D (solute transport model) models were used for existing and future prediction of groundwater level and quality till 2030. The comprehensive data set of aquifer lithology, canal network, groundwater level, groundwater salinity, evapotranspiration, groundwater abstraction, recharge etc. were used in PMWIN model development. The model was thus, successfully calibrated and validated with respect to groundwater level for the periods of 2003 to 2007 and 2008 to 2012, respectively. The coefficient of determination (R2) and model efficiency (MEF) for calibration and validation period were calculated as 0.89 and 0.98, respectively, which argued a high level of correlation between the calculated and measured data. For solute transport model (MT3D), the values of advection and dispersion parameters were used. The model used for future scenario up to 2030, by assuming that there would be no uncertain change in climate and groundwater abstraction rate would increase gradually. The model predicted results revealed that the groundwater would decline from 0.0131 to 1.68m/year during 2013 to 2030 and the maximum decline would be on the lower side of the study area, where infrastructure of canal system is very less. This lowering of groundwater level might cause an increase in the tubewell installation and pumping cost. Similarly, the predicted total dissolved solids (TDS) of the groundwater would increase from 6.88 to 69.88mg/L/year during 2013 to 2030 and the maximum increase would be on lower side. It was found that in 2030, the good quality would reduce by 21.4%, while marginal and hazardous quality water increased by 19.28 and 2%, respectively. It was found from the simulated results that the salinity of the study area had increased due to the intrusion of salts. The deterioration of groundwater quality would cause soil salinity and ultimately the reduction in crop productivity. It was concluded from the predicted results of groundwater model that the groundwater deteriorated with the depth of water table i.e. TDS increased with declining groundwater level. It is recommended that agronomic and engineering practices i.e. land leveling, rainwater harvesting, skimming well, ASR (Aquifer Storage and Recovery Wells) etc. should be integrated to meliorate management of groundwater for higher crop production in salt affected soils.

Keywords: groundwater quality, groundwater management, PMWIN, MT3D model

Procedia PDF Downloads 378

Authors: Niharika Kaushal, Minni Singh

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Citrus fruits contain an abundance of phytochemicals that can promote health. A substantial amount of agrowaste is produced from the juice processing industries, primarily peels and seeds. This leftover agrowaste is a reservoir of nutraceuticals, particularly bioflavonoids which render it antioxidant and potentially anticancerous. It is, therefore, favorable to utilize this biomass and contribute towards sustainability in a manner that value-added products may be derived from them, nutraceuticals, in this study. However, the pre-systemic metabolism of flavonoids in the gastric phase limits the effectiveness of these bioflavonoids derived from mandarin biomass. In this study, ‘kinnow’ mandarin (Citrus nobilis X Citrus deliciosa) biomass was explored for its flavonoid profile. This work entails supercritical fluid extraction and identification of bioflavonoids from mandarin biomass. Furthermore, to overcome the limitations of these flavonoids in the gastrointestinal tract, a double-layered vehicular mechanism comprising the fabrication of nanoconjugates and edible hydrogels was adopted. Total flavonoids in the mandarin peel extract were estimated by the aluminum chloride complexation method and were found to be 47.3±1.06 mg/ml rutin equivalents as total flavonoids. Mass spectral analysis revealed the abundance of polymethoxyflavones (PMFs), nobiletin and tangeretin as the major flavonoids in the extract, followed by hesperetin and naringenin. Furthermore, the antioxidant potential was analyzed by the 2,2-diphenyl-1-picrylhydrazyl (DPPH) method, which showed an IC50 of 0.55μg/ml. Nanoconjugates were fabricated via the solvent evaporation method, which was further impregnated into hydrogels. Additionally, the release characteristics of nanoconjugate-laden hydrogels in a simulated gastrointestinal environment were studied. The PLGA-PMFs nanoconjugates exhibited a particle size between 200-250nm having a smooth and spherical shape as revealed by FE-SEM. The impregnated alginate hydrogels offered a dense network that ensured the holding of PLGA-PMF nanoconjugates, as confirmed by Cryo-SEM images. Rheological studies revealed the shear-thinning behavior of hydrogels and their high resistance to deformation. Gastrointestinal studies showed a negligible 4.0% release of flavonoids in the gastric phase, followed by a sustained release over the next hours in the intestinal environment. Therefore, based on the enormous potential of recovering nutraceuticals from agro-processing wastes, further augmented by nanotechnological interventions for enhancing the bioefficacy of these compounds, lays the foundation for exploring the path towards the development of value-added products, thereby contributing towards the sustainable use of agrowaste.

Keywords: agrowaste, gastrointestinal, hydrogel, nutraceuticals

Procedia PDF Downloads 93

Authors: Aaron Liggett

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This research focuses on the visionary proposal made by the Olmsted Brothers Landscape Architecture firm in the 1920s for a network of interconnected parkways in Los Angeles. Their envisioned parkways aimed to address environmental and cultural strains by providing green space for recreation, wildlife habitat, and stormwater management while serving as multimodal transportation routes. Although the parkways were never constructed, through an evidence-based approach, this research presents a framework for evaluating the potential functionality and success of the parkways by modeling and visualizing their quantitative and qualitative landscape performance and benefits. Historical documents and innovative digital modeling tools produce detailed analysis, modeling, and visualization of the parkway designs. A set of 1928 construction documents are used to analyze and interpret the design intent of the parkways. Grading plans are digitized in CAD and modeled in Sketchup to produce 3D visualizations of the parkway. Drainage plans are digitized to model stormwater performance. Planting plans are analyzed to model urban forestry and biodiversity. The EPA's Storm Water Management Model (SWMM) predicts runoff quantity and quality. The USDA Forests Service tools evaluate carbon sequestration and air quality. Spatial and overlay analysis techniques are employed to assess urban connectivity and the spatial impacts of the parkway designs. The study reveals how the integration of blue infrastructure, green infrastructure, and transportation infrastructure within the parkway design creates a multifunctional landscape capable of offering alternative spatial and temporal uses. The analysis demonstrates the potential for multiple functional, ecological, aesthetic, and social benefits to be derived from the proposed parkways. The analysis of the Olmsted Brothers' proposed Los Angeles parkways, which predated contemporary ecological design and resiliency practices, demonstrates the potential for providing multiple functional, ecological, aesthetic, and social benefits within urban designs. The findings highlight the importance of integrated blue, green, and transportation infrastructure in creating a multifunctional landscape that simultaneously serves multiple purposes. The research contributes new methods for modeling and visualizing landscape performance benefits, providing insights and techniques for informing future designs and sustainable development strategies.

Keywords: landscape architecture, ecological urban design, greenway, landscape performance

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Authors: Linda D. F. Bambara, Marie Sawadogo

