Search results for: production costs
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9008

Search results for: production costs

6368 Managing Configuration Management in Different Types of Organizations

Authors: Dilek Bilgiç

Abstract:

Configuration Management (CM) is a discipline assuring the consistency between product information the reality all along the product lifecycle. Although the extensive benefits of this discipline, such as the direct impact on increasing return on investment, reducing lifecycle costs, are realized by most organizations. It is worth evaluating that CM functions might be successfully implemented in some organized anarchies. This paper investigates how to manage ambiguity in CM processes as an opportunity within an environment that has different types of complexities and choice arenas. It is not explained how to establish a configuration management organization in a company; more specifically, it is analyzed how to apply configuration management processes when different types of streams exist. From planning to audit, all the CM functions may provide different organization learning opportunities when those applied with the right leadership methods.

Keywords: configuration management, leadership, organizational analysis, organized anarchy, cm process, organizational learning, organizational maturity, configuration status accounting, leading innovation, change management

Procedia PDF Downloads 208
6367 Tower Crane Selection and Positioning on Construction Sites

Authors: Dirk Briskorn, Michael Dienstknecht

Abstract:

Cranes are a key element in construction projects as they are the primary lifting equipment and among the most expensive construction equipment. Thus, selecting cranes and locating them on-site is an important factor for a project's profitability. We focus on a site with supply and demand areas that have to be connected by tower cranes. There are several types of tower cranes differing in certain specifications such as costs or operating radius. The objective is to select cranes and determine their locations such that each demand area is connected to its supply area at minimum cost. We detail the problem setting and show how to obtain a discrete set of candidate locations for each crane type without losing optimality. This discretization allows us to reduce our problem to the classic set cover problem. Despite its NP-hardness, we achieve good results employing a standard solver and a greedy heuristic, respectively.

Keywords: positioning, selection, standard solver, tower cranes

Procedia PDF Downloads 367
6366 Solutions of Fuzzy Transportation Problem Using Best Candidates Method and Different Ranking Techniques

Authors: M. S. Annie Christi

Abstract:

Transportation Problem (TP) is based on supply and demand of commodities transported from one source to the different destinations. Usual methods for finding solution of TPs are North-West Corner Rule, Least Cost Method Vogel’s Approximation Method etc. The transportation costs tend to vary at each time. We can use fuzzy numbers which would give solution according to this situation. In this study the Best Candidate Method (BCM) is applied. For ranking Centroid Ranking Technique (CRT) and Robust Ranking Technique have been adopted to transform the fuzzy TP and the above methods are applied to EDWARDS Vacuum Company, Crawley, in West Sussex in the United Kingdom. A Comparative study is also given. We see that the transportation cost can be minimized by the application of CRT under BCM.

Keywords: best candidate method, centroid ranking technique, fuzzy transportation problem, robust ranking technique, transportation problem

Procedia PDF Downloads 291
6365 Integration of Constraints Related to Composite Materials in the Design of Industrial Products

Authors: A. Boumedine, K. Benfriha, S. Lecheb

Abstract:

Manufacturing methods for products and structures made of composite materials reduce the number of parts and integrate technical functions, this advantage of composite materials leads to a lot of innovation but also to a reduction of costs and a gain in quality. A material has attributes: its density, it’s resistance, it’s cost, it’s resistance to corrosion. For the design of a product, a certain profile of these attributes is required: low density, resistance removed, low cost. The problem is then to identify this attribute profile and to compare it with those of the materials, in order to find the one that comes closest. The aim of this work is to demonstrate the feasibility of characterizing a mini turbine made of 3D printed fiber-filled composite material by the process of additive manufacturing, then compare the performance of the alloy turbine with the composite turbine according to the results of the simulation by Abaqus software.

Keywords: additive manufacturing, composite materials, design, 3D printer, turbine

Procedia PDF Downloads 127
6364 Esterification Reaction of Stearic Acid with Methanol Over Surface Functionalised PAN Fibrous Solid Acid Catalyst

Authors: Rawaz A. Ahmed, Katherine Huddersman

Abstract:

High-lipid Fats, Oils and Grease (FOGs) from wastewater are underutilized despite their potential for conversion into valuable fuels; this work describes a surface-functionalized fibrous Polyacrylonitrile (PAN) mesh as a novel heterogeneous acid catalyst for the conversion of free fatty acids (FFAs), via a catalytic esterification process into biodiesel. The esterification of stearic acid (SA) with methanol was studied over an acidified PAN solid acid catalyst. Disappearance of the carboxylic acid (C=O) peak of the stearic acid at 1696 cm-1 in the FT-IR spectrum with the associated appearance of the ester (C=O) peak at 1739 cm-1 confirmed the production of the methyl stearate. This was further supported by 1H NMR spectra with the appearance of the ester (-CH₂OCOR) at 3.60-3.70 ppm. Quantitate analysis by GC-FID showed the catalyst has excellent activity with >95 % yield of methyl stearate (MS) at 90 ◦C after 3 h and a molar ratio of methanol to SA of 35:1. To date, to our best knowledge, there is no research in the literature on the esterification reaction for biodiesel production using a modified PAN mesh as a catalyst. It is noteworthy that this acidified PAN mesh catalyst showed comparable activity to conventional Brönsted acids, namely H₂SO₄ and p-TSA, as well as exhibiting higher activity than various other heterogeneous catalysts such as zeolites, ion-exchange resins and acid clay.

