Search results for: quantitative precipitation forecast (QPF)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1017

Search results for: quantitative precipitation forecast (QPF)

957 Selective Sulfidation of Copper, Zinc and Nickelin Plating Wastewater using Calcium Sulfide

Authors: K. Soya, N. Mihara, D. Kuchar, M. Kubota, H. Matsuda, T. Fukuta

Abstract:

The present work is concerned with sulfidation of Cu, Zn and Ni containing plating wastewater with CaS. The sulfidation experiments were carried out at a room temperature by adding solid CaS to simulated metal solution containing either single-metal of Ni, Zn and Cu, or Ni-Zn-Cu mixture. At first, the experiments were conducted without pH adjustment and it was found that the complete sulfidation of Zn and Ni was achieved at an equimolar ratio of CaS to a particular metal. However, in the case of Cu, a complete copper sulfidation was achieved at CaS to Cu molar ratio of about 2. In the case of the selective sulfidation, a simulated plating solution containing Cu, Zn and Ni at the concentration of 100 mg/dm3 was treated with CaS under various pH conditions. As a result, selective precipitation of metal sulfides was achieved by a sulfidation treatment at different pH values. Further, the precipitation agents of NaOH, Na2S and CaS were compared in terms of the average specific filtration resistance and compressibility coefficients of metal sulfide slurry. Consequently, based on the lowest filtration parameters of the produced metal sulfides, it was concluded that CaS was the most effective precipitation agent for separation and recovery of Cu, Zn and Ni.

Keywords: Calcium sulfide, Plating Wastewater, Filtrationcharacteristics, Heavy metals, Sulfidation.

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956 Effect of Formulation Compositions on Particle Size and Zeta Potential of Diclofenac Sodium-Loaded Chitosan Nanoparticles

Authors: Rathapon Asasutjarit, Chayanid Sorrachaitawatwong, Nardauma Tipchuwong, Sirijit Pouthai

Abstract:

This study was conducted to formulate diclofenac sodium-loaded chitosan nanoparticles and to study the effect of formulation compositions on particle size and zeta potential of chitosan nanoparticles (CSN) containing diclofenac sodium (DC) prepared by ionotropic gelation method. It was found that the formulations containing chitosan, DC and tripolyphosphate (TPP) at a weight ratio of 4:1:1, respectively, with various pH provided various systems. At pH 5.0 and 6.0, the obtained systems were turbid because of precipitation of DC and chitosan, respectively. However, the dispersed system of CSN possessing diameter of 108±1 nm and zeta potential of 19±1 mV could be obtained at pH 5.5. These CSN also showed spherical morphology observed via a transmission scanning electron microscope. Change in weight ratio of chitosan:DC:TPP i.e. 1:1:1, 2:1:1, 3:1:1 and 4:1:1 showed that these ratios led to precipitation of particles except for the ratio of 4:1:1 providing CSN properly. The effect of Tween 80 as a stabilizer was also determined. It suggested that increment of Tween 80 concentration to 0.02% w/v could stabilize CSN at least 48 hours. However, increment of Tween 80 to 0.03% w/v led to quick precipitation of particles. The study of effect of TPP suggested that increment of TPP concentration increased particle size but decreased zeta potential. The excess TPP caused precipitation of CSN. Therefore, the optimized CSN was the CSN containing chitosan, DC and TPP at the ratio of 4:1:1and 0.02% w/v Tween 80 prepared at pH 5.5. Their particle size, zeta potential and entrapment efficiency were 128±1 nm, 15±1 mV and 45.8±2.6%, respectively.

Keywords: Chitosan nanoparticles, diclofenac sodium, size, zeta potential.

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955 Trend Analysis of Annual Total Precipitation Data in Konya

Authors: Naci Büyükkaracığan

Abstract:

Hydroclimatic observation values ​​are used in the planning of the project of water resources. Climate variables are the first of the values ​​used in planning projects. At the same time, the climate system is a complex and interactive system involving the atmosphere, land surfaces, snow and bubbles, the oceans and other water structures. The amount and distribution of precipitation, which is an important climate parameter, is a limiting environmental factor for dispersed living things. Trend analysis is applied to the detection of the presence of a pattern or trend in the data set. Many trends work in different parts of the world are usually made for the determination of climate change. The detection and attribution of past trends and variability in climatic variables is essential for explaining potential future alteration resulting from anthropogenic activities. Parametric and non-parametric tests are used for determining the trends in climatic variables. In this study, trend tests were applied to annual total precipitation data obtained in period of 1972 and 2012, in the Konya Basin. Non-parametric trend tests, (Sen’s T, Spearman’s Rho, Mann-Kendal, Sen’s T trend, Wald-Wolfowitz) and parametric test (mean square) were applied to annual total precipitations of 15 stations for trend analysis. The linear slopes (change per unit time) of trends are calculated by using a non-parametric estimator developed by Sen. The beginning of trends is determined by using the Mann-Kendall rank correlation test. In addition, homogeneities in precipitation trends are tested by using a method developed by Van Belle and Hughes. As a result of tests, negative linear slopes were found in annual total precipitations in Konya.

Keywords: Trend analysis, precipitation, hydroclimatology, Konya, Turkey.

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954 GMDH Modeling Based on Polynomial Spline Estimation and Its Applications

Authors: LI qiu-min, TIAN yi-xiang, ZHANG gao-xun

Abstract:

GMDH algorithm can well describe the internal structure of objects. In the process of modeling, automatic screening of model structure and variables ensure the convergence rate.This paper studied a new GMDH model based on polynomial spline  stimation. The polynomial spline function was used to instead of the transfer function of GMDH to characterize the relationship between the input variables and output variables. It has proved that the algorithm has the optimal convergence rate under some conditions. The empirical results show that the algorithm can well forecast Consumer Price Index (CPI).

Keywords: spline, GMDH, nonparametric, bias, forecast.

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953 The Investigation of Precipitation Conditions of Chevreul’s Salt

Authors: Turan Çalban, Fatih Sevim, Oral Laçin

Abstract:

In this study, the precipitation conditions of Chevreul’s salt were evaluated. The structure of Chevreul’s salt was examined by considering the previous studies. Thermodynamically, the most important precipitation parameters were pH, temperature, and sulphite-copper(II) ratio. The amount of Chevreul’s salt increased with increasing the temperature and sulphite-copper(II) ratio at the certain range, while it increased with decreasing the pH value at the chosen range. The best solution medium for recovery of Chevreul’s salt is sulphur dioxide gas-water system. Moreover, the soluble sulphite salts are used as efficient precipitating reagents. Chevreul’s salt is generally used to produce the highly pure copper powders from synthetic copper sulphate solutions and impure leach solutions. When the pH of the initial ammoniacal solution is greater than 8.5, ammonia in the medium is not free, and Chevreul’s salt from solution does not precipitate. In contrast, copper ammonium sulphide is precipitated. The pH of the initial solution containing ammonia for precipitating of Chevreul’s salt must be less than 8.5.

Keywords: Chevreul’s salt, copper sulphites, mixed-valence sulphite compounds, precipitating.

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952 Extraction of Bran Protein Using Enzymes and Polysaccharide Precipitation

Authors: Sudarat Jiamyangyuen, Tipawan Thongsook, Riantong Singanusong, Chanida Saengtubtim

Abstract:

Rice bran is normally used as a raw material for rice bran oil production or sold as feed with a low price. Conventionally, the protein in defatted rice bran was extracted using alkaline extraction and acid precipitation, which involves in chemical usage and lowering some nutritious component. This study was conducted in order to extract of rice bran protein concentrate (RBPC) from defatted rice bran using enzymes and employing polysaccharides in a precipitating step. The properties of RBPC obtained will be compared to those of a control sample extracted using a conventional method. The results showed that extraction of protein from rice bran using enzymes exhibited the higher protein recovery compared to that extraction with alkaline. The extraction conditions using alcalase 2% (v/w) at 50 C, pH 9.5 gave the highest protein (2.44%) and yield (32.09%) in extracted solution compared to other enzymes. Rice bran protein concentrate powder prepared by a precipitation step using alginate (protein in solution: alginate 1:0.016) exhibited the highest protein (27.55%) and yield (6.84%). Precipitation using alginate was better than that of acid. RBPC extracted with alkaline (ALK) or enzyme alcalase (ALC), then precipitated with alginate (AL) (samples RBP-ALK-AL and RBP-ALC-AL) yielded the precipitation rate of 75% and 91.30%, respectively. Therefore, protein precipitation using alginate was then selected. Amino acid profile of control sample, and sample precipitated with alginate, as compared to casein and soy protein isolated, showed that control sample showed the highest content among all sample. Functional property study of RBP showed that the highest nitrogen solubility occurred in pH 8-10. There was no statically significant between emulsion capacity and emulsion stability of control and sample precipitated by alginate. However, control sample showed a higher of foaming capacity and foaming stability compared to those of sample precipitated with alginate. The finding was successful in terms of minimizing chemicals used in extraction and precipitation steps in preparation of rice bran protein concentrate. This research involves in a production of value-added product in which the double amount of protein (28%) compared to original amount (14%) contained in rice bran could be beneficial in terms of adding to food products e.g. healthy drink with high protein and fiber. In addition, the basic knowledge of functional property of rice bran protein concentrate was obtained, which can be used to appropriately select the application of this value-added product from rice bran.