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Jatropha curcas (jatropha) is the plant that has been the most studied for biofuel production in West Africa. There exist however other plants such as Balanites aegyptiaca (balanites) that have been targeted as a potential feedstock for biofuel production. This biomass could be an alternative feedstock for the production of straight vegetable oil (SVO) at costs lower than jatropha-based SVO production costs. This study aims firstly to determine, through an MILP model, the optimal organization that minimizes the costs of the oilseeds supply of two biomass conversion units (BCU) exploiting respectively jatropha seeds and the balanitès seeds. Secondly, the study aims to carry out a comparative study of these costs obtained for each BCU. The model was then implemented on two theoretical cases studies built on the basis of the common practices in Burkina Faso and two scenarios were carried out for each case study. In Scenario 1, 3 pre-processing locations ("at the harvesting area", "at the gathering points", "at the BCU") are possible. In scenario 2, only one location ("at the BCU") is possible. For each biomass, the system studied is the upstream supply chain (harvesting, transport and pre-processing (drying, dehulling, depulping)), including cultivation (for jatropha). The model optimizes the area of land to be exploited based on the productivity of the studied plants and material losses that may occur during the harvesting and the supply of the BCU. It then defines the configuration of the logistics network allowing an optimal supply of the BCU taking into account the most common means of transport in West African rural areas. For the two scenarios, the results of the implementation showed that the total area exploited for balanites (1807 ha) is 4.7 times greater than the total area exploited for Jatropha (381 ha). In both case studies, the location of pre-processing “at the harvesting area” was always chosen for scenario1. As the balanites trees were not planted and because the first harvest of the jatropha seeds took place 4 years after planting, the cost price of the seeds at the BCU without the pre-processing costs was about 430 XOF/kg. This cost is 3 times higher than the balanites's one, which is 140 XOF/kg. After the first year of harvest, i.e. 5 years after planting, and assuming that the yield remains constant, the same cost price is about 200 XOF/kg for Jatropha. This cost is still 1.4 times greater than the balanites's one. The transport cost of the balanites seeds is about 120 XOF/kg. This cost is similar for the jatropha seeds. However, when the pre-processing is located at the BCU, i.e. for scenario2, the transport costs of the balanites seeds is 1200 XOF/kg. These costs are 6 times greater than the transport costs of jatropha which is 200 XOF/kg. These results show that the cost price of the balanites seeds at the BCU can be competitive compared to the jatropha's one if the pre-processing is located at the harvesting area.

Keywords: Balanites aegyptiaca, biomass conversion, Jatropha curcas, optimization, post-harvest operations

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Authors: Gideon C. Joseph

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The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

Procedia PDF Downloads 347

Authors: Sidramappa Gaddnakeri, Lokanath Malligawad

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Any kind of research on production technology of individual crop / commodity /breed has not brought sustainability or stability in crop production. The sustainability of the system over years depends on the maintenance of the soil health. Organic production system includes use of organic manures, biofertilizers, green manuring for nutrient supply and biopesticides for plant protection helps to sustain the productivity even under adverse climatic condition. The study was initiated to evaluate the performance of different cropping systems under organic, inorganic and integrated production systems at The Institute of Organic Farming, University of Agricultural Sciences, Dharwad (Karnataka-India) under ICAR Network Project on Organic Farming. The trial was conducted for four years (2013-14 to 2016-17) on fixed site. Five cropping systems viz., sequence cropping of cowpea – safflower, greengram– rabi sorghum, maize-bengalgram, sole cropping of pigeonpea and intercropping of groundnut + cotton were evaluated under six nutrient management practices. The nutrient management practices are NM1 (100% Organic farming (Organic manures equivalent to 100% N (Cereals/cotton) or 100% P2O5 (Legumes), NM2 (75% Organic farming (Organic manures equivalent to 75% N (Cereals/cotton) or 100% P2O5 (Legumes) + Cow urine and Vermi-wash application), NM3 (Integrated farming (50% Organic + 50% Inorganic nutrients, NM4 (Integrated farming (75% Organic + 25% Inorganic nutrients, NM5 (100% Inorganic farming (Recommended dose of inorganic fertilizers)) and NM6 (Recommended dose of inorganic fertilizers + Recommended rate of farm yard manure (FYM). Among the cropping systems evaluated for different production systems indicated that the Groundnut + Hybrid cotton (2:1) intercropping system found more remunerative as compared to Sole pigeonpea cropping system, Greengram-Sorghum sequence cropping system, Maize-Chickpea sequence cropping system and Cowpea-Safflower sequence cropping system irrespective of the production systems. Production practices involving application of recommended rates of fertilizers + recommended rates of organic manures (Farmyard manure) produced higher net monetary returns and higher B:C ratio as compared to integrated production system involving application of 50 % organics + 50 % inorganic and application of 75 % organics + 25 % inorganic and organic production system only Both the two organic production systems viz., 100 % Organic production system (Organic manures equivalent to 100 % N (Cereals/cotton) or 100 % P2O5 (Legumes) and 75 % Organic production system (Organic manures equivalent to 75 % N (Cereals) or 100 % P2O5 (Legumes) + Cow urine and Vermi-wash application) are found to be on par. Further, integrated production system involving application of organic manures and inorganic fertilizers found more beneficial over organic production systems.

Keywords: cropping systems, production systems, cowpea, safflower, greengram, pigeonpea, groundnut, cotton

Procedia PDF Downloads 199

Authors: Mohamed Gaafar, Evan Davies

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Many municipalities within Canada and abroad use chloramination to disinfect drinking water so as to avert the production of the disinfection by-products (DBPs) that result from conventional chlorination processes and their consequential public health risks. However, the long-lasting monochloramine disinfectant (NH2Cl) can pose a significant risk to the environment. As, it can be introduced into stormwater sewers, from different water uses, and thus freshwater sources. Little research has been undertaken to monitor and characterize the decay of NH2Cl and to study the parameters affecting its decomposition in stormwater networks. Therefore, the current study was intended to investigate this decay starting by building a stormwater model and validating its hydraulic and hydrologic computations, and then modelling water quality in the storm sewers and examining the effects of different parameters on chloramine decay. The presented work here is only the first stage of this study. The 30th Avenue basin in Southern Edmonton was chosen as a case study, because the well-developed basin has various land-use types including commercial, industrial, residential, parks and recreational. The City of Edmonton has already built a MIKE-URBAN stormwater model for modelling floods. Nevertheless, this model was built to the trunk level which means that only the main drainage features were presented. Additionally, this model was not calibrated and known to consistently compute pipe flows higher than the observed values; not to the benefit of studying water quality. So the first goal was to complete modelling and updating all stormwater network components. Then, available GIS Data was used to calculate different catchment properties such as slope, length and imperviousness. In order to calibrate and validate this model, data of two temporary pipe flow monitoring stations, collected during last summer, was used along with records of two other permanent stations available for eight consecutive summer seasons. The effect of various hydrological parameters on model results was investigated. It was found that model results were affected by the ratio of impervious areas. The catchment length was tested, however calculated, because it is approximate representation of the catchment shape. Surface roughness coefficients were calibrated using. Consequently, computed flows at the two temporary locations had correlation coefficients of values 0.846 and 0.815, where the lower value pertained to the larger attached catchment area. Other statistical measures, such as peak error of 0.65%, volume error of 5.6%, maximum positive and negative differences of 2.17 and -1.63 respectively, were all found in acceptable ranges.

Keywords: stormwater, urban drainage, simulation, validation, MIKE URBAN

Procedia PDF Downloads 296

Authors: E. Hegazy, S. Anderberg, J. Krook

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The city's wire-based infrastructure systems (WBIS) are responsible for the delivery of electricity, telecommunications, sanitation, drainage, and district heating and are a necessity for sustainable modern urban life. Maintaining the functionality of these structures involves high costs and, brings disturbance to the local community and effects on the environment. One key reason for this is that the cables and pipes are placed under streets, making system parts easily worn and their service lifetime reduced, and all maintenance and renewal rely on recurrent needs for excavation. In Sweden, a significant part of wire-based infrastructure is already outdated and will need to be replaced in the coming decades. The replacement of these systems will entail massive costs as well as important traffic disruption and environmental disturbance. However, this challenge may also open a unique opportunity to introduce new, more sustainable technologies and management practices. The transformation of WBIS management for long-term sustainability and meeting maintenance and renewal needs does not have a comprehensive approach. However, a systemic approach may inform WBIS management. This approach considers both technical and non-technical aspects, as well as time-related factors. Nevertheless, there is limited systemic knowledge of how different factors influence current management practices. The aim of this study is to address this knowledge gap and contribute to the understanding of what factors influence the current practice of WBIS management. A case study approach is used to identify current management practices, the underlying factors that influence them, and their implications for sustainability outcomes. The case study is based on both quantitative data on the local system and data from interviews and workshops with local practitioners and other stakeholders. Linköping was selected as a case since it provided good accessibility to the water administration and relevant data for analyzing water infrastructure management strategies. It is a sufficiently important city in Sweden to be able to identify challenges, which, to some extent, are common to all Swedish cities. By uncovering current practices and what is influencing Linköping, knowledge gaps and uncertainties related to sustainability consequences were highlighted. The findings show that goals, priorities, and policies controlling management are short-termed, and decisions on maintenance and renewal are often restricted to finding solutions to the most urgent issues. Sustainability transformation in the infrastructure area will not be possible through individual efforts without coordinated technical, organizational, business, and regulatory changes.

