Search results for: quantity estimation

Authors: M. Devaki, K. B. Jayanthi

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The identification of water bodies from satellite images has recently received a great deal of attention. Different methods have been developed to distinguish water bodies from various satellite images that vary in terms of time and space. Urban water identification issues body manifests in numerous applications with a great deal of certainty. There has been a sharp rise in the usage of satellite images to map natural resources, including urban water bodies and forests, during the past several years. This is because water and forest resources depend on each other so heavily that ongoing monitoring of both is essential to their sustainable management. The relevant elements from satellite pictures have been chosen using a variety of techniques, including machine learning. Then, a convolution neural network (CNN) architecture is created that can identify a superpixel as either one of two classes, one that includes water or doesn't from input data in a complex metropolitan scene. The deep learning technique, CNN, has advanced tremendously in a variety of visual-related tasks. CNN can improve classification performance by reducing the spectral-spatial regularities of the input data and extracting deep features hierarchically from raw pictures. Calculate the water body using the satellite image's resolution. Experimental results demonstrate that the suggested method outperformed conventional approaches in terms of water extraction accuracy from remote-sensing images, with an average overall accuracy of 97%.

Keywords: water body, Deep learning, satellite images, convolution neural network

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Authors: Feng-Ming Fan, Xiu-Hui Wen, Po-Feng Chen, Yi-Ching Tu

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Because of inborn natural conditions and man-made sabotage, the water resources insufficient phenomenon in Taiwan is a very important issue needed to face immediately. The regulations and law of water resources protection and recycling are gradually completed now but still lack of specific water recycling effectiveness checking method. The research focused on the industrial parks that already had been certificated with EIA to establish a professional checking system, carry through and forge ahead to contribute one’s bit in water resources sustainable usage. Taiwan Government Policies of Environmental Impact Assessment established in 1994, some development projects were requested to set certain water recycling ratio for water resources effective usage. The water covers and contains everything because all-inclusive companies enter and be stationed. For control the execution status of industrial park water and waste water recycling ratio about EIA commitment effectively, we invited experts and scholars in this filed to discuss with related organs to formulate the policy and audit plan. Besides, call a meeting to set public version water equilibrium diagrams and recycles parameter. We selected nine industrial parks that were requested set certain water recycling ratio in EIA examination stage and then according to the water usage quantity, we audited 340 factories in these industrial parks with spot and documents examination and got fruitful results – the average water usage of unit area per year of all these examined industrial parks is 31,000 tons/hectare/year, the value is just half of Taiwan industries average. It is obvious that the industrial parks with EIA commitment can decrease the water resources consumption effectively. Taiwan government policies of Environmental Impact Assessment took follow though tracking function into consideration at the beginning. The results of this research verify the importance of the implementing with water recycling to save water resources in EIA commitment. Inducing development units to follow EIA commitment to get the balance between environmental protection and economic development is one of the important EIA value.

Keywords: Taiwan government policies of environmental impact assessment, water recycling ratio of EIA commitment, water resources sustainable usage, water recycling

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Authors: Ofosuhene O. Apenteng, Noor Azina Ismail

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The human immunodeficiency virus (HIV) that causes acquired immune deficiency syndrome (AIDS) remains a global cause of morbidity and mortality. It has caused panic since its emergence. Relationships between migration and HIV/AIDS have become complex. In the absence of prospectively designed studies, dynamic mathematical models that take into account the migration movement which will give very useful information. We have explored the utility of mathematical models in understanding transmission dynamics of HIV and AIDS and in assessing the magnitude of how migration has impact on the disease. The model was calibrated to HIV and AIDS incidence data from Malaysia Ministry of Health from the period of 1986 to 2011 using Bayesian analysis with combination of Markov chain Monte Carlo method (MCMC) approach to estimate the model parameters. From the estimated parameters, the estimated basic reproduction number was 22.5812. The rate at which the susceptible individual moved to HIV compartment has the highest sensitivity value which is more significant as compared to the remaining parameters. Thus, the disease becomes unstable. This is a big concern and not good indicator from the public health point of view since the aim is to stabilize the epidemic at the disease-free equilibrium. However, these results suggest that the government as a policy maker should make further efforts to curb illegal activities performed by migrants. It is shown that our models reflect considerably the dynamic behavior of the HIV/AIDS epidemic in Malaysia and eventually could be used strategically for other countries.

Keywords: epidemic model, reproduction number, HIV, MCMC, parameter estimation

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Authors: N. A. P. Camaforte, P. M. P. Vareda, L. L. Saldanha, A. L. Dokkedal, J. M. Rezende-Neto, M. R. Senger, F. P. Silva-Jr, J. R. Bosqueiro

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Diabetes mellitus is a disease characterized by deficiency of insulin secretion and/or action which results in hyperglycemia. Nowadays, acarbose is a medicine used by diabetic people to inhibit alpha-glucosidases leading to the decreasing of post-feeding glycaemia, but with low effectiveness and many side effects. Medicinal plants have been used for the treatment of many diseases including diabetes and their action occurs through the modulation of insulin-depending processes, pancreas regeneration or inhibiting glucose absorption by the intestine. Previous studies in our laboratory showed that the treatment using two crude extracts of plants from Brazilian cerrado was able to decrease fasting blood glucose and improve glucose tolerance in streptozotocin-diabetic mice. Because of this and the importance of the search for new alternatives to decrease the hyperglycemia, we decided to evaluate the inhibitory action of two plants from Brazilian cerrado - B.H. and Myrcia bella. The enzymatic assay was performed in 50 µL of final volume using pancreatic α-amylase and maltase together with theirs commercial substrates. The inhibition potency (IC50) was determined by the incubation of eight different concentrations of both extracts and the enzymes for 5 minutes at 37ºC. After, the substrate was added to start the reaction. Glucosidases assay was evaluated measuring the quantity of p-nitrophenol in 405 nmin 384 wells automatic reader. The in vitro assay with the extracts of B.H. and M. bella showed an IC50 of 28,04µg/mL and 16,93 µg/mL for α-amilase, and 43,01µg/mL and 17 µg/mL for maltase, respectively. M. bella extract showed a higher inhibitory activity for those enzymes than B.H. extract. The crude extracts tested showed a higher inhibition rate to α-amylase, but were less effective against maltase in comparison to acarbose (IC50 36µg/mL and 9 µg/mL, respectively). In conclusion, the crude extract of B.H. and M. bella showed a potent inhibitory effect against α-amylase and showed promising results to the possible development of new medicines to treat diabetes with less or even without side effects.