Keywords: fats oil and greases (FOGs), free fatty acid, esterification reaction, methyl ester, PAN

Procedia PDF Downloads 228
6363 Postmodernism and Metanarrative: Deconstruction of Narrative in a Song of Ice and Fire Fantasy TV Series

Authors: Narjes Azimi

Abstract:

It has been a while that narrative and storytelling turned to be the inevitable part of media. The narrative has so many aspects and among those entire aspects, the fantasy genre is consciously challenging one as fantasy readers are used to reading narratives like good versus evil plot. This paper will analyze the ASOIF TV series as a Meta narrative cultural production that deconstructs the elements of a traditional narrative. This study will shade on a grand narrative perspective from poststructuralism point of view. The theoretical framework is structuralism and post structuralism. Lyotard and Barthes are two main poststructuralists and focus of the study. Lyotard grand narrative elements will analyze in this research study. Fantasy genre generated a number of outstanding authors that explore innovative perspectives. Among all these leading authors George R.R Martin is one of the best. George R. R. Martin’s Fantasy a Song of Ice and Fire picturized the brutal world that seven kingdoms struggling for the power. Since 2011 this production has been followed and watched by millions of audiences all around the world. The methodology is the textual analysis of selected scenes. Martin’s distinctive fantasy style which makes it different from other fantasies, yet this shift does not negate how the previous fantasy writers represent the mentioned concepts of war, and etc., but Martin’ fantasy and left the mature audiences full of uncertainty.

Keywords: narrative theory, metanarrative, deconstruction, post-structuralism, Lyotard, Barthes

Procedia PDF Downloads 288
6362 Flexural Strength of Alkali Resistant Glass Textile Reinforced Concrete Beam with Prestressing

Authors: Jongho Park, Taekyun Kim, Jungbhin You, Sungnam Hong, Sun-Kyu Park

Abstract:

Due to the aging of bridges, increasing of maintenance costs and decreasing of structural safety is occurred. The steel corrosion of reinforced concrete bridge is the most common problem and this phenomenon is accelerating due to abnormal weather and increasing CO2 concentration due to climate change. To solve these problems, composite members using textile have been studied. A textile reinforced concrete can reduce carbon emissions by reduced concrete and without steel bars, so a lot of structural behavior studies are needed. Therefore, in this study, textile reinforced concrete beam was made and flexural test was performed. Also, the change of flexural strength according to the prestressing was conducted. As a result, flexural strength of TRC with prestressing was increased compared and flexural behavior was shown as reinforced concrete.

Keywords: AR-glass, flexural strength, prestressing, textile reinforced concrete

Procedia PDF Downloads 325
6361 Quality and Quantity in the Strategic Network of Higher Education Institutions

Authors: Juha Kettunen

Abstract:

This study analyzes the quality and the size of the strategic network of higher education institutions. The study analyses the concept of fitness for purpose in quality assurance. It also analyses the transaction costs of networking that have consequences on the number of members in the network. Empirical evidence is presented of the Consortium on Applied Research and Professional Education, which is a European strategic network of six higher education institutions. The results of the study support the argument that the number of members in the strategic network should be relatively small to provide high quality results. The practical importance is that networking has been able to promote international research and development projects. The results of this study are important for those who want to design and improve international networks in higher education.

Keywords: balanced scorecard, higher education, social networking, strategic planning

Procedia PDF Downloads 340
6360 Product Quality and Profitability of Sea Bream Fish Farms in Greece

Authors: C. Nathanailides, S. Anastasiou, P. Logothetis, G. Kanlis

Abstract:

Production parameters of gilt head sea bream fish farm such as feeding regimes, mortalities, fish densities were used to calculate the economic efficiency of six different aquaculture sites from West Greece. Samples of farmed sea bream were collected and lipid content, microbial load and filleting yield of the samples were used as quality criteria. The results indicate that Lipid content, filleting yield and microbial load of fish originating from different fish farms varied significantly with improved quality exhibited in fish farms which exhibited improved Feed conversion rates and lower mortalities. Changes in feeding management practices such as feed quality and feeding regimes have a significant impact on the financial performance of sea bass farms. Fish farms which exhibited improved feeding conversion rates also exhibited increased profitability. Improvements in the FCR explained about 13.4 % of the difference in profitability of the different aquaculture sites. Lower mortality and higher growth rates were also exhibited by the fish farms which exhibited improved FCR. It is concluded that best feeding management practices resulted in improved product quality and profitability.