Keywords: case study, infrastructure, management, practice, Sweden

Procedia PDF Downloads 84

Authors: Thelma Maria Melo Pinheiro, Guilherme Raposo Diniz Vieira, Sidney Matos da Silva, Leonardo Mendonça de Oliveira Queiroz, Mateus Sousa Pinheiro, Danyllo Wenceslau de Oliveira Lopes

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The present article has the objective to describe the regulatory impact analysis (RIA) of the contracting efficiency of the Brazilian transmission system usage. This contracting is made by users connected to the main transmission network and is used to guide necessary investments to supply the electrical energy demand. Therefore, an inefficient contracting of this energy amount distorts the real need for grid capacity, affecting the sector planning accuracy and resources optimization. In order to provide this efficiency, the Brazilian Electricity Regulatory Agency (ANEEL) homologated the Normative Resolution (NR) No. 666, from July 23th of 2015, which consolidated the procedures for the contracting of transmission system usage and the contracting efficiency verification. Aiming for a more efficient and rational transmission system contracting, the resolution established economic incentives denominated as Inefficiency installment for excess (IIE) and inefficiency installment for over-contracting (IIOC). The first one, IIE, is verified when the contracted demand exceeds the established regulatory limit; it is applied to consumer units, generators, and distribution companies. The second one, IIOC, is verified when the distributors over-contract their demand. Thus, the establishment of the inefficiency installments IIE and IIOC intends to avoid the agent contract less energy than necessary or more than it is needed. Knowing that RIA evaluates a regulatory intervention to verify if its goals were achieved, the results from the application of the above-mentioned normative resolution to the Brazilian transmission sector were analyzed through indicators that were created for this RIA to evaluate the contracting efficiency transmission system usage, using real data from before and after the homologation of the normative resolution in 2015. For this, indicators were used as the efficiency contracting indicator (ECI), excess of demand indicator (EDI), and over-contracting of demand indicator (ODI). The results demonstrated, through the ECI analysis, a decrease of the contracting efficiency, a behaviour that was happening even before the normative resolution of 2015. On the other side, the EDI showed a considerable decrease in the amount of excess for the distributors and a small reduction for the generators; moreover, the ODI notable decreased, which optimizes the usage of the transmission installations. Hence, with the complete evaluation from the data and indicators, it was possible to conclude that IIE is a relevant incentive for a more efficient contracting, indicating to the agents that their contracting values are not adequate to keep their service provisions for their users. The IIOC also has its relevance, to the point that it shows to the distributors that their contracting values are overestimated.

Keywords: contracting, electricity regulation, evaluation, regulatory impact analysis, transmission power system

Procedia PDF Downloads 121

Authors: Seyed Reza Naghibulsadat

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The nature of communication includes various forms of media productions, which include film and theater. In the current situation, since social networks have emerged, they have brought their own communication capabilities and have features that show speed, public access, lack of media organization and the production of extensive content, and the development of critical thinking; Also, they contain capabilities to develop access to all kinds of media productions, including movies and theater shows; Of course, this works differently in different conditions and communities. In terms of the scale of exploitation, the film has a more general audience, and the theater has a special audience. The film industry is more developed based on more modern technologies, but the theater, based on the older ways of communication, contains more intimate and emotional aspects. ; But in general, the main focus is the development of access to movies and theater shows, which is emphasized by those involved in this field due to the capabilities of social networks. In this research, we will look at these 2 areas and the relevant components for both areas through social networks and also the common points of both types of media production. The main goal of this research is to know the strengths and weaknesses of using social networks for the marketing of movies and theater shows and, at the same time are, also considered the opportunities and threats of this field. The attractions of these two types of media production, with the emergence of social networks, and the ability to change positions, can provide the opportunity to become a media with greater exploitation and higher profitability; But the main consideration is the opinions about these capabilities and the ability to use them for film and theater marketing. The main question of the research is, what are the marketing components for movies and theaters using social media capabilities? What are its strengths and weaknesses? And what opportunities and threats are facing this market? This research has been done with two methods SWOT and meta-analysis. Non-probability sampling has been used with purposeful technique. The results show that a recent approach is an approach based on eliminating threats and weaknesses and emphasizing strengths, and exploiting opportunities in the direction of developing film and theater marketing based on the capabilities of social networks within the framework of local cultural values and presenting achievements on an international scale or It is universal. This introduction leads to the introduction of authentic Iranian culture and foreign enthusiasts in the framework of movies and theater art. Therefore, for this issue, the model for using the capabilities of social networks for movie or theater marketing, according to the results obtained from Respondents, is a model based on SO strategies and, in other words, offensive strategies so that it can take advantage of the internal strengths and made maximum use of foreign situations and opportunities to develop the use of movies and theater performances.

Keywords: marketing, movies, theatrical show, social network potentials

Procedia PDF Downloads 76

Authors: Pratima Pokharel

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When sewer overflow due to rainfall in urban areas, this leads to public health risks when an individual is exposed to that contaminated floodwater. Nevertheless, it is still unclear the extent to which the infections pose a risk to public health. This study analyzed reported diarrheal cases by month and age in Bangkok, Thailand. The results showed that the cases are reported higher in the wet season than in the dry season. It was also found that in Bangkok, the probability of infection with diarrheal diseases in the wet season is higher for the age group between 15 to 44. However, the probability of infection is highest for kids under 5 years, but they are not influenced by wet weather. Further, this study introduced a vulnerability that leads to health risks from urban flooding. This study has found some vulnerability variables that contribute to health risks from flooding. Thus, for vulnerability analysis, the study has chosen two variables, economic status, and age, that contribute to health risk. Assuming that the people's economic status depends on the types of houses they are living in, the study shows the spatial distribution of economic status in the vulnerability maps. The vulnerability map result shows that people living in Sukhumvit have low vulnerability to health risks with respect to the types of houses they are living in. In addition, from age the probability of infection of diarrhea was analyzed. Moreover, a field survey was carried out to validate the vulnerability of people. It showed that health vulnerability depends on economic status, income level, and education. The result depicts that people with low income and poor living conditions are more vulnerable to health risks. Further, the study also carried out 1D Hydrodynamic Advection-Dispersion modelling with 2-year rainfall events to simulate the dispersion of fecal coliform concentration in the drainage network as well as 1D/2D Hydrodynamic model to simulate the overland flow. The 1D result represents higher concentrations for dry weather flows and a large dilution of concentration on the commencement of a rainfall event, resulting in a drop of the concentration due to runoff generated after rainfall, whereas the model produced flood depth, flood duration, and fecal coliform concentration maps, which were transferred to ArcGIS to produce hazard and risk maps. In addition, the study also simulates the 5-year and 10-year rainfall simulations to show the variation in health hazards and risks. It was found that even though the hazard coverage is very high with a 10-year rainfall events among three rainfall events, the risk was observed to be the same with a 5-year and 10-year rainfall events.