Keywords: Alginate, carrageenan, rice bran, rice bran protein.

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951 The Effect of Ageing on Impact Toughness and Microstructure of 2024 Al-Cu-Mg Alloy

Authors: Swami Naidu Gurugubelli

Abstract:

The present study aims at determining the effect of ageing on the impact toughness and microstructure of 2024 Al-Cu - Mg alloy. Following the 2 h solutionizing treatment at 450°C and water quench, the specimens were aged at 200°C for various periods (1 to 18 h). The precipitation stages during ageing were monitored by hardness measurements. For each specimen group, Charpy impact and hardness tests were carried out. During ageing the impact toughness of the alloy first increased, and then, following a maxima decreased due to the precipitation of intermediate phases, finally it reached its minimum at the peak hardness. Correlations between hardness and impact toughness were investigated.

Keywords: Ageing, alloy, hardness, microstructure.

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950 Application of Neural Networks in Financial Data Mining

Authors: Defu Zhang, Qingshan Jiang, Xin Li

Abstract:

This paper deals with the application of a well-known neural network technique, multilayer back-propagation (BP) neural network, in financial data mining. A modified neural network forecasting model is presented, and an intelligent mining system is developed. The system can forecast the buying and selling signs according to the prediction of future trends to stock market, and provide decision-making for stock investors. The simulation result of seven years to Shanghai Composite Index shows that the return achieved by this mining system is about three times as large as that achieved by the buy and hold strategy, so it is advantageous to apply neural networks to forecast financial time series, the different investors could benefit from it.

Keywords: Data mining, neural network, stock forecasting.

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949 The Application of Non-quantitative Modelling in the Analysis of a Network Warfare Environment

Authors: N. Veerasamy, JPH Eloff

Abstract:

Network warfare is an emerging concept that focuses on the network and computer based forms through which information is attacked and defended. Various computer and network security concepts thus play a role in network warfare. Due the intricacy of the various interacting components, a model to better understand the complexity in a network warfare environment would be beneficial. Non-quantitative modeling is a useful method to better characterize the field due to the rich ideas that can be generated based on the use of secular associations, chronological origins, linked concepts, categorizations and context specifications. This paper proposes the use of non-quantitative methods through a morphological analysis to better explore and define the influential conditions in a network warfare environment.

Keywords: Morphological, non-quantitative, network warfare.

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948 Analysis of Meteorological Drought Using Standardized Precipitation Index – A Case Study of Puruliya District, West Bengal, India

Authors: Moumita Palchaudhuri, Sujata Biswas

Abstract:

Drought is universally acknowledged as a phenomenon associated with scarcity of water. The Standardized Precipitation Index (SPI) expresses the actual rainfall as standardized departure from rainfall probability distribution function. In this study severity and spatial pattern of meteorological drought was analyzed in the Puruliya District, West Bengal, India using multi-temporal SPI. Daily gridded data for the period 1971-2005 from 4 rainfall stations surrounding the study area were collected from IMD, Pune, and used in the analysis. Geographic Information System (GIS) was used to generate drought severity maps for the different time scales and months of the year. Temporal SPI graphs show that the maximum SPI value (extreme drought) occurs in station 3 in the year 1993. Mild and moderate droughts occur in the central portion of the study area. Severe and extreme droughts were mostly found in the northeast, northwest and the southwest part of the region.

Keywords: Standardized Precipitation Index, Meteorological Drought, Geographical Information System, Drought severity.