Keywords: aquaculture economics, gilt head sea, production fish, feeding management

Procedia PDF Downloads 496
6359 Wind Power Forecasting Using Echo State Networks Optimized by Big Bang-Big Crunch Algorithm

Authors: Amir Hossein Hejazi, Nima Amjady

Abstract:

In recent years, due to environmental issues traditional energy sources had been replaced by renewable ones. Wind energy as the fastest growing renewable energy shares a considerable percent of energy in power electricity markets. With this fast growth of wind energy worldwide, owners and operators of wind farms, transmission system operators, and energy traders need reliable and secure forecasts of wind energy production. In this paper, a new forecasting strategy is proposed for short-term wind power prediction based on Echo State Networks (ESN). The forecast engine utilizes state-of-the-art training process including dynamical reservoir with high capability to learn complex dynamics of wind power or wind vector signals. The study becomes more interesting by incorporating prediction of wind direction into forecast strategy. The Big Bang-Big Crunch (BB-BC) evolutionary optimization algorithm is adopted for adjusting free parameters of ESN-based forecaster. The proposed method is tested by real-world hourly data to show the efficiency of the forecasting engine for prediction of both wind vector and wind power output of aggregated wind power production.

Keywords: wind power forecasting, echo state network, big bang-big crunch, evolutionary optimization algorithm

Procedia PDF Downloads 566
6358 Immobilization of β-Galactosidase from Kluyveromyces Lactis on Polyethylenimine-Agarose for Production of Lactulose

Authors: Carlos A. C. G. Neto, Natan C. G. Silva, Thais O. Costa, Luciana R. B. Goncalves, Maria v. P. Rocha

Abstract:

Galactosidases are enzymes responsible for catalyzing lactose hydrolysis reactions and also favoring transgalactosylation reactions for the production of prebiotics, among which lactulose stands out. These enzymes, when immobilized, can have some enzymatic characteristics substantially improved, and the coating of supports with multifunctional polymers in immobilization processes is a promising alternative in order to extend the useful life of the biocatalysts, for example, the coating with polyethyleneimine (PEI). PEI is a flexible polymer that suits the structure of the enzyme, giving greater stability, especially for multimeric enzymes such as β-galactosidases and also protects it from environmental variations, for example, pH and temperature. In addition, it can substantially improve the immobilization parameters and also the efficiency of enzymatic reactions. In this context, the aim of the present work was first to develop biocatalysts of β-galactosidase from Kluyveromyces lactis immobilized on PEI coated agarose, determining the immobilization parameters, its operational and thermal stability, and then to apply it in the hydrolysis of lactose and synthesis of lactulose, using whey as a substrate. This immobilization strategy was chosen in order to improve the catalytic efficiency of the enzyme in the transgalactosylation reaction for the production of prebiotics, and there are few studies with β-galactosidase from this strain. The immobilization of β-galactosidase in agarose previously functionalized with 48% (w/v) glycidol and then coated with 10% (w/v) PEI solution was evaluated using an enzymatic load of 10 mg/g of protein. Subsequently, the hydrolysis and transgalactosylation reactions were conducted at 50 °C, 120 RPM for 20 minutes, using whey (66.7 g/L of lactose) supplemented with 133.3 g/L fructose at a ratio of 1:2 (lactose/fructose). Operational stability studies were performed in the same conditions for 10 cycles. Thermal stabilities of biocatalysts were conducted at 50 ºC in 50 mM phosphate buffer, pH 6.6, with 0.1 mM MnCl2. The biocatalysts whose supports were coated were named AGA_GLY_PEI_GAL, and those that were not coated were named AGA_GLY_GAL. The coating of the support with PEI considerably improved immobilization yield (2.6-fold), the biocatalyst activity (1.4-fold), and efficiency (2.2-fold). The biocatalyst AGA_GLY_PEI_GAL was better than AGA_GLY_GAL in hydrolysis and transgalactosylation reactions, converting 88.92% of lactose at 5 min of reaction and obtaining a residual concentration of 5.24 g/L. Besides that, it was produced 13.90 g/L lactulose in the same time interval. AGA_GLY_PEI_GAL biocatalyst was stable during the 10 cycles evaluated, converting approximately 80% of lactose and producing 10.95 g/L of lactulose even after the tenth cycle. However, the thermal stability of AGA_GLY_GAL biocatalyst was superior, with a half-life time 5 times higher, probably because the enzyme was immobilized by covalent bonding, which is stronger than adsorption (AGA_GLY_PEI_GAL). Therefore, the strategy of coating the supports with PEI has proven to be effective for the immobilization of β-galactosidase from K. lactis, considerably improving the immobilization parameters, as well as the enzyme, catalyzed reactions. In addition, the use of whey as a raw material for lactulose production has proved to be an industrially advantageous alternative.

Keywords: β-galactosidase, immobilization, lactulose, polyethylenimine, whey

Procedia PDF Downloads 113
6357 An Artificial Intelligence Framework to Forecast Air Quality

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 115
6356 Effect of Permeability on Glass Fiber Reinforced Plastic Laminate Produced by Vacuum Assisted Resin Transfer Molding Process

Authors: Nagri Sateesh, Kundavarapu Vengalrao, Kopparthi Phaneendra Kumar

Abstract:

Vacuum assisted resin transfer molding (VARTM) is one of the manufacturing technique that is viable for production of fiber reinforced polymer composite components suitable for aerospace, marine and commercial applications. However, the repeatable quality of the product can be achieved by critically fixing the process parameters such as Vacuum Pressure (VP) and permeability of the preform. The present investigation is aimed at studying the effect of permeability for production of Glass Fiber Reinforced Plastic (GFRP) components with consistent quality. The VARTM mould is made with an acrylic transparent top cover to observe and record the resin flow pattern. Six layers of randomly placed glass fiber under five different vacuum pressures VP1 = 0.013, VP2 = 0.026, VP3 = 0.039, VP4 = 0.053 and VP5 = 0.066 MPa were studied. The laminates produced by this process under the above mentioned conditions were characterized with ASTM D procedures so as to study the effect of these process parameters on the quality of the laminate. Moreover, as mentioned there is a considerable effect of permeability on the impact strength and the void content in the laminates under different vacuum pressures. SEM analysis of the impact tested fractured GFRP composites showed the bonding of fiber and matrix.