Keywords: alfa-glucosidases, diabetes mellitus, glycaemia, medicinal plants

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Authors: Khandoker Akib Mohammad

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While analyzing time-to-event data, it is possible that a certain fraction of subjects will never experience the event of interest, and they are said to be cured. When this feature of survival models is taken into account, the models are commonly referred to as cure models. In the presence of covariates, the conditional survival function of the population can be modelled by using the cure model, which depends on the probability of being uncured (incidence) and the conditional survival function of the uncured subjects (latency), and a combination of logistic regression and Cox proportional hazards (PH) regression is used to model the incidence and latency respectively. In this paper, we have shown the asymptotic normality of the profile likelihood estimator via asymptotic expansion of the profile likelihood and obtain the explicit form of the variance estimator with an implicit function in the profile likelihood. We have also shown the efficient score function based on projection theory and the profile likelihood score function are equal. Our contribution in this paper is that we have expressed the efficient information matrix as the variance of the profile likelihood score function. A simulation study suggests that the estimated standard errors from bootstrap samples (SMCURE package) and the profile likelihood score function (our approach) are providing similar and comparable results. The numerical result of our proposed method is also shown by using the melanoma data from SMCURE R-package, and we compare the results with the output obtained from the SMCURE package.

Keywords: Cox PH model, cure model, efficient score function, EM algorithm, implicit function, profile likelihood

Procedia PDF Downloads 136

Authors: Oludamilare Bode Adewuyi, Yanxia Sun, Isaiah Gbadegesin Adebayo

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Voltage stability analysis is crucial to the reliable and economic operation of power systems. The power system of developing nations is more susceptible to failures due to the continuously increasing load demand, which is not matched with generation increase and efficient transmission infrastructures. Thus, most power systems are heavily stressed, and the planning of extra generation from distributed generation sources needs to be efficiently done so as to ensure the security of the power system. Some voltage stability index-based approach for DG siting has been reported in the literature. However, most of the existing voltage stability indices, though sufficient, are found to be inaccurate, especially for overloaded power systems. In this paper, the performance of a relatively different approach using a line voltage stability margin indicator, which has proven to have better accuracy, has been presented and compared with a conventional line voltage stability index for DG siting using the Nigerian 28 bus system. Critical boundary index (CBI) for voltage stability margin estimation was deployed to identify suitable locations for DG placement, and the performance was compared with DG placement using the Novel Line Stability Index (NLSI) approach. From the simulation results, both CBI and NLSI agreed greatly on suitable locations for DG on the test system; while CBI identified bus 18 as the most suitable at system overload, NLSI identified bus 8 to be the most suitable. Considering the effect of the DG placement at the selected buses on the voltage magnitude profile, the result shows that the DG placed on bus 18 identified by CBI improved the performance of the power system better.

Keywords: voltage stability analysis, voltage collapse, voltage stability index, distributed generation

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Authors: Mohammadreza Delfieh, Seyed Ali Mohammad Modarres Sanavy, Rouzbeh Farhoudi

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Fennel is of most important medicinal plants which is widely used in food and pharmaceutical industries. In order to investigate the effect of different nitrogen nutritional systems including chemical, organic and biologic ones at different plant densities on yield, yield components and seed essential oil content and yield of this valuable medicinal plant, a field experiment was carried out in 2013-2014 agricultural season at Islamic Azad University of Shoushtar agricultural college in split plot design with 18 treatments and based on completely randomized blocks design. Different nitrogen system treatments consisting of: 1. N1 or control (Uniformly spreading urea fertilizer in the plot, 50% at planting time and 50% at stem elongation), 2. N2 (Uniformly spreading 50% of urea fertilizer in the plot at planting time and spraying the other 50% of urea fertilizer at stem elongation on fennel foliage), 3. N3 or cow manure, 4. N4 or biofertilizer (Inoculation of fennel seeds with Azotobacter and Azospirillum), 5. N5 or Integrated-1 (Cow manure + uniformly spreading urea fertilizer in the plot at stem elongation), 6. N6 or Integrated-2 (Cow manure + Inoculation of fennel seeds with Azotobacter and Azospirillum) were applied to the main plots. Three fennel densities consisting of: 1. FD1 (60 plant/m2), 2. FD2 (80 plant/m2) and 3. FD3 (100 plant/m2) were applied to subplots. Results showed that all of the traits were significantly affected by applied treatments (P 0.01). The interaction between treatments also were significant at 5 percent level for shoot dry weight and at 1 percent level for other traits. Based on the results, using the Integrated-1 treatment at 100 plant per m2 produced 94.575 g/m2 seed yield containing 3.375 percent of essential oil. Utilization of such combination not only could lead to a desirable fennel quantity and quality, but also is more consistent with environment.