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947 Quantitative Estimation of Periodicities in Lyari River Flow Routing

Authors: Rana Khalid Naeem, Asif Mansoor

Abstract:

The hydrologic time series data display periodic structure and periodic autoregressive process receives considerable attention in modeling of such series. In this communication long term record of monthly waste flow of Lyari river is utilized to quantify by using PAR modeling technique. The parameters of model are estimated by using Frances & Paap methodology. This study shows that periodic autoregressive model of order 2 is the most parsimonious model for assessing periodicity in waste flow of the river. A careful statistical analysis of residuals of PAR (2) model is used for establishing goodness of fit. The forecast by using proposed model confirms significance and effectiveness of the model.

Keywords: Diagnostic checks, Lyari river, Model selection, Monthly waste flow, Periodicity, Periodic autoregressive model.

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946 Optimization of the Co-Precipitation of Industrial Waste Metals in a Continuous Reactor System

Authors: Thomas S. Abia II, Citlali Garcia-Saucedo

Abstract:

A continuous copper precipitation treatment (CCPT) system was conceived at Intel Chandler Site to serve as a first-of-kind (FOK) facility-scale waste copper (Cu), nickel (Ni), and manganese (Mn) co-precipitation facility. The process was designed to treat highly variable wastewater discharged from a substrate packaging research factory. The paper discusses metals co-precipitation induced by internal changes for manufacturing facilities that lack the capacity for hardware expansion due to real estate restrictions, aggressive schedules, or budgetary constraints. Herein, operating parameters such as pH and oxidation reduction potential (ORP) were examined to analyze the ability of the CCPT System to immobilize various waste metals. Additionally, influential factors such as influent concentrations and retention times were investigated to quantify the environmental variability against system performance. A total of 2,027 samples were analyzed and statistically evaluated to measure the performance of CCPT that was internally retrofitted for Mn abatement to meet environmental regulations. In order to enhance the consistency of the influent, a separate holding tank was cannibalized from another system to collect and slow-feed the segregated Mn wastewater from the factory into CCPT. As a result, the baseline influent Mn decreased from 17.2+18.7 mg1L-1 at pre-pilot to 5.15+8.11 mg1L-1 post-pilot (70.1% reduction). Likewise, the pre-trial and post-trial average influent Cu values to CCPT were 52.0+54.6 mg1L-1 and 33.9+12.7 mg1L-1, respectively (34.8% reduction). However, the raw Ni content of 0.97+0.39 mg1L-1 at pre-pilot increased to 1.06+0.17 mg1L-1 at post-pilot. The average Mn output declined from 10.9+11.7 mg1L-1 at pre-pilot to 0.44+1.33 mg1L-1 at post-pilot (96.0% reduction) as a result of the pH and ORP operating setpoint changes. In similar fashion, the output Cu quality improved from 1.60+5.38 mg1L-1 to 0.55+1.02 mg1L-1 (65.6% reduction) while the Ni output sustained a 50% enhancement during the pilot study (0.22+0.19 mg1L-1 reduced to 0.11+0.06 mg1L-1). pH and ORP were shown to be significantly instrumental to the precipitative versatility of the CCPT System.

Keywords: Copper, co-precipitation, industrial wastewater treatment, manganese, optimization, pilot study.

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945 Enhancing Protein Incorporation in Calcium Phosphate Coating on Titanium by Rapid Biomimetic Co-Precipitation Technique

Authors: J. Suwanprateeb, F. Thammarakcharoen

Abstract:

Calcium phosphate coating (CaP) has been employed for protein delivery, but the typical direct protein adsorption on the coating led to low incorporation content and fast release of the protein from the coating. By using bovine serum albumin (BSA) as a model protein, rapid biomimetic co-precipitation between calcium phosphate and BSA was employed to control the distribution of BSA within calcium phosphate coating during biomimetic formation on titanium surface for only 6 h at 50oC in an accelerated calcium phosphate solution. As a result, the amount of BSA incorporation and release duration could be increased by using a rapid biomimetic coprecipitation technique. Up to 43 fold increases in the BSA incorporation content and the increase from 6 h to more than 360 h in release duration compared to typical direct adsorption technique were observed depending on the initial BSA concentration used during coprecipitation (1, 10 and 100 μg.ml-1). From x-ray diffraction and Fourier transform infrared spectroscopy studies, the coating composition was not altered with the incorporation of BSA by this rapid biomimetic co-precipitation and mainly comprised octacalcium phosphate and hydroxyapatite. However, the microstructure of calcium phosphate crystals changed from straight, plate-like units to curved, plate-like units with increasing BSA content.