Keywords: permeability, vacuum assisted resin transfer molding (VARTM), ASTM D standards, SEM

Procedia PDF Downloads 151
6355 Improved Food Security and Alleviation of Cyanide Intoxication through Commercialization and Utilization of Cassava Starch by Tanzania Industries

Authors: Mariam Mtunguja, Henry Laswai, Yasinta Muzanilla, Joseph Ndunguru

Abstract:

Starchy tuberous roots of cassava provide food for people but also find application in various industries. Recently there has been the focus of concentrated research efforts to fully exploit its potential as a sustainable multipurpose crop. High starch yield is the important trait for commercial cassava production for the starch industries. Furthermore, cyanide present in cassava root poses a health challenge in the use of cassava for food. Farming communities where cassava is a staple food, prefer bitter (high cyanogenic) varieties as protection from predators and thieves. As a result, food insecure farmers prefer growing bitter cassava. This has led to cyanide intoxication to this farming communities. Cassava farmers can benefit from marketing cassava to starch producers thereby improving their income and food security. This will decrease dependency on cassava as staple food as a result of increased income and be able to afford other food sources. To achieve this, adequate information is required on the right cassava cultivars and appropriate harvesting period so as to maximize cassava production and profitability. This study aimed at identifying suitable cassava cultivars and optimum time of harvest to maximize starch production. Six commonly grown cultivars were identified and planted in a complete random block design and further analysis was done to assess variation in physicochemical characteristics, starch yield and cyanogenic potentials across three environments. The analysis showed that there is a difference in physicochemical characteristics between landraces (p ≤ 0.05), and can be targeted to different industrial applications. Among landraces, dry matter (30-39%), amylose (11-19%), starch (74-80%) and reducing sugars content (1-3%) varied when expressed on a dry weight basis (p ≤ 0.05); however, only one of the six genotypes differed in crystallinity and mean starch granule particle size, while glucan chain distribution and granule morphology were the same. In contrast, the starch functionality features measured: swelling power, solubility, syneresis, and digestibility differed (p ≤ 0.05). This was supported by Partial least square discriminant analysis (PLS-DA), which highlighted the divergence among the cassavas based on starch functionality, permitting suggestions for the targeted uses of these starches in diverse industries. The study also illustrated genotypic difference in starch yield and cyanogenic potential. Among landraces, Kiroba showed potential for maximum starch yield (12.8 t ha-1) followed by Msenene (12.3 t ha-1) and third was Kilusungu (10.2 t ha-1). The cyanide content of cassava landraces was between 15 and 800 ppm across all trial sites. GGE biplot analysis further confirmed that Kiroba was a superior cultivar in terms of starch yield. Kilusungu had the highest cyanide content and average starch yield, therefore it can also be suitable for use in starch production.

Keywords: cyanogen, cassava starch, food security, starch yield

Procedia PDF Downloads 215
6354 Hydrological-Economic Modeling of Two Hydrographic Basins of the Coast of Peru

Authors: Julio Jesus Salazar, Manuel Andres Jesus De Lama

Abstract:

There are very few models that serve to analyze the use of water in the socio-economic process. On the supply side, the joint use of groundwater has been considered in addition to the simple limits on the availability of surface water. In addition, we have worked on waterlogging and the effects on water quality (mainly salinity). In this paper, a 'complex' water economy is examined; one in which demands grow differentially not only within but also between sectors, and one in which there are limited opportunities to increase consumptive use. In particular, high-value growth, the growth of the production of irrigated crops of high value within the basins of the case study, together with the rapidly growing urban areas, provides a rich context to examine the general problem of water management at the basin level. At the same time, the long-term aridity of nature has made the eco-environment in the basins located on the coast of Peru very vulnerable, and the exploitation and immediate use of water resources have further deteriorated the situation. The presented methodology is the optimization with embedded simulation. The wide basin simulation of flow and water balances and crop growth are embedded with the optimization of water allocation, reservoir operation, and irrigation scheduling. The modeling framework is developed from a network of river basins that includes multiple nodes of origin (reservoirs, aquifers, water courses, etc.) and multiple demand sites along the river, including places of consumptive use for agricultural, municipal and industrial, and uses of running water on the coast of Peru. The economic benefits associated with water use are evaluated for different demand management instruments, including water rights, based on the production and benefit functions of water use in the urban agricultural and industrial sectors. This work represents a new effort to analyze the use of water at the regional level and to evaluate the modernization of the integrated management of water resources and socio-economic territorial development in Peru. It will also allow the establishment of policies to improve the process of implementation of the integrated management and development of water resources. The input-output analysis is essential to present a theory about the production process, which is based on a particular type of production function. Also, this work presents the Computable General Equilibrium (CGE) version of the economic model for water resource policy analysis, which was specifically designed for analyzing large-scale water management. As to the platform for CGE simulation, GEMPACK, a flexible system for solving CGE models, is used for formulating and solving CGE model through the percentage-change approach. GEMPACK automates the process of translating the model specification into a model solution program.