Keywords: fennel (foeniculum vulgare mill.), nutritional system, nitrogen, biofertilizer, organic fertilizer, chemical fertilizer, density

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Authors: Reina Kawase, Yuzuru Matsuoka

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To mitigate climate change, to reduce CO2 emission from steel sector, energy intensive sector, is essential. One of the effective countermeasure is recycling of iron scrap and shifting to electric arc furnace. This research analyzes the feasibility of iron scrap recycling with considering demand-supply balance and quantifies the effective by CO2 emission reduction. Generally, the quality of steel made from iron scrap is lower than the quality of steel made from basic oxygen furnace. So, the constraint of demand side is goods-wise steel demand and that of supply side is generation of iron scap. Material Stock and Flow Model (MSFM_demand) was developed to estimate goods-wise steel demand and generation of iron scrap and was applied to 35 regions which aggregated countries in the world for 2005-2050. The crude steel production was estimated under two case; BaU case (No countermeasures) and CM case (With countermeasures). For all the estimation periods, crude steel production is greater than generation of iron scrap. This makes it impossible to substitute electric arc furnaces for all the basic oxygen furnaces. Even though 100% recycling rate of iron scrap, under BaU case, CO2 emission in 2050 increases by 12% compared to that in 2005. With same condition, 32% of CO2 emission reduction is achieved in CM case. With a constraint from demand side, the reduction potential is 6% (CM case).

Keywords: iron scrap recycling, CO2 emission reduction, steel demand, MSFM demand

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Authors: RAM PAL SINGH, VIKASH CHAUDHARY, MONIKA VERMA

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In this paper, we proposed the implementation of optimization based Extreme Learning Machine (ELM) for watermarking of B-channel of color image in discrete wavelet transform (DWT) domain. ELM, a regularization algorithm, works based on generalized single-hidden-layer feed-forward neural networks (SLFNs). However, hidden layer parameters, generally called feature mapping in context of ELM need not to be tuned every time. This paper shows the embedding and extraction processes of watermark with the help of ELM and results are compared with already used machine learning models for watermarking.Here, a cover image is divide into suitable numbers of non-overlapping blocks of required size and DWT is applied to each block to be transformed in low frequency sub-band domain. Basically, ELM gives a unified leaning platform with a feature mapping, that is, mapping between hidden layer and output layer of SLFNs, is tried for watermark embedding and extraction purpose in a cover image. Although ELM has widespread application right from binary classification, multiclass classification to regression and function estimation etc. Unlike SVM based algorithm which achieve suboptimal solution with high computational complexity, ELM can provide better generalization performance results with very small complexity. Efficacy of optimization method based ELM algorithm is measured by using quantitative and qualitative parameters on a watermarked image even though image is subjected to different types of geometrical and conventional attacks.

Keywords: BER, DWT, extreme leaning machine (ELM), PSNR

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Authors: Stephane Laussac, Jacques Piazzola, Gilles Tedeschi

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Estimation of the impact of atmospheric aerosols on the climate evolution is an important scientific challenge. One of a major source of particles is constituted by the oceans through the generation of sea-spray aerosols. In coastal areas, marine aerosols can affect air quality through their ability to interact chemically and physically with other aerosol species and gases. The integration of accurate sea-spray emission terms in modeling studies is then required. However, it was found that sea-spray concentrations are not represented with the necessary accuracy in some situations, more particularly at short fetch. In this study, the WRF-Chem model was implemented on a North-Western Mediterranean coastal region. WRF-Chem is the Weather Research and Forecasting (WRF) model online-coupled with chemistry for investigation of regional-scale air quality which simulates the emission, transport, mixing, and chemical transformation of trace gases and aerosols simultaneously with the meteorology. One of the objectives was to test the ability of the WRF-Chem model to represent the fine details of the coastal geography to provide accurate predictions of sea spray evolution for different fetches and the anthropogenic aerosols. To assess the performance of the model, a comparison between the model predictions using a local emission inventory and the physicochemical analysis of aerosol concentrations measured for different wind direction on the island of Porquerolles located 10 km south of the French Riviera is proposed.

Keywords: sea-spray aerosols, coastal areas, sea-spray concentrations, short fetch, WRF-Chem model

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Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: artificial neural networks, fuel consumption, friedman test, machine learning, statistical hypothesis testing

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Authors: Abimbola M. Enitan, J. Adeyemo

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Anaerobic modeling is a useful tool to describe and simulate the condition and behaviour of anaerobic treatment units for better effluent quality and biogas generation. The present investigation deals with the anaerobic treatment of brewery wastewater with varying organic loads. The chemical oxygen demand (COD) and total suspended solids (TSS) of the influent and effluent of the bioreactor were determined at various retention times to generate data for kinetic coefficients. The bio-kinetic coefficients in the modified Stover–Kincannon kinetic and methane generation models were determined to study the performance of anaerobic digestion process. At steady-state, the determination of the kinetic coefficient (K), the endogenous decay coefficient (Kd), the maximum growth rate of microorganisms (µmax), the growth yield coefficient (Y), ultimate methane yield (Bo), maximum utilization rate constant Umax and the saturation constant (KB) in the model were calculated to be 0.046 g/g COD, 0.083 (dˉ¹), 0.117 (d-¹), 0.357 g/g, 0.516 (L CH4/gCODadded), 18.51 (g/L/day) and 13.64 (g/L/day) respectively. The outcome of this study will help in simulation of anaerobic model to predict usable methane and good effluent quality during the treatment of industrial wastewater. Thus, this will protect the environment, conserve natural resources, saves time and reduce cost incur by the industries for the discharge of untreated or partially treated wastewater. It will also contribute to a sustainable long-term clean development mechanism for the optimization of the methane produced from anaerobic degradation of waste in a close system.

Keywords: brewery wastewater, methane generation model, environment, anaerobic modeling

Procedia PDF Downloads 259

Authors: Maria A. Castillo H., Andrés R. Leandro C.