Keywords: urban flooding, risk, hazard, vulnerability, health risk, framework

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Authors: Feng Yue, Fei Dai

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With the rapid development of urbanization process in China, its environmental protection pressure is severely tested. So, analyzing and optimizing the landscape pattern is an important measure to ease the pressure on the ecological environment. This paper takes Wuhan Urban Development Zone as the research object, and studies its landscape pattern evolution and quantitative optimization strategy. First, remote sensing image data from 1990 to 2015 were interpreted by using Erdas software. Next, the landscape pattern index of landscape level, class level, and patch level was studied based on Fragstats. Then five indicators of ecological environment based on National Environmental Protection Standard of China were selected to evaluate the impact of landscape pattern evolution on the ecological environment. Besides, the cost distance analysis of ArcGIS was applied to simulate wildlife migration thus indirectly measuring the improvement of ecological environment quality. The result shows that the area of land for construction increased 491%. But the bare land, sparse grassland, forest, farmland, water decreased 82%, 47%, 36%, 25% and 11% respectively. They were mainly converted into construction land. On landscape level, the change of landscape index all showed a downward trend. Number of patches (NP), Landscape shape index (LSI), Connection index (CONNECT), Shannon's diversity index (SHDI), Aggregation index (AI) separately decreased by 2778, 25.7, 0.042, 0.6, 29.2%, all of which indicated that the NP, the degree of aggregation and the landscape connectivity declined. On class level, the construction land and forest, CPLAND, TCA, AI and LSI ascended, but the Distribution Statistics Core Area (CORE_AM) decreased. As for farmland, water, sparse grassland, bare land, CPLAND, TCA and DIVISION, the Patch Density (PD) and LSI descended, yet the patch fragmentation and CORE_AM increased. On patch level, patch area, Patch perimeter, Shape index of water, farmland and bare land continued to decline. The three indexes of forest patches increased overall, sparse grassland decreased as a whole, and construction land increased. It is obvious that the urbanization greatly influenced the landscape evolution. Ecological diversity and landscape heterogeneity of ecological patches clearly dropped. The Habitat Quality Index continuously declined by 14%. Therefore, optimization strategy based on greenway network planning is raised for discussion. This paper contributes to the study of landscape pattern evolution in planning and design and to the research on spatial layout of urbanization.

Keywords: landscape pattern, optimization strategy, ArcGIS, Erdas, landscape metrics, landscape architecture

Procedia PDF Downloads 164

Authors: Nwamaka Patricia Ibeme, Musa Zakari

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E-learning is made more effective because; it is enable student to students to easily interact, share, and collaborate across time and space with the help of e-governance platform. Zoom and the Microsoft classroom team can invite students from all around the world to join a conversation on a certain subject simultaneously. E-governance may be able to work on problem solving skills, as well as brainstorming and developing ideas. As a result of the shared experiences and knowledge, students are able to express themselves and reflect on their own learning." For students, e-governance facilities provide greater opportunity for students to build critical (higher order) thinking abilities through constructive learning methods. Students' critical thinking abilities may improve with more time spent in an online classroom. Students' inventiveness can be enhanced through the use of computer-based instruction. Discover multimedia tools and produce products in the styles that are easily available through games, Compact Disks, and television. The use of e-learning has increased both teaching and learning quality by combining student autonomy, capacity, and creativity over time in developed countries." Teachers are catalysts for the integration of technology through Information and Communication Technology, and e-learning supports teaching by simplifying access to course content." Creating an Information and Communication Technology class will be much easier if educational institutions provide teachers with the assistance, equipment, and resources they need. The study adopted survey research design. The populations of the study are Students and staff. The study adopted a simple random sampling technique to select a representative population. Both primary and secondary method of data collection was used to obtain the data. A chi-square statistical technique was used to analyze. Finding from the study revealed that e-learning has increase accesses to universities educational by public servants in Nigeria. Public servants in Nigeria have utilized e-learning and Online Distance Learning (ODL) programme to into various degree programmes. Finding also shows that E-learning plays an important role in teaching because it is oriented toward the use of information and communication technologies that have become a part of the everyday life and day-to-day business. E-learning contributes to traditional teaching methods and provides many advantages to society and citizens. The study recommends that the e-learning tools and internet facilities should be upgrade to foster any network challenges in the online facilitation and lecture delivery system.

Keywords: E-governance, E-learning, online distance learning, university education public servants, Nigeria

Procedia PDF Downloads 69

Authors: Priyanka Bhowmik, Subrata Majumdar, Debprasad Chattopadhyay

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Background: Cervical cancer is the third major cause of cancer in women and the second most frequent cause of cancer related deaths causing 300,000 deaths annually worldwide. Evasion of immune response by Human Papilloma Virus (HPV), the key contributing factor behind cancer and pre-cancerous lesions of the uterine cervix, makes immunotherapy a necessity to treat this disease. Objective: A Heat killed fraction of Mycobacterium indicus pranii (MIP), a non-pathogenic Mycobacterium has been shown to exhibit cytotoxic effects on different cancer cells, including human cervical carcinoma cell line HeLa. However, the underlying mechanisms remain unknown. The aim of this study is to decipher the mechanism of MIP induced HeLa cell death. Methods: The cytotoxicity of Mycobacterium indicus pranii against HeLa cells was evaluated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Apoptosis was detected by annexin V and Propidium iodide (PI) staining. The assessment of reactive oxygen species (ROS) generation and cell cycle analysis were measured by flow cytometry. The expression of apoptosis associated genes was analyzed by real time PCR. Result: MIP could inhibit the proliferation of HeLa cell in a time and dose dependent manner but caused minor damage to normal cells. The induction of apoptosis was confirmed by the cell surface presentation of phosphatidyl serine, DNA fragmentation, and mitochondrial damage. MIP caused very early (as early as 30 minutes) transcriptional activation of p53, followed by a higher activation (32 fold) at 24 hours suggesting prime importance of p53 in MIP-induced apoptosis in HeLa cell. The up regulation of p53 dependent pro-apoptotic genes Bax, Bak, PUMA, and Noxa followed a lag phase that was required for the transcriptional p53 program. MIP also caused the transcriptional up regulation of Toll like receptor 2 and 4 after 30 minutes of MIP treatment suggesting recognition of MIP by toll like receptors. Moreover, MIP caused the inhibition of expression of HPV anti apoptotic gene E6, which is known to interfere with p53/PUMA/Bax apoptotic cascade. This inhibition might have played a role in transcriptional up regulation of PUMA and subsequently apoptosis. ROS was generated transiently which was concomitant with the highest transcription activation of p53 suggesting a plausible feedback loop network of p53 and ROS in the apoptosis of HeLa cells. Scavenger of ROS, such as N-acetyl-L-cysteine, decreased apoptosis suggesting ROS is an important effector of MIP induced apoptosis. Conclusion: Taken together, MIP possesses full potential to be a novel therapeutic agent in the clinical treatment of cervical cancer.

Keywords: cancer, mycobacterium, immunity, immunotherapy.

Procedia PDF Downloads 249

Authors: Vahid Bairami Rad

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The intelligentization of agricultural fields can control the temperature, humidity, and variables affecting the growth of agricultural products online and on a mobile phone or computer. Smarting agricultural fields and gardens is one of the best and best ways to optimize agricultural equipment and has a 100 percent direct effect on the growth of plants and agricultural products and farms. Smart farms are the topic that we are going to discuss today, the Internet of Things and artificial intelligence. Agriculture is becoming smarter every day. From large industrial operations to individuals growing organic produce locally, technology is at the forefront of reducing costs, improving results and ensuring optimal delivery to market. A key element to having a smart agriculture is the use of useful data. Modern farmers have more tools to collect intelligent data than in previous years. Data related to soil chemistry also allows people to make informed decisions about fertilizing farmland. Moisture meter sensors and accurate irrigation controllers have made the irrigation processes to be optimized and at the same time reduce the cost of water consumption. Drones can apply pesticides precisely on the desired point. Automated harvesting machines navigate crop fields based on position and capacity sensors. The list goes on. Almost any process related to agriculture can use sensors that collect data to optimize existing processes and make informed decisions. The Internet of Things (IoT) is at the center of this great transformation. Internet of Things hardware has grown and developed rapidly to provide low-cost sensors for people's needs. These sensors are embedded in IoT devices with a battery and can be evaluated over the years and have access to a low-power and cost-effective mobile network. IoT device management platforms have also evolved rapidly and can now be used securely and manage existing devices at scale. IoT cloud services also provide a set of application enablement services that can be easily used by developers and allow them to build application business logic. Focus on yourself. These development processes have created powerful and new applications in the field of Internet of Things, and these programs can be used in various industries such as agriculture and building smart farms. But the question is, what makes today's farms truly smart farms? Let us put this question in another way. When will the technologies associated with smart farms reach the point where the range of intelligence they provide can exceed the intelligence of experienced and professional farmers?