Keywords: water economy, simulation, modeling, integration

Procedia PDF Downloads 145
6353 Impact Assessment of Phosphogypsum on the Groundwater of Sfax-Agareb Aquifer, in Southeast of Tunisia

Authors: Samira Melki, Moncef Gueddari

Abstract:

In Tunisia, solid wastes storage continue to be uncontrolled. It is eliminated by land raising without any protection measurement against water table and soil contamination. Several industries are located in Sfax area, especially those of the Tunisian Chemical Group (TCG) for the enrichment and transformation of phosphate. The activity of the TCG focuses primarily on the production of chemical fertilizers and phosphoric acid, by transforming natural phosphates. This production generates gaseous emissions, liquid discharges and huge amounts of phosphogypsum (PG) stored directly on the soil surface. Groundwater samples were collected from Tunisian Chemical Group (TCG) site, to assess the effects of phosphogypsum leatchate on groundwater quality. The measurements of various physicochemical parameters including heavy metals (Al, Fe, Zn and F) and stable isotopes of the water molecule (¹⁸O, ²H) were determined in groundwater samples and are reported. The moderately high concentrations of SO₄⁼, Ortho-P, NH₄⁺ Al and F⁻ in groundwater particularly near to the phosphogypsum storage site, likely indicate that groundwater quality is being significantly affected by leachate percolation. The effect of distance of the piezometers from the pollution source was also investigated. The isotopic data of water molecule, showed that the waters of the Sfax-Agreb aquifer amount to recent-evaporation induced rainfall.

Keywords: phosphogypsum leatchate, groundwater quality, pollution, stable isotopes, Sfax-Agareb, Tunisia

Procedia PDF Downloads 188
6352 The Impact of Regulation on Corporate Social Responsibility Reporting Quality: UK Evidence

Authors: Ruba Hamed, Khaled Hussainey, Basiem Al-Shattarat, Wasim Al-Shattarat

Abstract:

This paper examines how the influence of mandating corporate social responsibility reporting (CSR) on subsequent financial performance through accounting-based measures and market-based measures. We provide evidence about the negative impact of reporting CSR voluntarily on the firm’s future performance due to the increased spending on and costs related to such activities. On the contrary, mandating CSR reporting enhances firms’ future performance by signalling to the market about the firm’s positive stance towards sustainability issues in the UK. Our findings are of interest to regulation setters and stakeholders with respect to mandatory CSR reporting and provide further insight and feedback into accounting and reporting practices.

Keywords: accounting-based performance, mandatory CSR, mandatory regulation, market-based performance

Procedia PDF Downloads 118
6351 Optimization of the Production Processes of Biodiesel from a Locally Sourced Gossypium herbaceum and Moringa oleifera

Authors: Ikechukwu Ejim

Abstract:

This research project addresses the optimization of biodiesel production from gossypium herbaceum (cottonseed) and moringa oleifera seeds. Soxhlet extractor method using n-hexane for gossypium herbaceum (cottonseed) and ethanol for moringa oleifera were used for solvent extraction. 1250 ml of oil was realized from both gossypium herbaceum (cottonseed) and moringa oleifera seeds before characterization. In transesterification process, a 4-factor-3-level experiment was conducted using an optimal design of Response Surface Methodology. The effects of methanol/oil molar ratio, catalyst concentration (%), temperature (°C) and time (mins), on the yield of methyl ester for both cottonseed and moringa oleifera oils were determined. The design consisted of 25 experimental runs (5 lack of fit points, five replicate points, 0 additional center points and I optimality) and provided sufficient information to fit a second-degree polynomial model. The experimental results suggested that optimum conditions were as follows; cottonseed yield (96.231%), catalyst concentration (0.972%), temperature (55oC), time (60mins) and methanol/oil molar ratios (8/1) respectively while moringa oleifera optimum values were yield (80.811%), catalyst concentration (1.0%), temperature (54.7oC), time (30mins ) and methanol/oil molar ratios (8/1) respectively. This optimized conditions were validated with the actual biodiesel yield in experimental trials and literature.