Keywords: Biomimetic, Calcium Phosphate Coating, Protein, Titanium.

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944 Improving Co-integration Trading Rule Profitability with Forecasts from an Artificial Neural Network

Authors: Paul Lajbcygier, Seng Lee

Abstract:

Co-integration models the long-term, equilibrium relationship of two or more related financial variables. Even if cointegration is found, in the short run, there may be deviations from the long run equilibrium relationship. The aim of this work is to forecast these deviations using neural networks and create a trading strategy based on them. A case study is used: co-integration residuals from Australian Bank Bill futures are forecast and traded using various exogenous input variables combined with neural networks. The choice of the optimal exogenous input variables chosen for each neural network, undertaken in previous work [1], is validated by comparing the forecasts and corresponding profitability of each, using a trading strategy.

Keywords: Artificial neural networks, co-integration, forecasting, trading rule.

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943 Energy Performance of Buildings Due to Downscaled Seasonal Models

Authors: Anastasia K. Eleftheriadou, Athanasios Sfetsos, Nikolaos Gounaris

Abstract:

The current paper presents an extensive bottom-up framework for assessing building sector-specific vulnerability to climate change: energy supply and demand. The research focuses on the application of downscaled seasonal models for estimating energy performance of buildings in Greece. The ARW-WRF model has been set-up and suitably parameterized to produce downscaled climatological fields for Greece, forced by the output of the CFSv2 model. The outer domain, D01/Europe, included 345 x 345 cells of horizontal resolution 20 x 20 km2 and the inner domain, D02/Greece, comprised 180 x 180 cells of 5 x 5 km2 horizontal resolution. The model run has been setup for a period with a forecast horizon of 6 months, storing outputs on a six hourly basis.

Keywords: Urban environment, vulnerability, climate change, energy performance, seasonal forecast models.

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942 A Critical Approach to Modern Conception in the Context of Objectivity and Quantitative Method

Authors: Sergun Kurtoglu

Abstract:

The struggle between modern and postmodern understanding is also displayed in terms of the superiorities of quantitative and qualitative methods to each other which are evaluated within the scope of these understandings. By way of assuming that the quantitative researches (modern) are able to account for structure while the qualitative researches (postmodern) explain the process, these methods are turned into a means for worldviews specific to a period. In fact, process is not a functioning independent of structure. In addition to this issue, the ability of quantitative methods to provide scientific knowledge is also controversial so long as they exclude the dialectical method. For this reason, the critiques charged against modernism in terms of quantitative methods are, in a sense, legitimate. Nevertheless, the main issue is in which parameters postmodernist critique tries to legitimize its critiques and whether these parameters represent a point of view enabling democratic solutions. In this respect, the scientific knowledge covered in Turkish media as a means through which ordinary people have access to scientific knowledge will be evaluated by means of content analysis within a new objectivity conception.

Keywords: knowledge and objectivity, dialectic method, qualitative and quantitative methods, modernism/postmodernism.

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941 Study on Extraction of Niobium Oxide from Columbite–Tantalite Concentrate

Authors: Htet Htike Htwe, Kay Thi Lwin

Abstract:

The principal objective of this study is to be able to extract niobium oxide from columbite-tantalite concentrate of Thayet Kon Area in Nay Phi Taw. It is recovered from columbite-tantalite concentrate which contains 19.29 % Nb2O5.The recovery of niobium oxide from columbite-tantalite concentrate can be divided into three main sections, namely, digestion of the concentrate, recovery from the leached solution and precipitation and calcinations. The concentrate was digested with hydrofluoric acid and sulfuric acid. Of the various parameters that effect acidity and time were studied. In the recovery section solvent extraction process using methyl isobutyl ketone was investigated. Ammonium hydroxide was used as a precipitating agent and the precipitate was later calcined. The percentage of niobium oxide is 74%.

Keywords: Calcination, Digestion, Precipitation, SolventExtraction.