Keywords: food security, IoT automation, wireless communication, hybrid lifestyle, arduino Uno

Procedia PDF Downloads 56

Authors: Jamuna Loganath

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Education is the key to the development of any individual’s personality. Today’s students will be tomorrow’s citizens of the global society. The education of the student is the edifice on which his/her future will be built. Schools therefore should provide an all-round development of students so as to foster a healthy society. The behaviors and the attitude of the students in school play an essential role for the success of the education process. Frequent reports of misbehaviors such as clowning, harassing classmates, verbal insults are becoming common in schools today. If this issue is left unattended, it may develop a negative attitude and increase the delinquent behavior. So, the need of the hour is to find a solution to this problem. To solve this issue, it is important to monitor the students’ behaviors in school and give necessary feedback and mentor them to develop a positive attitude and help them to become a successful grownup. Nevertheless, measuring students’ behavior and attitude is extremely challenging. None of the present technology has proven to be effective in this measurement process because actions, reactions, interactions, response of the students are rarely used in the course of the data due to complexity. The purpose of this proposal is to recommend an effective supervising system after carrying out a feasibility study by measuring the behavior of the Students. This can be achieved by equipping schools with CCTV cameras. These CCTV cameras installed in various schools of the world capture the facial expressions and interactions of the students inside and outside their classroom. The real time raw videos captured from the CCTV can be uploaded to the cloud with the help of a network. The video feeds get scooped into various nodes in the same rack or on the different racks in the same cluster in Hadoop HDFS. The video feeds are converted into small frames and analyzed using various Pattern recognition algorithms and MapReduce algorithm. Then, the video frames are compared with the bench marking database (good behavior). When misbehavior is detected, an alert message can be sent to the counseling department which helps them in mentoring the students. This will help in improving the effectiveness of the education process. As Video feeds come from multiple geographical areas (schools from different parts of the world), BIG DATA helps in real time analysis as it analyzes computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. It also analyzes data that can’t be analyzed by traditional software applications such as RDBMS, OODBMS. It has also proven successful in handling human reactions with ease. Therefore, BIG DATA could certainly play a vital role in handling this issue. Thus, effectiveness of the education process can be enhanced with the help of video analytics using the latest BIG DATA technology.

Keywords: big data, cloud, CCTV, education process

Procedia PDF Downloads 240

Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

Procedia PDF Downloads 418

Authors: Ruwani N. Nugara, Masashi Inafuku, Kensaku Takara, Hironori Iwasaki, Hirosuke Oku

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Pteryxin from the partially purified hexane phase (HP) of Peucedanum japonicum Thunb (PJT) was identified as the active compound related to anti-obesity. Thus, in this study we investigated the mechanisms related to anti-obesity activity in-vitro. The HP was fractionated, and effect on the triglyceride (TG) content was evaluated in 3T3-L1 and HepG2 cells. Comprehensive spectroscopic analyses were used to identify the structure of the active compound. The dose dependent effect of active constituent on the TG content, and the gene expressions related to adipogenesis, fatty acid catabolism, energy expenditure, lipolysis and lipogenesis (20 μg/mL) were examined in-vitro. Furthermore, higher dosage of pteryxin (50μg/mL) was tested against 20μg/mL in 3T3-L1 adipocytes. The mRNA were subjected to SOLiD next generation sequencer and the obtained data were analyzed by Ingenuity Pathway Analysis (IPA). The active constituent was identified as pteryxin, a known compound in PJT. However, its biological activities against obesity have not been reported previously. Pteryxin dose dependently suppressed TG content in both 3T3-L1 adipocytes and HepG2 hepatocytes (P < 0.05). Sterol regulatory element-binding protein-1 (SREBP1 c), Fatty acid synthase (FASN), and acetyl-CoA carboxylase-1 (ACC1) were downregulated in pteryxin-treated adipocytes (by 18.0, 36.1 and 38.2%; P < 0.05, respectively) and hepatocytes (by 72.3, 62.9 and 38.8%, respectively; P < 0.05) indicating its suppressive effects on fatty acid synthesis. The hormone-sensitive lipase (HSL), a lipid catabolising gene was upregulated (by 15.1%; P < 0.05) in pteryxin-treated adipocytes suggesting improved lipolysis. Concordantly, the adipocyte size marker gene, paternally expressed gene1/mesoderm specific transcript (MEST) was downregulated (by 42.8%; P < 0.05), further accelerating the lipolytic activity. The upregulated trend of uncoupling protein 2 (UCP2; by 77.5%; P < 0.05) reflected the improved energy expenditure due to pteryxin. The 50μg/mL dosage of pteryxin completely suppressed PPARγ, MEST, SREBP 1C, HSL, Adiponectin, Fatty Acid Binding Protein (FABP) 4, and UCP’s in 3T3-L1 adipocytes. The IPA suggested that pteryxin at 20μg/mL and 50μg/mL suppress obesity in two different pathways, whereas the WNT signaling pathway play a key role in the higher dose of pteryxin in preadipocyte stage. Pteryxin in PJT play the key role in regulating lipid metabolism related gene network and improving energy production in vitro. Thus, the results suggests pteryxin as a new natural compound to be used as an anti-obesity drug in pharmaceutical industry.

Keywords: obesity, peucedanum japonicum thunb, pteryxin, food science

Procedia PDF Downloads 453

Authors: Rafael do Amaral Teodoro, Leandro Augusto da Silva

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Originated from graphite, graphene is a two-dimensional (2D) material that promises to revolutionize technology in many different areas, such as energy, telecommunications, civil construction, aviation, textile, and medicine. This is possible because its structure, formed by carbon bonds, provides desirable optical, thermal, and mechanical characteristics that are interesting to multiple areas of the market. Thus, several research and development centers are studying different manufacturing methods and material applications of graphene, which are often compromised by the scarcity of more agile and accurate methodologies to characterize the material – that is to determine its composition, shape, size, and the number of layers and crystals. To engage in this search, this study proposes a computational methodology that applies deep learning to identify graphene oxide crystals in order to characterize samples by crystal sizes. To achieve this, a fully convolutional neural network called U-net has been trained to segment SEM graphene oxide images. The segmentation generated by the U-net is fine-tuned with a standard deviation technique by classes, which allows crystals to be distinguished with different labels through an object delimitation algorithm. As a next step, the characteristics of the position, area, perimeter, and lateral measures of each detected crystal are extracted from the images. This information generates a database with the dimensions of the crystals that compose the samples. Finally, graphs are automatically created showing the frequency distributions by area size and perimeter of the crystals. This methodological process resulted in a high capacity of segmentation of graphene oxide crystals, presenting accuracy and F-score equal to 95% and 94%, respectively, over the test set. Such performance demonstrates a high generalization capacity of the method in crystal segmentation, since its performance considers significant changes in image extraction quality. The measurement of non-overlapping crystals presented an average error of 6% for the different measurement metrics, thus suggesting that the model provides a high-performance measurement for non-overlapping segmentations. For overlapping crystals, however, a limitation of the model was identified. To overcome this limitation, it is important to ensure that the samples to be analyzed are properly prepared. This will minimize crystal overlap in the SEM image acquisition and guarantee a lower error in the measurements without greater efforts for data handling. All in all, the method developed is a time optimizer with a high measurement value, considering that it is capable of measuring hundreds of graphene oxide crystals in seconds, saving weeks of manual work.