Keywords: optimization, Gossypium herbaceum, Moringa oleifera, biodiesel

Procedia PDF Downloads 137
6350 COVID-19 Pandemic and Disruptions in Nigeria’s Domestic Economic Activities: A Pre-post Empirical Investigation

Authors: Amaefule, Leonard Ifeanyi

Abstract:

The study evaluated the disruptions in Nigeria’s domestic economic activities occasioned by the COVID-19 pandemic: a pre and post-pandemic investigation approach. Domestic economic activities were measured with composite manufacturing purchasing managers index (PMI) and composite non-manufacturing PMI. Production and employment levels indices were proxies for composite manufacturing PMI, while business activities and employment level indices were proxies for non-manufacturing PMI. Data for these indices were sourced from monthly and quarterly publications of the Central Bank of Nigeria for periods covering fifteen (15) months before and 15 months after the outbreak of the virus in Nigeria. Test of equality of means was employed in establishing the significance of the difference of means between the pre and post-pandemic domestic economic activities. Results from the analysis indicated that a significant negative difference exists in each of the measures of domestic economic activities between the pre and post-pandemic periods. These findings, therefore, offer empirical evidence that the COVID-19 pandemic has disrupted domestic economic activities in Nigeria; thus, it exerts a negative influence on the measures of the nation’s domestic economic activities. The study thus recommended (among other things) that the Nigerian government should focus on policies that would enhance domestic production, employment and enhance business activities.

Keywords: COVID-19, domestic economic activities, composite manufacturing indices, composite non-manufacturing indices

Procedia PDF Downloads 167
6349 Horse Race Model of Communication

Authors: Ariyaratna Athugala

Abstract:

Mass media play a significant role in democratic societies. The Political Economy of the Mass Media postulates that elite media interlock with other institutional sectors in ownership, and editorial management effectively circumscribing their ability to remain analytically detached from other dominant institutional sectors. The production of meaning in news discourse is not valued neutral, but part of a larger process of presenting a hegemonic understanding of the world to audiences as the “production of consent.” The horse race model argues that “the raw material of news” pressures six bands that ultimately shape the news audiences receive. The six bands are as follows: Crown piece (raw material), brow band (professionalism), throat latch (gatekeeper), a bit (construction), nose band (perception), and reins (ownership). dThe horse race model suggests that media ultimately serve to “manufacture consent” for a range of self-serving elite opinion options. These bands determine what events are deemed newsworthy, how they are covered, where they are placed within the media and how much coverage they receive. Highly descriptive in nature, the horse race model of communication is concerned with the question of whether media can be seen to play a hegemonic role in the society oriented towards legitimization, hegemonic pressures and ideological construction.

Keywords: hegemonic pressures, horse race, ideological construction, six bands

Procedia PDF Downloads 243
6348 Weight Comparison of Oil and Dry Type Distribution Transformers

Authors: Murat Toren, Mehmet Çelebi

Abstract:

Reducing the weight of transformers while providing good performance, cost reduction and increased efficiency is important. Weight is one of the most significant factors in all electrical machines, and as such, many transformer design parameters are related to weight calculations. This study presents a comparison of the weight of oil type transformers and dry type transformer weight. Oil type transformers are mainly used in industry; however, dry type transformers are becoming more widespread in recent years. MATLAB is typically used for designing transformers and design parameters (rated voltages, core loss, etc.) along with design in ANSYS Maxwell. Similar to other studies, this study presented that the dry type transformer option is limited. Moreover, the commonly-used 50 kVA distribution transformers in the industry are oil type and dry type transformers are designed and considered in terms of weight. Currently, the preference for low-cost oil-type transformers would change if costs for dry-type transformer were more competitive. The aim of this study was to compare the weight of transformers, which is a substantial cost factor, and to provide an evaluation about increasing the use of dry type transformers.

Keywords: weight, optimization, oil-type transformers, dry-type transformers

Procedia PDF Downloads 344
6347 Causal Relationship between Macro-Economic Indicators and Fund Unit Price Behaviour: Evidence from Malaysian Equity Unit Trust Fund Industry

Authors: Anwar Hasan Abdullah Othman, Ahamed Kameel, Hasanuddeen Abdul Aziz

Abstract:

In this study, an attempt has been made to investigate the relationship specifically the causal relation between fund unit prices of Islamic equity unit trust fund which measure by fund NAV and the selected macro-economic variables of Malaysian economy by using VECM causality test and Granger causality test. Monthly data has been used from Jan, 2006 to Dec, 2012 for all the variables. The findings of the study showed that industrial production index, political election and financial crisis are the only variables having unidirectional causal relationship with fund unit price. However, the global oil prices is having bidirectional causality with fund NAV. Thus, it is concluded that the equity unit trust fund industry in Malaysia is an inefficient market with respect to the industrial production index, global oil prices, political election and financial crisis. However, the market is approaching towards informational efficiency at least with respect to four macroeconomic variables, treasury bill rate, money supply, foreign exchange rate and corruption index.

Keywords: fund unit price, unit trust industry, Malaysia, macroeconomic variables, causality

Procedia PDF Downloads 464
6346 Microwave and Ultrasound Assisted Extraction of Pectin from Mandarin and Lemon Peel: Comparisons between Sources and Methods

Authors: Pınar Karbuz, A. Seyhun Kıpcak, Mehmet B. Piskin, Emek Derun, Nurcan Tugrul

Abstract:

Pectin is a complex colloidal polysaccharide, found on the cell walls of all young plants such as fruit and vegetables. It acts as a thickening, stabilizing and gelling agent in foods. Pectin was extracted from mandarin and lemon peels using ultrasound and microwave assisted extraction methods to compare with these two different sources and methods of pectin production. In this work, the effect of microwave power (360, 600 W) and irradiation time (1, 2, 3 min) on the yield of extracted pectin from mandarin and lemon peels for microwave assisted extraction (MAE) were investigated. For ultrasound assisted extraction (UAE), parameters were determined as temperature (60, 75 °C) and sonication time (15, 30, 45 min) and hydrochloric acid (HCl) was used as an extracting agent for both extraction methods. The highest yields of extracted pectin from lemon peels were found to be 8.16 % (w/w) for 75 °C, 45 min by UAE and 8.58 % (w/w) for 360 W, 1 min by MAE. Additionally, the highest yields of extracted pectin from mandarin peels were found to be 11.29 % (w/w) for 75 °C, 45 min by UAE and 16.44 % (w/w) for 600 W, 1 min by MAE. The results showed that the use of microwave assisted extraction promoted a better yield when compared to the two extraction methods. On the other hand, according to the results of experiments, mandarin peels contain more pectin than lemon peels when the compared to the pectin product values of two sources. Therefore, these results suggested that MAE could be used as an efficient and rapid method for extraction of pectin and mandarin peels should be preferred as sources of pectin production compared to lemon peels.

Keywords: mandarin peel, lemon peel, pectin, ultrasound, microwave, extraction

Procedia PDF Downloads 231
6345 Genome Sequencing of the Yeast Saccharomyces cerevisiae Strain 202-3

Authors: Yina A. Cifuentes Triana, Andrés M. Pinzón Velásco, Marío E. Velásquez Lozano

Abstract:

In this work the sequencing and genome characterization of a natural isolate of Saccharomyces cerevisiae yeast (strain 202-3), identified with potential for the production of second generation ethanol from sugarcane bagasse hydrolysates is presented. This strain was selected because its capability to consume xylose during the fermentation of sugarcane bagasse hydrolysates, taking into account that many strains of S. cerevisiae are incapable of processing this sugar. This advantage and other prominent positive aspects during fermentation profiles evaluated in bagasse hydrolysates made the strain 202-3 a candidate strain to improve the production of second-generation ethanol, which was proposed as a first step to study the strain at the genomic level. The molecular characterization was carried out by genome sequencing with the Illumina HiSeq 2000 platform paired end; the assembly was performed with different programs, finally choosing the assembler ABYSS with kmer 89. Gene prediction was developed with the approach of hidden Markov models with Augustus. The genes identified were scored based on similarity with public databases of nucleotide and protein. Records were organized from ontological functions at different hierarchical levels, which identified central metabolic functions and roles of the S. cerevisiae strain 202-3, highlighting the presence of four possible new proteins, two of them probably associated with the positive consumption of xylose.

Keywords: cellulosic ethanol, Saccharomyces cerevisiae, genome sequencing, xylose consumption

Procedia PDF Downloads 316
6344 Ties of China and the United States Regarding to the Shanghai Cooperation Organization on the Basis of Soft Power Theory

Authors: Shabnam Dadparvar, Laijin Shen

Abstract:

After a period of conflict between Russia and the West, new signs of confrontation between the United States and China are observed. China, as the most populous country in the world with a high rate of economic growth, neither stands the hegemonic power of the United States nor has the intention of direct confrontation with it. By raising the costs of the United States’ leadership at the international level, China seeks to find a better status without direct confrontation with the US. Meanwhile, the Shanghai Cooperation Organization (SCO), as a soft balancing strategy against the hegemony of the United States is used as a tool to reach this goal. The authors by using a descriptive-analytical method try to explain the policies of China and the United States on Shanghai Cooperation Organization as well as confrontation between these two countries within the framework of 'balance of soft power theory'.

Keywords: balance of soft power, Central Asia, Shanghai cooperation organization, terrorism

Procedia PDF Downloads 366
6343 Screening of High-Alcohol Producing Yeasts for Manufacturing Process of Whisky

Authors: Byeong-Uk Lim, Young-Ran Song, Sang-Ho Baik

Abstract:

This study aimed to develop yeast starters for scientific alcohol production and systematic quality control of whisky. A total of 389 yeast strains were isolated from traditional Korean fermentation starter (nuruk) and rice wine (makgeolli), and ten strains were finally selected for their high alcohol productivities, in which their alcohol productions were above 17.3% (v/v) during 10 days under two steps of glucose feeding condition (30% and then 15%, w/v). By 18s rDNA sequence analysis, all strains were identified as Saccharomyces cerevisiae (SC), and they can grow well under 50% (w/v) glucose and 10% (v/v) ethanol conditions. Furthermore, the capability of ten different SC strains to ferment rice wine for whisky was studied. Rice wine was fermented with only steamed rice, water, and two types of enzymes (glucoamylase and α-amylase) during 14 days at 25 °C, and then their oenological properties have been determined. As the results, the fermented rice wines indicated the final pH range of 4.24-4.38 and acidity range of 0.12-0.18. The highest ethanol production of 20.2% (v/v) was found in the fermentation with a SC-156 strain, whereas SC-92 (16.8%) and SC-119 (16.4%) showed significantly lowest ethanol productions. In addition, the residual sugar contents showed negative correlation with alcohol contents. Moreover, this study focused on nucleotide polymorphisms in the MSN2 and MSN4 genes to investigate the cause of the defective stress responses in yeast. Consequently, it was also confirmed that the deletion of the N termini of Msn4p from identified point mutations in SC-63, SC-95, SC-156, SC-158, and SC-160 strains.