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During the last decades, agricultural productivity in Latin America has increased with precision agriculture and more efficient agricultural technologies. The use of automated systems, satellite images, geographic information systems, and tools for data analysis, and artificial intelligence have contributed to making more effective strategic decisions. Twenty years ago, the state of Mérida, located in the Venezuelan Andes, reported the largest area covered by greenhouses in the country, where certified seeds of potatoes, vegetables, ornamentals, and flowers were produced for export and consumption in the central region of the country. In recent years, it is estimated that production under greenhouses has changed, and the area covered has decreased due to different factors, but there are few historical statistical data in sufficient quantity and quality to support this estimate or to be used for analysis and decision making. The objective of this study is to compare data collected about geoposition, use, and covered areas of the greenhouses in 2007 to data available in 2021, as support for the analysis of the current situation of horticultural production in the main municipalities of the state of Mérida. The document presents the development of the work in the diagnosis and integration of geographic coordinates in GIS and data analysis phases. As a result, an evaluation of the process is made, a dashboard is presented with the most relevant data along with the geographical coordinates integrated into GIS, and an analysis of the obtained information is made. Finally, some recommendations for actions are added, and works that expand the information obtained and its geographical traceability over time are proposed. This study contributes to granting greater certainty in the supporting data for the evaluation of social, environmental, and economic sustainability indicators and to make better decisions according to the sustainable development goals in the area under review. At the same time, the methodology provides improvements to the agricultural data collection process that can be extended to other study areas and crops.

Keywords: greenhouses, geographic information system, protected agriculture, data analysis, Venezuela

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Authors: Nader Khalafian, Mohsen Ghaderi

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Field observations have revealed many examples of structures which were damaged due to ground surface deformation caused by the faulting phenomena. In this paper some efforts were made in order to estimate the length and location of the ground surface where large displacements were created due to the reverse faulting. This research has conducted in two steps; (1) in the first step, a 2D explicit finite element model were developed using ABAQUS software. A subroutine for Mohr-Coulomb failure criterion with strain softening model was developed by the authors in order to properly model the stress strain behavior of the soil in the fault rapture zone. The results of the numerical analysis were verified with the results of available centrifuge experiments. Reasonable coincidence was found between the numerical and experimental data. (2) In the second step, the effects of the fault dip angle (δ), depth of soil layer (H), dilation and friction angle of sand (ψ and φ) and the amount of fault offset (d) on the soil surface displacement and fault rupture path were investigated. An artificial neural network-based model (ANN), as a powerful prediction tool, was developed to generate a general model for predicting faulting characteristics. A properly sized database was created to train and test network. It was found that the length and location of the zone of displaced ground surface can be accurately estimated using the proposed model.

Keywords: reverse faulting, surface deformation, numerical, neural network

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Authors: H. Aljabiry, L. Bailey, S. Young

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Qatar is a desert with an average temperature 37⁰C, reaching over 40⁰C during summer. Precipitation is uncommon and mostly in winter. Qatar depends on desalination for drinking water and on groundwater and recycled water for irrigation. Water consumption and network leakage per capita in Qatar are amongst the highest in the world; re-use of treated wastewater is extremely limited with only 14% of treated wastewater being used for irrigation. This has led to the country disposing of unwanted water from various sources in lagoons situated around the country, causing concern over the possibility of environmental pollution. Accordingly, our hypothesis underpinning this research is that the quality and quantity of water in lagoons is having an impact on the groundwater reservoirs in Qatar. Lagoons (n = 14) and wells (n = 55) were sampled for both summer and winter in 2018 (summer and winter). Water, adjoining soil and plant samples were analysed for multiple elements by Inductively Coupled Plasma Mass Spectrometry. Organic and inorganic carbon were measured (CN analyser) and the major anions were determined by ion chromatography. Salinization in both the lagoon and the wells was seen with good correlations between Cl⁻, Na⁺, Li, SO₄, S, Sr, Ca, Ti (p-value < 0.05). Association of heavy metals was observed of Ni, Cu, Ag, and V, Cr, Mo, Cd which is due to contamination from anthropological activities such as wastewater disposal or spread of contaminated dust. However, looking at each elements none of them exceeds the Qatari regulation. Moreover, gypsum saturation in the system was observed in both the lagoon and wells water samples. Lagoons and the water of the well are found to be of a saline type as well as Ca²⁺, Cl⁻, SO₄²⁻ type evidencing both gypsum dissolution and salinization in the system. Moreover, Maps produced by Inverse distance weighting showed an increasing level of Nitrate in the groundwater in winter, and decrease chloride and sulphate level, indicating recharge effect after winter rain events. While E. coli and faecal bacteria were found in most of the lagoons, biological analysis for wells needs to be conducted to understand the biological contamination from lagoon water infiltration. As a conclusion, while both the lagoon and the well showed the same results, more sampling is needed to understand the impact of the lagoons on the groundwater.

Keywords: groundwater quality, lagoon, treated wastewater, water management, wastewater treatment, wetlands

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Authors: Behzad Hajalilou, Nasim Hajalilou, Saeid Ansari

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The study area is located in East Azerbaijan province, north of Ahar city, and 1/100000 geological map of Varzgan. This region is located in the middle of Iran zone. Ali Javad Porphyry copper-gold ore deposit has been created in a magmatic complex containing intrusive masses, combining Granodiorite and quartz Monzonite that penetrates into the Eocene volcanic aggregate. The most important mineralization includes primary oxides minerals (magnetite), sulfide (pyrite, chalcopyrite, Molybdenite, Bornite, Chalcocite, Covollite), secondary oxide or hydroxide minerals (hematite, goethite, limonite), and carbonate (malachite and Azurite). The mineralization forms into the vein-veinlets and scattered system. The alterations observed in the region include intermediate Argillic, advanced Argillic, Phyllic, silica, Propylitic, chlorite and Potassic. The 3D model of mineralization of the Alijavad is provided by Data DATAMINE software and based on the study of 700 polished sections of 32 drilled boreholes in the region. This model is completely compatible with the model provided by Lowell and Gilbert for the mineralization of porphyry copper deposits of quartz Monzonite type. The estimated cumulative residual value of copper for Ali Javad deposit is 81.5 million tons with 0.75 percent of copper, and for gold is 8.37 million tons with 1.8 ppm.