Keywords: characterization, graphene oxide, nanomaterials, U-net, deep learning

Procedia PDF Downloads 160

Authors: Tanmaya Pradhan, K. Midhun, M. Joy Thomas

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Increasing the shelf life and improving the quality are important objectives for the success of packaged liquid food industry. One of the methods by which this can be achieved is by deactivating the micro-organisms present in the liquid food through pasteurization. Pasteurization is done by heating, but some serious disadvantages such as the reduction in food quality, flavour, taste, colour, etc. were observed because of heat treatment, which leads to the development of newer methods instead of pasteurization such as treatment using UV radiation, high pressure, nuclear irradiation, pulsed electric field, etc. In recent years the use of the pulsed electric field (PEF) for inactivation of the microbial content in the food is gaining popularity. PEF uses a very high electric field for a short time for the inactivation of microorganisms, for which we require a high voltage pulsed power source. Pulsed power sources used for PEF treatments are usually in the range of 5kV to 50kV. Different pulse shapes are used, such as exponentially decaying and square wave pulses. Exponentially decaying pulses are generated by high power switches with only turn-on capacity and, therefore, discharge the total energy stored in the capacitor bank. These pulses have a sudden onset and, therefore, a high rate of rising but have a very slow decay, which yields extra heat, which is ineffective in microbial inactivation. Square pulses can be produced by an incomplete discharge of a capacitor with the help of a switch having both on/off control or by using a pulse forming network. In this work, a pulsed power-based system is designed with the help of high voltage capacitors and solid-state switches (IGBT) for the inactivation of pathogenic micro-organism in liquid food such as fruit juices. The high voltage generator is based on the Marx generator topology, which can produce variable amplitude, frequency, and pulse width according to the requirements. Liquid food is treated in a chamber where pulsed electric field is produced between stainless steel electrodes using the pulsed output voltage of the supply. Preliminary bacterial inactivation tests were performed by subjecting orange juice inoculated with Escherichia Coli bacteria. With the help of the developed pulsed power source and the chamber, the inoculated orange has been PEF treated. The voltage was varied to get a peak electric field up to 15kV/cm. For a total treatment time of 200µs, a 30% reduction in the bacterial count has been observed. The detailed results and analysis will be presented in the final paper.

Keywords: Escherichia coli bacteria, high voltage generator, microbial inactivation, pulsed electric field, pulsed forming line, solid-state switch

Procedia PDF Downloads 184

Authors: Dino Carpentras, Alejandro Dinkelberg, Michael Quayle

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Within agent-based modeling, opinion dynamics is the field that focuses on modeling people's opinions. In this prolific field, most of the literature is dedicated to the exploration of the two 'degrees of freedom' and how they impact the model’s properties (e.g., the average final opinion, the number of final clusters, etc.). These degrees of freedom are (1) the interaction rule, which determines how agents update their own opinion, and (2) the network topology, which defines the possible interaction among agents. In this work, we show that the third degree of freedom exists. This can be used to change a model's output up to 100% of its initial value or to transform two models (both from the literature) into each other. Since opinion dynamics models are representations of the real world, it is fundamental to understand how people’s opinions can be measured. Even for abstract models (i.e., not intended for the fitting of real-world data), it is important to understand if the way of numerically representing opinions is unique; and, if this is not the case, how the model dynamics would change by using different representations. The process of measuring opinions is non-trivial as it requires transforming real-world opinion (e.g., supporting most of the liberal ideals) to a number. Such a process is usually not discussed in opinion dynamics literature, but it has been intensively studied in a subfield of psychology called psychometrics. In psychometrics, opinion scales can be converted into each other, similarly to how meters can be converted to feet. Indeed, psychometrics routinely uses both linear and non-linear transformations of opinion scales. Here, we analyze how this transformation affects opinion dynamics models. We analyze this effect by using mathematical modeling and then validating our analysis with agent-based simulations. Firstly, we study the case of perfect scales. In this way, we show that scale transformations affect the model’s dynamics up to a qualitative level. This means that if two researchers use the same opinion dynamics model and even the same dataset, they could make totally different predictions just because they followed different renormalization processes. A similar situation appears if two different scales are used to measure opinions even on the same population. This effect may be as strong as providing an uncertainty of 100% on the simulation’s output (i.e., all results are possible). Still, by using perfect scales, we show that scales transformations can be used to perfectly transform one model to another. We test this using two models from the standard literature. Finally, we test the effect of scale transformation in the case of finite precision using a 7-points Likert scale. In this way, we show how a relatively small-scale transformation introduces both changes at the qualitative level (i.e., the most shared opinion at the end of the simulation) and in the number of opinion clusters. Thus, scale transformation appears to be a third degree of freedom of opinion dynamics models. This result deeply impacts both theoretical research on models' properties and on the application of models on real-world data.

Keywords: degrees of freedom, empirical validation, opinion scale, opinion dynamics

Procedia PDF Downloads 119

Authors: Claire Norman-Maillet

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Insider fraud, including its various synonyms such as occupational, employee or internal fraud, is a major financial crime threat whereby an employee defrauds (or attempts to defraud) their current, prospective, or past employer. ‘Employee’ covers anyone employed by the company, including contractors, directors, and part time staff; they may be a solo bad actor or working in collusion with others, whether internal or external. Insider fraud is even more of a concern given the impacts of the Coronavirus pandemic, which has generated multiple opportunities to commit insider fraud. Insider fraud is something that is not necessarily thought of as a significant financial crime threat; the focus of most academics and practitioners has historically been on that of ‘external fraud’ against businesses or entities where an individual or group has no professional ties. Without the face-to-face, ‘over the shoulder’ capabilities of staff being able to keep an eye on their employees, there is a heightened reliance on trust and transparency. With this, naturally, comes an increased risk of insider fraud perpetration. The objective of the research is to better understand how companies are impacted by insider fraud, and therefore how to stop it. This research will make both an original contribution and stimulate debate within the financial crime field. The financial crime landscape is never static – criminals are always creating new ways to perpetrate financial crime, and new legislation and regulations are implemented as attempts to strengthen controls, in addition to businesses doing what they can internally to detect and prevent it. By focusing on insider fraud specifically, the research will be more specific and will be of greater use to those in the field. To achieve the aims of the research, semi-structured interviews were conducted with 22 individuals who either work in financial services and deal with insider fraud or work within insider fraud perpetration in a recruitment or advisory capacity. This was to enable the sourcing of information from a wide range of individuals in a setting where they were able to elaborate on their answers. The principal recruitment strategy was engaging with the researcher’s network on LinkedIn. The interviews were then transcribed and analysed thematically. Main findings in the research suggest that insider fraud has been ignored owing to the denial of accepting the possibility that colleagues would defraud their employer. Whilst Coronavirus has led to a significant rise in insider fraud, this type of crime has been a major risk to businesses since their inception, however have never been given the financial or strategic backing required to be mitigated, until it's too late. Furthermore, Coronavirus should have led to companies tightening their access rights, controls and policies to mitigate the insider fraud risk. However, in most cases this has not happened. The research concludes that insider fraud needs to be given a platform upon which to be recognised as a threat to any company and given the same level of weighting and attention by Executive Committees and Boards as other types of economic crime.