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940 Estimation of Reconnaissance Drought Index (RDI) for Bhavnagar District, Gujarat, India

Authors: Ravi Shah, V. L. Manekar, R. A. Christian, N. J. Mistry

Abstract:

There are two types of drought as conceptual drought and operational drought. The three parameters as the beginning, the end and the degree of severity of the drought can be identifying in operational drought by average precipitation in the whole region. One of the methods classified to measure drought is Reconnaissance Drought Index (RDI). Evapotranspiration is calculated using Penman-Monteith method by analyzing thirty nine years prolong climatic data. The evapotranspiration is then utilized in RDI to classify normalized and standardized RDI. These RDI classifications led to what kind of drought faced in Bhavnagar region on 12 month time scale basis. The comparison between actual drought conditions and RDI method used to find out drought are also illustrated. It can be concluded that the index results of drought in a particular year are same in both methods but having different index values where as severity remain same.

Keywords: Drought, Drought index, Reconnaissance Drought Index (RDI), Precipitation.

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939 Comparison of Artificial Neural Network Architectures in the Task of Tourism Time Series Forecast

Authors: João Paulo Teixeira, Paula Odete Fernandes

Abstract:

The authors have been developing several models based on artificial neural networks, linear regression models, Box- Jenkins methodology and ARIMA models to predict the time series of tourism. The time series consist in the “Monthly Number of Guest Nights in the Hotels" of one region. Several comparisons between the different type models have been experimented as well as the features used at the entrance of the models. The Artificial Neural Network (ANN) models have always had their performance at the top of the best models. Usually the feed-forward architecture was used due to their huge application and results. In this paper the author made a comparison between different architectures of the ANNs using simply the same input. Therefore, the traditional feed-forward architecture, the cascade forwards, a recurrent Elman architecture and a radial based architecture were discussed and compared based on the task of predicting the mentioned time series.

Keywords: Artificial Neural Network Architectures, time series forecast, tourism.

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938 Qualitative and Quantitative Case Study Research Method on Social Science: Accounting Perspective

Authors: Bubaker F. Shareia

Abstract:

The main aim of this paper is to set the parameters within which the study is to be conducted, specifically justifying the use of qualitative research, informed by theory. This paper argues that the social world is subjective in nature and may be accessed through the interpretive approach provided by the people involved in the context of the study. The paper defines and distinguishes between qualitative and quantitative research methodologies, explores Burrell and Morgan's framework for social research, and presents the study's adopted methodology and methods, with the rationale for these choices.

Keywords: Accounting, methodologies, qualitative, quantitative research.

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937 Study of Qualitative and Quantitative Metric for Pixel Factor Mapping and Extended Pixel Mapping Method

Authors: Indradip Banerjee, Souvik Bhattacharyya, Gautam Sanyal

Abstract:

In this paper, an approach is presented to investigate the performance of Pixel Factor Mapping (PFM) and Extended PMM (Pixel Mapping Method) through the qualitative and quantitative approach. These methods are tested against a number of well-known image similarity metrics and statistical distribution techniques. The PFM has been performed in spatial domain as well as frequency domain and the Extended PMM has also been performed in spatial domain through large set of images available in the internet.

Keywords: Qualitative, quantitative, PFM, EXTENDED PMM.

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936 A New Quantile Based Fuzzy Time Series Forecasting Model

Authors: Tahseen A. Jilani, Aqil S. Burney, C. Ardil

Abstract:

Time series models have been used to make predictions of academic enrollments, weather, road accident, casualties and stock prices, etc. Based on the concepts of quartile regression models, we have developed a simple time variant quantile based fuzzy time series forecasting method. The proposed method bases the forecast using prediction of future trend of the data. In place of actual quantiles of the data at each point, we have converted the statistical concept into fuzzy concept by using fuzzy quantiles using fuzzy membership function ensemble. We have given a fuzzy metric to use the trend forecast and calculate the future value. The proposed model is applied for TAIFEX forecasting. It is shown that proposed method work best as compared to other models when compared with respect to model complexity and forecasting accuracy.

Keywords: Quantile Regression, Fuzzy time series, fuzzy logicalrelationship groups, heuristic trend prediction.