Keywords: porphyry copper, mineralization, Ali Javad, modeling, reserve estimation

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Authors: Christine O. Wangia, Jennifer A. Orwa, Francis W. Muregi, Patrick G. Kareru, Kipyegon Cheruiyot, Eric Guantai

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Ruellia (syn. Dipteracanthus) species are wild perennial creepers belonging to the Acanthaceae family. These species are reported to possess anti-inflammatory, analgesic, antioxidant, gastroprotective, anticancer, and immuno-stimulant properties. Phytochemical screening of both aqueous and methanolic extracts of Ruellia species revealed the presence of saponins. Saponins have been reported to possess anti-inflammatory, antioxidant, immuno-stimulant, antihepatotoxic, antibacterial, anticarcinogenic, and antiulcerogenic activities. The objective of this study was to quantify and analyze the Fourier transform infrared (FTIR) spectra of saponins in crude extracts of three Kenyan Ruellia species namely Ruellia prostrata (RPM), Ruellia lineari-bracteolata (RLB) and Ruellia bignoniiflora (RBK). Sequential organic extraction of the ground whole plant material was done using petroleum ether (PE), chloroform, ethyl acetate (EtOAc), and absolute methanol by cold maceration, while aqueous extraction was by hot maceration. The plant powders and extracts were mixed with spectroscopic grade KBr and compressed into a pellet. The infrared spectra were recorded using a Shimadzu FTIR spectrophotometer of 8000 series in the range of 3500 cm^-1 - 500 cm^-1. Quantitative determination of the saponins was done using standard procedures. Quantitative analysis of saponins showed that RPM had the highest quantity of crude saponins (2.05% ± 0.03), followed by RLB (1.4% ± 0.15) and RBK (1.25% ± 0.11), respectively. FTIR spectra revealed the spectral peaks characteristic for saponins in RPM, RLB, and RBK plant powders, aqueous and methanol extracts; O-H absorption (3265 - 3393 cm^-1), C-H absorption ranging from 2851 to 2924 cm^-1, C=C absorbance (1628 - 1655 cm^-1), oligosaccharide linkage (C-O-C) absorption due to sapogenins (1036 - 1042 cm^-1). The crude saponins from RPM, RLB and RBK showed similar peaks to their respective extracts. The presence of the saponins in extracts of RPM, RLB and RBK may be responsible for some of the biological activities reported in the Ruellia species.1

Keywords: Ruellia bignoniiflora, Ruellia linearibracteolata, Ruellia prostrata, Saponins

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Authors: Taha Anjamrooz, Sareh Rajabi, Hasan Mahmmud, Ghassan Abulebdeh

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Water availability, as well as water demand, are not uniformly distributed in time and space. Numerous extra-large water diversion projects are launched in Amazon to alleviate water scarcities. This research utilizes statistical analysis to examine the temporal and spatial features of 40 extra-large water diversion projects in Amazon. Using a network analysis method, the correlation between seven major basins is measured, while the impact analysis method is employed to explore the associated economic, environmental, and social impacts. The study unearths that the development of water diversion in Amazon has witnessed four stages, from a preliminary or initial period to a phase of rapid development. It is observed that the length of water diversion channels and the quantity of water transferred have amplified significantly in the past five decades. As of 2015, in Amazon, more than 75 billion m³ of water was transferred amidst 12,000 km long channels. These projects extend over half of the Amazon Area. The River Basin E is currently the most significant source of transferred water. Through inter-basin water diversions, Amazon gains the opportunity to enhance the Gross Domestic Product (GDP) by 5%. Nevertheless, the construction costs exceed 70 billion US dollars, which is higher than any other country. The average cost of transferred water per unit has amplified with time and scale but reduced from western to eastern Amazon. Additionally, annual total energy consumption for pumping exceeded 40 billion kilowatt-hours, while the associated greenhouse gas emissions are assessed to be 35 million tons. Noteworthy to comprehend that ecological problems initiated by water diversion influence the River Basin B and River Basin D. Due to water diversion, more than 350 thousand individuals have been relocated, away from their homes. In order to enhance water diversion sustainability, four categories of innovative measures are provided for decision-makers: development of water tradeoff projects strategies, improvement of integrated water resource management, the formation of water-saving inducements, and pricing approach, and application of ex-post assessment.

Keywords: sustainability, water trade-off projects, environment, Amazon

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Authors: Maxime Alex Junior Kuitche, Ruxandra Mihaela Botez, Jean-Chirstophe Maunand

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The evolution of aircraft is closely linked to the study and improvement of propulsion systems. Determining the propulsion performance is a real challenge in aircraft modeling and design. In addition to theoretical methodologies, experimental procedures are used to obtain a good estimation of the propulsion performances. For piston-propeller propulsion, the propeller needs several experimental tests which could be extremely demanding in terms of time and money. This paper presents a new procedure to estimate the performance of a propeller from a numerical approach using computational fluid dynamic analysis. The propeller was initially scanned, and then, its 3D model was represented using CATIA. A structured meshing and Shear Stress Transition k-ω turbulence model were applied to describe accurately the flow pattern around the propeller. Thus, the Partial Differential Equations were solved using ANSYS FLUENT software. The method was applied on the UAS-S45’s propeller designed and manufactured by Hydra Technologies in Mexico. An extensive investigation was performed for several flight conditions in terms of altitudes and airspeeds with the aim to determine thrust coefficients, power coefficients and efficiency of the propeller. The Computational Fluid Dynamics results were compared with experimental data acquired from wind tunnel tests performed at the LARCASE Price-Paidoussis wind tunnel. The results of this comparison have demonstrated that our approach was highly accurate.