Keywords: yeast, high-alcohol, whisky, rice wine

Procedia PDF Downloads 320
6342 Natural Language Processing; the Future of Clinical Record Management

Authors: Khaled M. Alhawiti

Abstract:

This paper investigates the future of medicine and the use of Natural language processing. The importance of having correct clinical information available online is remarkable; improving patient care at affordable costs could be achieved using automated applications to use the online clinical information. The major challenge towards the retrieval of such vital information is to have it appropriately coded. Majority of the online patient reports are not found to be coded and not accessible as its recorded in natural language text. The use of Natural Language processing provides a feasible solution by retrieving and organizing clinical information, available in text and transforming clinical data that is available for use. Systems used in NLP are rather complex to construct, as they entail considerable knowledge, however significant development has been made. Newly formed NLP systems have been tested and have established performance that is promising and considered as practical clinical applications.

Keywords: clinical information, information retrieval, natural language processing, automated applications

Procedia PDF Downloads 397
6341 Oakes Test and Proportionality Test: Balance between the Practical Costs of Limiting Rights and the Benefits Arising from the Law

Authors: Rafael Tedrus Bento

Abstract:

The analysis of proportionality as a test is raised as a basic foundation for the achievement of Fundamental Rights. We used legal dogmatics and empirical analysis to seek the expected results, from the reading of the RV Oakes trial by the Supreme Court of Canada. In cases involving freedom of expression, two tests are used to resolve disputes. The first examines whether, in fact, the case can be characterized as a violation of freedom of expression; the second assesses whether this violation can be justified by the reasonable limit clause. This test was defined in the RV Oakes trial by the Supreme Court of Canada, concluding with the Oakes Test, used worldwide as a proportionality test. Resulting is a proportionality between the effects of the limiting measure and the objective - the more serious the harmful effects of a measure, the more important the objective must be.

Keywords: Oakes, proportionality, fundamental rights, Supreme Court of Canada

Procedia PDF Downloads 142
6340 Performance Prediction Methodology of Slow Aging Assets

Authors: M. Ben Slimene, M.-S. Ouali

Abstract:

Asset management of urban infrastructures faces a multitude of challenges that need to be overcome to obtain a reliable measurement of performances. Predicting the performance of slowly aging systems is one of those challenges, which helps the asset manager to investigate specific failure modes and to undertake the appropriate maintenance and rehabilitation interventions to avoid catastrophic failures as well as to optimize the maintenance costs. This article presents a methodology for modeling the deterioration of slowly degrading assets based on an operating history. It consists of extracting degradation profiles by grouping together assets that exhibit similar degradation sequences using an unsupervised classification technique derived from artificial intelligence. The obtained clusters are used to build the performance prediction models. This methodology is applied to a sample of a stormwater drainage culvert dataset.

Keywords: artificial Intelligence, clustering, culvert, regression model, slow degradation

Procedia PDF Downloads 101
6339 Charcoal Production from Invasive Species: Suggested Shift for Increased Household Income and Forest Plant Diversity in Nepal

Authors: Kishor Prasad Bhatta, Suman Ghimire, Durga Prasad Joshi

Abstract:

Invasive Alien Species (IAS) are considered waste forest resources in Nepal. The rapid expansion of IAS is one of the nine main drivers of forest degradation, though the extent and distribution of this species are not well known. Further, the knowledge of the impact of IAS removal on forest plant diversity is hardly known, and the possibilities of income generation from them at the grass-root communities are rarely documented. Systematic sampling of 1% with nested circular plots of 500 square meters was performed in IAS removed and non-removed area, each of 30 hectares in Udayapur Community Forest User Group (CFUG), Chitwan, central Nepal to observe whether the removal of IAS contributed to an increase in plant diversity. In addition, ten entrepreneurs of Udaypur CFUG, involved in the charcoal production, briquette making and marketing were interviewed and interacted as well as their record keeping booklets were reviewed to understand if the charcoal production contributed to their income and employment. The average annual precipitation and temperature of the study area is 2100 mm and 34 degree Celsius respectively with Shorea robusta as main tree species and Eupatorium odoratum as dominant IAS. All the interviewed households were from the ̔below-poverty-line’ category as per Community Forestry Guidelines. A higher Shannon-Weiner plant diversity index at regeneration level was observed in IAS removed areas (2.43) than in control site (1.95). Furthermore, the number of tree seedlings and saplings in the IAS harvested blocks were significantly higher (p < 0.005) compared to the unharvested one. The sale of charcoal produced through the pyrolysis of IAS in ̔ Bio-energy kilns’ contributed for an average increased income of 30.95 % (Nepalese rupees 31,000) of the involved households. Despite above factors, some operational policy hurdles related to charcoal transport and taxation existed at field level. This study suggests that plant diversity could be increased through the removal of IAS, and considerable economic benefits could be achieved if charcoal is substantially produced and utilized.

Keywords: briquette, economic benefits, pyrolysis, regeneration

Procedia PDF Downloads 268