Keywords: fraud, insider fraud, economic crime, coronavirus, Covid-19

Procedia PDF Downloads 68

Authors: Kedar J. Mahadeshwar

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Concept introduction: This paper talks about how an innovative cloud based analytics enabled solution that could address a major industry challenge that is approaching all of us globally faster than what one would think. The world of supply chain for drugs and devices is changing today at a rapid speed. In the US, the Drug Supply Chain Security Act (DSCSA) is a new law for Tracing, Verification and Serialization phasing in starting Jan 1, 2015 for manufacturers, repackagers, wholesalers and pharmacies / clinics. Similarly we are seeing pressures building up in Europe, China and many countries that would require an absolute traceability of every drug and device end to end. Companies (both manufacturers and distributors) can use this opportunity not only to be compliant but to differentiate themselves over competition. And moreover a country such as UAE can be the leader in coming up with a global solution that brings innovation in this industry. Problem definition and timing: The problem of counterfeit drug market, recognized by FDA, causes billions of dollars loss every year. Even in UAE, the concerns over prevalence of counterfeit drugs, which enter through ports such as Dubai remains a big concern, as per UAE pharma and healthcare report, Q1 2015. Distribution of drugs and devices involves multiple processes and systems that do not talk to each other. Consumer confidence is at risk due to this lack of traceability and any leading provider is at risk of losing its reputation. Globally there is an increasing pressure by government and regulatory bodies to trace serial numbers and lot numbers of every drug and medical devices throughout a supply chain. Though many of large corporations use some form of ERP (enterprise resource planning) software, it is far from having a capability to trace a lot and serial number beyond the enterprise and making this information easily available real time. Solution: The solution here talks about a service provider that allows all subscribers to take advantage of this service. The solution allows a service provider regardless of its physical location, to host this cloud based traceability and analytics solution of millions of distribution transactions that capture lots of each drug and device. The solution platform will capture a movement of every medical device and drug end to end from its manufacturer to a hospital or a doctor through a series of distributor or retail network. The platform also provides advanced analytics solution to do some intelligent reporting online. Why Dubai? Opportunity exists with huge investment done in Dubai healthcare city also with using technology and infrastructure to attract more FDI to provide such a service. UAE and countries similar will be facing this pressure from regulators globally in near future. But more interestingly, Dubai can attract such innovators/companies to run and host such a cloud based solution and become a hub of such traceability globally.

Keywords: cloud, pharmaceutical, supply chain, tracking

Procedia PDF Downloads 526

Authors: Neha Pranav Kolhe, Harithapriya Vijaye, Arushi Kamle

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The economic growth engines are urban regions. As the economy expands, so does the need for peace and quiet, and noise pollution is one of the important social and environmental issue. Health and wellbeing are at risk from environmental noise pollution. Because of urbanisation, population growth, and the consequent rise in the usage of increasingly potent, diverse, and highly mobile sources of noise, it is now more severe and pervasive than ever before, and it will only become worse. Additionally, it will expand as long as there is an increase in air, train, and highway traffic, which continue to be the main contributors of noise pollution. The current study will be conducted in two zones of class I city of central India (population range: 1 million–4 million). Total 56 measuring points were chosen to assess noise pollution. The first objective evaluates the noise pollution in various urban habitats determined as formal and informal settlement. It identifies the comparison of noise pollution within the settlements using T- Test analysis. The second objective assess the noise pollution in silent zones (as stated in Central Pollution Control Board) in a hierarchical way. It also assesses the noise pollution in the settlements and compares with prescribed permissible limits using class I sound level equipment. As appropriate indices, equivalent noise level on the (A) frequency weighting network, minimum sound pressure level and maximum sound pressure level were computed. The survey is conducted for a period of 1 week. Arc GIS is used to plot and map the temporal and spatial variability in urban settings. It is discovered that noise levels at most stations, particularly at heavily trafficked crossroads and subway stations, were significantly different and higher than acceptable limits and squares. The study highlights the vulnerable areas that should be considered while city planning. The study demands area level planning while preparing a development plan. It also demands attention to noise pollution from the perspective of residential and silent zones. The city planning in urban areas neglects the noise pollution assessment at city level. This contributes to that, irrespective of noise pollution guidelines, the ground reality is far away from its applicability. The result produces incompatible land use on a neighbourhood scale with respect to noise pollution. The study's final results will be useful to policymakers, architects and administrators in developing countries. This will be useful for noise pollution in urban habitat governance by efficient decision making and policy formulation to increase the profitability of these systems.

Keywords: noise pollution, formal settlements, informal settlements, built environment, silent zone, residential area

Procedia PDF Downloads 118

Authors: Thor Alexis Sazon, Alexander Guzman-Urbina, Yasuhiro Fukushima

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This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system.

Keywords: solar photovoltaic, fuzzy logic, inference system, artificial neural networks

Procedia PDF Downloads 164

Authors: Bagam Venkateswarlu

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NMDC Limited, Indian multinational mining company operates under administrative control of Ministry of Steel, Government of India. This study is undertaken to evaluate how sustainable mining practiced by the company fulfils the provisions of Indian Constitution to secure to its citizen – justice, equality of status and opportunity, promoting social, economic, political, and religious wellbeing. The Constitution of India lays down a road map as to how the goal of being a “Welfare State” shall be achieved. The vision of sustainable mining being practiced is oriented along the constitutional responsibilities on Indian Citizens and the Corporate World. This qualitative study shall be backed by quantitative studies of National Mineral Development Corporation performances in various domains of sustainable mining and ESG, that is, environment, social and governance parameters. For example, Five Star Rating of mine is a comprehensive evaluation system introduced by Ministry of Mines, Govt. of India is one of the methodologies. Corporate Social Responsibilities is one of the thrust areas for securing social well-being. Green energy initiatives in and around the mines has given the title of “Eco-Friendly Miner” to NMDC Limited. While operating fully mechanized large scale iron ore mine (18.8 million tonne per annum capacity) in Bacheli, Chhattisgarh, M/s NMDC Limited caters to the needs of mineral security of State of Chhattisgarh and Indian Union. It preserves forest, wild-life, and environment heritage of richly endowed State of Chhattisgarh. In the remote and far-flung interiors of Chhattisgarh, NMDC empowers the local population by providing world class educational & medical facilities, transportation network, drinking water facilities, irrigational agricultural supports, employment opportunities, establishing religious harmony. All this ultimately results in empowered, educated, and improved awareness in population. Thus, the basic tenets of constitution of India- secularism, democracy, welfare for all, socialism, humanism, decentralization, liberalism, mixed economy, and non-violence is fulfilled. Constitution declares India as a welfare state – for the people, of the people and by the people. The sustainable mining practices by NMDC are in line with the objective. Thus, the purpose of study is fully met with. The potential benefit of the study includes replicating this model in existing or new establishments in various parts of country – especially in the under-privileged interiors and far-flung areas which are yet to see the lights of development.

Keywords: ESG values, Indian constitution, NMDC limited, sustainable mining, CSR, green energy

Procedia PDF Downloads 75

Authors: S. I. Mwasha, Z. Robinson, M. Musgrave

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Communities, especially in the global south, have been reported to have low adaptive capacity to cope with climate change impacts. As an attempt to improve adaptive capacity, most studies have focused on understanding the access of the household resources which can contribute to resilience against changes. However, little attention has been shown in uncovering how the household resources could be used and their implications to resilience against weather related shocks. By using a case study qualitative study, this project analyzed the trends in livelihoods practices and their implication to social equity. The study was done in three different villages within Kilimanjaro region. Each in different agro ecological zone. Two focus group discussions in two agro-ecological zones were done, one for women and another one for men except in the third zone where focus group participant were combined together (due to unforeseen circumstances). In the focus group discussion, several participatory rural appraisal tools were used to understand trend in crops and animal production and the use in which it is made: climate trends, soil fertility, trees and other livelihoods resources. Data were analyzed using thematic network analysis. Using an amalgam of magnitude (to note weather comments made were positive or negative) and descriptive coding (to note the topic), six basic themes were identified under social equity: individual ownership, family ownership, love and respect, women no education, women access to education as well as women access to loans. The results implied that despite mum and dad in the family providing labor in the agro pastoral activities, there were separations on who own what, as well as individual obligations in the family. Dad owned mostly income creating crops and mum, food crops. therefore, men controlled the economy which made some of them become arrogant and spend money to meet their interests sometimes not taking care of the family. Separation in ownership was reported to contribute to conflicts in the household as well as causing controversy on the use income is spent. Men were reported to use income to promote matriarchy system. However, as women were capacitated through access to education and loans they become closer to their husband and get access to own and plan the income together for the interest of the family. Joint ownership and planning on the household resources were reported to be important if families have to better adapt to climate change. The aim of this study is not to show women empowerment and joint ownership and planning as only remedy for low adaptive capacity. There is the need to understand other practices that either directly or indirectly impacts environmental integrity, food security and economic development for household resilience against changing climate.