Keywords: CFD analysis, propeller performance, unmanned aerial system propeller, UAS-S45

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Authors: Kanupreiya, Rajani Sharma

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Construction of a single underground structure is itself a challenging task, and it becomes more critical in tectonically active young mountains such as the Himalayas which are highly anisotropic. The Himalayan geology mostly comprises of incompetent and sheared rock mass in addition to fold/faults, rock burst, and water ingress. Underground tunnels form the most essential and important structure in run-of-river hydroelectric projects. Punatsangchhu I hydroelectric project (PHEP-I), Bhutan (1200 MW) is a run-of-river scheme which has four parallel underground desilting chambers. The Punatsangchhu River carries a large quantity of silt load during monsoon season. Desilting chambers were provided to remove the silt particles of size greater than and equal to 0.2 mm with 90% efficiency, thereby minimizing the rate of damage to turbines. These chambers are 330 m long, 18 m wide at the center and 23.87 m high, with a 5.87 m hopper portion. The geology of desilting chambers was known from an exploratory drift which exposed low dipping foliation joint and six joint sets. The RMR and Q value in this reach varied from 40 to 60 and 1 to 6 respectively. This paper describes different rock engineering principles undertaken for safe excavation and rock support of the moderately jointed, blocky and thinly foliated biotite gneiss. For the design of rock support system of desilting chambers, empirical and numerical analysis was adopted. Finite element analysis was carried out for cavern design and finalization of pillar width using Phase2. Phase2 is a powerful tool for simulation of stage-wise excavation with simultaneous provision of support system. As the geology of the region had 7 sets of joints, in addition to FEM based approach, safety factors for potentially unstable wedges were checked using UnWedge. The final support recommendations were based on continuous face mapping, numerical modelling, empirical calculations, and practical experiences.

Keywords: dam siltation, Himalayan geology, hydropower, rock support, numerical modelling

Procedia PDF Downloads 86

Authors: Claudia Troccoli

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Childbearing constitutes one of the key factors affecting labour market differences between men and women, accounting for almost a quarter of the gender wage gap. Family leave policies, such as maternity, paternity, and parental leave, represent potential key policy tools to address these inequalities, as they can promote mothers' job continuity and career progression. This paper analyses four major reforms implemented in Finland between the 1960s and the early 1980s. It studies the effects of these maternity and parental leave extensions on mothers' short- and long-run labour market outcomes. Eligibility to longer leave was determined on the basis of the child's date of birth. Therefore, estimation of the causal effects of the reforms is possible by exploiting random variation in children's birthdates and comparing the outcomes of mothers giving birth just before and just after the reform cutoff date. Overall, the three maternity leave reforms did not significantly improve mothers' earnings or employment rates. On the contrary, the estimates, although imprecise, seem to indicate negative effects on women's labour market outcomes. The extension of parental leave is, on the other hand, the only reform that improved mothers' short- and long-term labour market outcomes, both in terms of earnings and employment rate. At the same time, fathers appeared to be negatively affected by the reform. These results provide suggestive evidence that shareable parental leave might have more beneficial effects on mothers' job continuity, as it weakens the connotation of childcare as a task reserved for mothers.

Keywords: family policies, Finland, maternal labour market outcomes, maternity leave

Procedia PDF Downloads 132

Authors: Carolina Zambrana, Grover Zurita

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The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.

Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence

Procedia PDF Downloads 72

Authors: Maletsema Alina Mofokeng, Nemera Shargie

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Sorghum is one of the most important cereal crops grown as a source of calories for many people in tropics and sub-tropics of the world. Proper characterisation and evaluation of crop germplasm is an important component for effective management of genetic resources and their utilisation in the improvement of the crop through plant breeding. The objective of the study was to estimate the genetic diversity present in sorghum accessions grown in South Africa using agro-morphological traits and some nutritional contents. The experiment was carried out in Potchefstroom. Data were subjected to correlations, principal components analysis, and hierarchical clustering using GenStat statistical software. There were highly significance differences among the accessions based on agro-morphological and nutritional quality traits. Grain yield was highly positively correlated with panicle weight. Plant height was highly significantly correlated with internode length, leaf length, leaf number, stem diameter, the number of nodes and starch content. The Principal component analysis revealed three most important PCs with a total variation of 78.6%. The protein content ranged from 7.7 to 14.7%, and starch ranged from 58.52 to 80.44%. The accessions that had high protein and starch content were AS16cyc and MP4277. There was vast genetic diversity observed among the accessions assessed that can be used by plant breeders to improve yield and nutritional traits.

Keywords: accessions, genetic diversity, nutritional quality, sorghum

Procedia PDF Downloads 258

Authors: Hasna Elalaoui Elabdallaoui, Abdelaziz Elfazziki, Mohamed Sadgal

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Outlines: The social economy is a moral approach to solidarity applied to the projects’ development. To reconcile economic activity and social equity, crowdfunding is as an alternative means of financing social projects. Several collaborative blockchain platforms exist. It eliminates the need for a central authority or an inconsiderate middleman. Also, the costs for a successful crowdfunding campaign are reduced, since there is no commission to be paid to the intermediary. It improves the transparency of record keeping and delegates authority to authorities who may be prone to corruption. Objectives: The objectives are: to define a software infrastructure for projects’ participatory financing within a social and solidarity economy, allowing transparent, secure, and fair management and to have a financial mechanism that improves financial inclusion. Methodology: The proposed methodology is: crowdfunding platforms literature review, financing mechanisms literature review, requirements analysis and project definition, a business plan, Platform development process and implementation technology, and testing an MVP. Contributions: The solution consists of proposing a new approach to crowdfunding based on Islamic financing, which is the principle of Mousharaka inspired by Islamic financing, which presents a financial innovation that integrates ethics and the social dimension into contemporary banking practices. Conclusion: Crowdfunding platforms need to secure projects and allow only quality projects but also offer a wide range of options to funders. Thus, a framework based on blockchain technology and Islamic financing is proposed to manage this arbitration between quality and quantity of options. The proposed financing system, "Musharaka", is a mode of financing that prohibits interests and uncertainties. The implementation is offered on the secure Ethereum platform as investors sign and initiate transactions for contributions using their digital signature wallet managed by a cryptography algorithm and smart contracts. Our proposal is illustrated by a crop irrigation project in the Marrakech region.

Keywords: social economy, Musharaka, blockchain, smart contract, crowdfunding

Procedia PDF Downloads 71

Authors: Ali Kharazi, Hassanali Aghajani, Hesami Azizi

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Tourism entrepreneurship is a growing field that has the potential to create new opportunities for sustainable development. The purpose of this study is to identify and classify the entrepreneurial opportunities in the blind tourism industry in Khuzestan Province of Iran that can be created through the operation of blinds’ tours. This study used a mixed methods approach. The qualitative data was collected through semi-structured interviews with 15 tourist guides and tourism activists, while the quantitative data was collected through a questionnaire survey of 40 blind people who had participated in blinds’ tours. The findings of this study suggest that there are a number of entrepreneurial opportunities in the blind tourism industry in Khuzestan Province, including (1) developing and providing accessible tourism services, such as tours, accommodations, restaurants, and transportation, (2) creating and marketing blind-friendly tourism products and experiences (3) training and educating tourism professionals on how to provide accessible and inclusive tourism services. This study contributes to the theoretical understanding of tourism entrepreneurship by providing insights into the entrepreneurial opportunities in the blind tourism industry. The findings of this study can be used to develop policies and programs that support the development of the blind tourism industry. The qualitative data were analyzed using content analysis. The quantitative data were analyzed using descriptive statistics and inferential statistics. This study examines the entrepreneurial opportunities within the blind tourism industry in Khuzestan Province, Iran. In addition, Khuzestan province has made relatively good development in the field of blinds’ tourism. Blind tourists have become loyal customers of blinds’ tours, which has increased their self-confidence and social participation. Tourist guides and centers of tourism services are interested in participating in blinds’ tours more than before, and even other parts outside the tourism field have encouraged sponsorship. Education had a great impact on the quality of tourism services, especially for the blind. It has played a significant role in improving the quality of tourism services for the blind. However, the quality and quantity of infrastructure should be increased in different sectors of tourism services to foster future growth. These opportunities can be used to create new businesses and jobs and to promote sustainable development in the region.

Keywords: entrepreneurship, tourism, blind, sustainable development, Khuzestan

Procedia PDF Downloads 63

Authors: Selamawit Dires, Solomon Tesfamariam, Thomas Tannert

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Modern earthquake engineering and design encompass performance-based design philosophy. The main objective in performance-based design is to achieve a system performing precisely to meet the design objectives so to reduce unintended seismic risks and associated losses. Energy-based earthquake-resistant design is one of the design methodologies that can be implemented in performance-based earthquake engineering. In energy-based design, the seismic demand is usually described as the ratio of the hysteretic to input energy. Once the hysteretic energy is known as a percentage of the input energy, it is distributed among energy-dissipating components of a structure. The hysteretic to input energy ratio is highly dependent on the inherent damping of a structural system. In numerical analysis, damping can be modeled as stiffness-proportional, mass-proportional, or a linear combination of stiffness and mass. In this study, the effect of mathematical modeling of damping on the estimation of seismic energy demands is investigated by considering elastic-perfectly-plastic single-degree-of-freedom systems representing short to long period structures. Furthermore, the seismicity of Vancouver, Canada, is used in the nonlinear time history analysis. According to the preliminary results, the input energy demand is not sensitive to the type of damping models deployed. Hence, consistent results are achieved regardless of the damping models utilized in the numerical analyses. On the other hand, the hysteretic to input energy ratios vary significantly for the different damping models.

Keywords: damping, energy-based seismic design, hysteretic energy, input energy

Procedia PDF Downloads 162

Authors: Violina Angelova, Galina Pevicharova

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A comparative research had been carried out to allow us to determine the quantities and the centers of accumulation of Pb, Cu, Zn and Cd in the vegetative and reproductive organs of the sweet potatoes and to ascertain the possibilities for growing them on soils, polluted with heavy metals. The experiments were performed on agricultural fields contaminated by the (1) Non-Ferrous-Metal Works near Plovdiv, (2) Lead and Zinc Complex near Kardjali and (3) a copper smelter near Pirdop, Bulgaria. The soils used in this experiment were characterized by acid, neutral and slightly alkaline reaction, loamy texture and a moderate content of organic matter. The total content of Zn, Pb, and Cd was high and exceeded the limit value in agriculture soils. Sweet potatoes were in a 2-year rotation scheme on three blocks in the experimental field. On reaching commercial ripeness the sweet potatoes were gathered and the contents of heavy metals in their different parts – root, tuber (peel and core), leaves and stems, were determined after microwave mineralization. The quantitative measurements were carried out with inductively coupled plasma atomic emission spectroscopy. The contamination of the sweet potatoes was due mainly to the presence of heavy metals in the soil, which entered the plants through their root system, as well as by diffusion through the peel. Pb, Cu, Zn, and Cd were selectively accumulated in the underground parts of the sweet potatoes, and most of all in the root system and the peel. Heavy metals have an impact on the development and productivity of the sweet potatoes. The high anthropogenic contamination leads to an increased assimilation of heavy metals which reduces the yield and the quality of the production of sweet potatoes, as well as leads to decrease of the absolute dry substance and the quantity of sugars in sweet potatoes. Sweet potatoes could be grown on soils, which are light to medium polluted with lead, zinc, and cadmium, as they do not accumulate these elements. On heavily polluted soils, however, (Pb – 1504 mg/kg, Zn – 3322 mg/kg, Cd – 47 mg/kg) the growing of sweet potatoes is not allowed, as the accumulation of Pb and Cd in the core of the potatoes exceeds the Maximum Acceptable Concentration. Acknowledgment: The authors gratefully acknowledge the financial support by the Bulgarian National Science Fund (Project DFNI DH04/9).