Keywords: adaptive capacity, climate change, resilience, women empowerment

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Authors: Selin Top, Raul Marcos, M. Sinan Bilgili

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Although there have been several studies related to collection, temporary storage, handling and disposal of solid wastes generated by hospitals, there are only a few studies related to liquid wastes generated by hospitals or hospital wastewaters. There is an important amount of water consumptions in hospitals. While minimum domestic water consumption per person is 100 L/day, water consumption per bed in hospitals is generally ranged between 400-1200 L. This high amount of consumption causes high amount of wastewater. The quantity of wastewater produced in a hospital depends on different factors: bed numbers, hospital age, accessibility to water, general services present inside the structure (kitchen, laundry, laboratory, diagnosis, radiology, and air conditioning), number and type of wards and units, institution management policies and awareness in managing the structure in safeguarding the environment, climate and cultural and geographic factors. In our country, characterization of hospital wastewaters conducted by classical parameters in a very few studies. However, as mentioned above, this type of wastewaters may contain different compounds than domestic wastewaters. Hospital Wastewater (HWW) is wastewater generated from all activities of the hospital, medical and non medical. Nowadays, hospitals are considered as one of the biggest sources of wastewater along with urban sources, agricultural effluents and industrial sources. As a health-care waste, hospital wastewater has the same quality as municipal wastewater, but may also potentially contain various hazardous components due to using disinfectants, pharmaceuticals, radionuclides and solvents making not suitable the connection of hospital wastewater to the municipal sewage network. These characteristics may represent a serious health hazard and children, adults and animals all have the potential to come into contact with this water. Therefore, the treatment of hospital wastewater is an important current interest point to focus on. This paper aims to approach on the investigation of hospital wastewater treatment by membrane systems. This study aim is to determined hospital wastewater’s characterization and also evaluates the efficiency of hospital wastewater treatment by high pressure filtration systems such as ultrafiltration (UF). Hospital wastewater samples were taken directly from sewage system from Şişli Etfal Training and Research Hospital, located in the district of Şişli, in the European part of Istanbul. The hospital is a 784 bed tertiary care center with a daily outpatient department of 3850 patients. Ultrafiltration membrane is used as an experimental treatment and the influence of the pressure exerted on the membranes was examined, ranging from 1 to 3 bar. The permeate flux across the membrane was observed to define the flooding membrane points. The global COD and BOD5 removal efficiencies were 54% and 75% respectively for ultrafiltration, all the SST removal efficiencies were above 90% and a successful removal of the pathological bacteria measured was achieved.

Keywords: hospital wastewater, membrane, ultrafiltration, treatment

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Authors: Bhavana Gulaty, Arshia Chaudhri

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Great civic projects contribute integrally to a city, and every city undergoes a recurring cycle of urban transformations and regeneration by their insertion. The M.I.C.E. (Meetings, Incentives, Convention and Exhibitions) industry is the forbearer of one category of such catalytic civic projects. Through a specific focus on M.I.C.E. destinations, this paper illustrates the multifarious dimensions that urban catalysts impact the city on S.P.U.R. (Seed. Profile. Urbane. Reflections), the theoretical framework of this paper aims to unearth these dimensions in the realm of the COEX (Convention & Exhibition) biosphere. The ‘COEX Biosphere’ is the filter of such catalysts being ecosystems unto themselves. Like a ripple in water, the impact of these strategic interventions focusing on art, culture, trade, and promotion expands right from the trigger; the immediate context to the region and subsequently impacts the global scale. These ripples are known to bring about significant economic, social, and political and network changes. The COEX inventory in the Asian context has one such prominent addition; the proposed India International Convention and Exhibition Centre (IICC) at New Delhi. It is envisioned to be the largest facility in Asia currently and would position India on the global M.I.C.E map. With the first phase of the project scheduled to open for use in the end of 2019, this flagship project of the Government of India is projected to cater to a peak daily footfall of 3,20,000 visitors and estimated to generate 5,00,000 jobs. While the economic benefits are yet to manifest in real time and ‘Good design is good business’ holds true, for the urban transformation to be meaningful, the benefits have to go beyond just a balance sheet for the city’s exchequer. This aspect has been found relatively unexplored in research on these developments. The methodology for investigation will comprise of two steps. The first will be establishing an inventory of the global success stories and associated benefits of COEX projects over the past decade. The rationale for capping the timeframe is the significant paradigm shift that has been observed in their recent conceptualization; for instance ‘Innovation Districts’ conceptualised in the city of Albuquerque that converges into the global economy. The second step would entail a comparative benchmarking of the projected transformations by IICC through a toolkit of parameters. This is posited to yield a matrix that can form the test bed for mapping the catalytic trajectory for projects in the pipeline globally. As a ready reckoner, it purports to be a catalyst to substantiate decision making in the planning stage itself for future projects in similar contexts.

Keywords: catalysts, COEX, M.I.C.E., urban transformations

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Authors: Shayla He

Abstract:

Background and Purpose: According to Chamie (2017), it’s estimated that no less than 150 million people, or about 2 percent of the world’s population, are homeless. The homeless population in the United States has grown rapidly in the past four decades. In New York City, the sheltered homeless population has increased from 12,830 in 1983 to 62,679 in 2020. Knowing the trend on the homeless population is crucial at helping the states and the cities make affordable housing plans, and other community service plans ahead of time to better prepare for the situation. This study utilized the data from New York City, examined the key factors associated with the homelessness, and developed systematic modeling to predict homeless populations of the future. Using the best model developed, named HP-RNN, an analysis on the homeless population change during the months of 2020 and 2021, which were impacted by the COVID-19 pandemic, was conducted. Moreover, HP-RNN was tested on the data from Seattle. Methods: The methodology involves four phases in developing robust prediction methods. Phase 1 gathered and analyzed raw data of homeless population and demographic conditions from five urban centers. Phase 2 identified the key factors that contribute to the rate of homelessness. In Phase 3, three models were built using Linear Regression, Random Forest, and Recurrent Neural Network (RNN), respectively, to predict the future trend of society's homeless population. Each model was trained and tuned based on the dataset from New York City for its accuracy measured by Mean Squared Error (MSE). In Phase 4, the final phase, the best model from Phase 3 was evaluated using the data from Seattle that was not part of the model training and tuning process in Phase 3. Results: Compared to the Linear Regression based model used by HUD et al (2019), HP-RNN significantly improved the prediction metrics of Coefficient of Determination (R2) from -11.73 to 0.88 and MSE by 99%. HP-RNN was then validated on the data from Seattle, WA, which showed a peak %error of 14.5% between the actual and the predicted count. Finally, the modeling results were collected to predict the trend during the COVID-19 pandemic. It shows a good correlation between the actual and the predicted homeless population, with the peak %error less than 8.6%. Conclusions and Implications: This work is the first work to apply RNN to model the time series of the homeless related data. The Model shows a close correlation between the actual and the predicted homeless population. There are two major implications of this result. First, the model can be used to predict the homeless population for the next several years, and the prediction can help the states and the cities plan ahead on affordable housing allocation and other community service to better prepare for the future. Moreover, this prediction can serve as a reference to policy makers and legislators as they seek to make changes that may impact the factors closely associated with the future homeless population trend.

Keywords: homeless, prediction, model, RNN

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