Keywords: heavy metals, polluted soils, sweet potatoes, uptake

Procedia PDF Downloads 201

Authors: H. Yousefnia, S. Zolghadri

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An early diagnosis of bone metastases is very important for providing a profound decision on a subsequent therapy. A prerequisite for the clinical application of new diagnostic radiopharmaceutical is the measurement of organ radiation exposure dose from biodistribution data in animals. In this study, the dosimetric studies of a novel agent for SPECT-imaging of bone methastases, 111In-(4-{[(bis(phosphonomethyl))carbamoyl]methyl}-7,10-bis(carboxymethyl)-1,4,7,10-tetraazacyclododec-1-yl) acetic acid (111In-BPAMD) complex, have been estimated in human organs based on mice data. The radiolabeled complex was prepared with high radiochemical purity at the optimal conditions. Biodistribution studies of the complex were investigated in male Syrian mice at selected times after injection (2, 4, 24 and 48 h). The human absorbed dose estimation of the complex was performed based on mice data by the radiation absorbed dose assessment resource (RADAR) method. 111In-BPAMD complex was prepared with high radiochemical purity >95% (ITLC) and specific activities of 2.85 TBq/mmol. Total body effective absorbed dose for 111In-BPAMD was 0.205 mSv/MBq. This value is comparable to the other 111In clinically used complexes. The results show that the dose to critical organs the complex is well within the acceptable considered range for diagnostic nuclear medicine procedures. Generally, 111In-BPAMD has interesting characteristics and can be considered as a viable agent for SPECT-imaging of the bone metastases in the near future.

Keywords: In-111, BPAMD, absorbed dose, RADAR

Procedia PDF Downloads 474

Authors: Yan-Wen Wang, Chu-Yang Chou, Jen-Cheng Wang, Min-Sheng Liao, Hsuan-Hsiang Hsu, Cheng-Ying Chou, Chen-Kang Huang, Kun-Chang Kuo, Joe-Air Jiang

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Performance-related parameters of high concentration photovoltaic (HCPV) modules (e.g. current and voltage) are required when estimating the maximum power point using numerical and approximation methods. The maximum power point on the characteristic curve for a photovoltaic module varies when temperature or solar radiation is different. It is also difficult to estimate the output performance and maximum power point (MPP) due to the special characteristics of HCPV modules. Based on the p-n junction semiconductor theory, a brand new and simple method is presented in this study to directly evaluate the MPP of HCPV modules. The MPP of HCPV modules can be determined from an irradiated I-V characteristic curve, because there is a non-linear relationship between the temperature of a solar cell and solar radiation. Numerical simulations and field tests are conducted to examine the characteristics of HCPV modules during maximum output power tracking. The performance of the presented method is evaluated by examining the dependence of temperature and irradiation intensity on the MPP characteristics of HCPV modules. These results show that the presented method allows HCPV modules to achieve their maximum power and perform power tracking under various operation conditions. A 0.1% error is found between the estimated and the real maximum power point.

Keywords: energy performance, high concentrated photovoltaic, maximum power point, p-n junction semiconductor

Procedia PDF Downloads 575

Authors: Edoghogho Ogbeifun, Charles Mbohwa, J. H. C. Pretorius

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Effective infrastructure development scheme planned and executed has positive influence on the quantity of available stock of infrastructure to meet the immediate and expansion needs of an organization, as well as contribute to the overall economic development of a nation, community or the local entity where the infrastructure is hosted. It is noteworthy, however, that infrastructure development scheme spans a long time frame, usually longer than the political life of the administration that initiates the scheme. In the majority of circumstances, execution may start and achieve different levels of completion; at best, only limited numbers are completed and put into functional use during the life of the administration that initiated the infrastructure scheme. When there is a change in leadership, many of the uncompleted projects are usually abandoned. The new administration repeats the circle of its predecessors and develops another set of infrastructure scheme which will suffer similar fate as the ones developed by their predecessors; thus doting the landscape with many uncompleted projects, which leads to infrastructure deficit. These circle will continue unless each succeeding leader sees governance as single continuum. Therefore, infrastructure projects not completed by one administration should be continued by succeeding administration, in order to increase the stock of relevant infrastructure available for the smooth operations organization and enhance the needed developments, as well as reduce the negative effects of infrastructure deficit. The single case study of qualitative research method was adopted to investigate the actions of the administration of three successive Vice-Chancellors, in a higher education institution in Nigeria, over a longitudinal period of twelve years. This is with a view to exploring the effects of each administration on the development and execution of infrastructure projects, with particular interest on abandoned projects. The findings revealed that although two of Vice-Chancellors were committed to infrastructure upgrade, they executed more new projects than completing abandoned ones, while the current leader has shown more pragmatism in completing abandoned projects alongside constructing new ones; thus demonstrating the importance of the continuity of governance. In this regard, there is a steady increase in the stock of infrastructure to accommodate the expansion of existing academic programmes, host new ones as well as reduce the negative effects of infrastructure deficit caused by abandoned projects.

Keywords: abandoned projects, continuity of governance, infrastructure development scheme, long time frame

Procedia PDF Downloads 175