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935 Removal of Iron from Groundwater by Sulfide Precipitation

Authors: H. Jusoh, N. Sapari, R.Z. Raja Azie

Abstract:

Iron in groundwater is one of the problems that render the water unsuitable for drinking. The concentration above 0.3 mg/L is common in groundwater. The conventional method of removal is by precipitation under oxic condition. In this study, iron removal under anaerobic conditions was examined by batch experiment as a main purpose. The process involved by purging of groundwater samples with H2S to form iron sulfide. Removal up to 83% for 1 mg/L iron solution was achieved. The removal efficiency dropped to 82% and 75% for the higher initial iron concentrations 3.55 and 5.01 mg/L, respectively. The average residual sulfide concentration in water after the process was 25*g/L. The Eh level during the process was -272 mV. The removal process was found to follow the first order reaction with average rate constant of 4.52 x 10-3. The half-life for the concentrations to reduce from initial values was 157 minutes.

Keywords: Anaerobic, chemical kinetics, hydrogen sulfide, iron, rate constant

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934 Modelling Hydrological Time Series Using Wakeby Distribution

Authors: Ilaria Lucrezia Amerise

Abstract:

The statistical modelling of precipitation data for a given portion of territory is fundamental for the monitoring of climatic conditions and for Hydrogeological Management Plans (HMP). This modelling is rendered particularly complex by the changes taking place in the frequency and intensity of precipitation, presumably to be attributed to the global climate change. This paper applies the Wakeby distribution (with 5 parameters) as a theoretical reference model. The number and the quality of the parameters indicate that this distribution may be the appropriate choice for the interpolations of the hydrological variables and, moreover, the Wakeby is particularly suitable for describing phenomena producing heavy tails. The proposed estimation methods for determining the value of the Wakeby parameters are the same as those used for density functions with heavy tails. The commonly used procedure is the classic method of moments weighed with probabilities (probability weighted moments, PWM) although this has often shown difficulty of convergence, or rather, convergence to a configuration of inappropriate parameters. In this paper, we analyze the problem of the likelihood estimation of a random variable expressed through its quantile function. The method of maximum likelihood, in this case, is more demanding than in the situations of more usual estimation. The reasons for this lie, in the sampling and asymptotic properties of the estimators of maximum likelihood which improve the estimates obtained with indications of their variability and, therefore, their accuracy and reliability. These features are highly appreciated in contexts where poor decisions, attributable to an inefficient or incomplete information base, can cause serious damages.

Keywords: Generalized extreme values (GEV), likelihood estimation, precipitation data, Wakeby distribution.

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933 Extreme Temperature Forecast in Mbonge, Cameroon through Return Level Analysis of the Generalized Extreme Value (GEV) Distribution

Authors: Nkongho Ayuketang Arreyndip, Ebobenow Joseph

Abstract:

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

Keywords: Return level, Generalized extreme value (GEV), Meteorology, Forecasting.

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932 Application of Artificial Neural Network to Forecast Actual Cost of a Project to Improve Earned Value Management System

Authors: Seyed Hossein Iranmanesh, Mansoureh Zarezadeh

Abstract:

This paper presents an application of Artificial Neural Network (ANN) to forecast actual cost of a project based on the earned value management system (EVMS). For this purpose, some projects randomly selected based on the standard data set , and it is produced necessary progress data such as actual cost ,actual percent complete , baseline cost and percent complete for five periods of project. Then an ANN with five inputs and five outputs and one hidden layer is trained to produce forecasted actual costs. The comparison between real and forecasted data show better performance based on the Mean Absolute Percentage Error (MAPE) criterion. This approach could be applicable to better forecasting the project cost and result in decreasing the risk of project cost overrun, and therefore it is beneficial for planning preventive actions.

Keywords: Earned Value Management System (EVMS), Artificial Neural Network (ANN), Estimate At Completion, Forecasting Methods, Project Performance Measurement.

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931 Forecast of the Small Wind Turbines Sales with Replacement Purchases and with or without Account of Price Changes

Authors: V. Churkin, M. Lopatin

Abstract:

The purpose of the paper is to estimate the US small wind turbines market potential and forecast the small wind turbines sales in the US. The forecasting method is based on the application of the Bass model and the generalized Bass model of innovations diffusion under replacement purchases. In the work an exponential distribution is used for modeling of replacement purchases. Only one parameter of such distribution is determined by average lifetime of small wind turbines. The identification of the model parameters is based on nonlinear regression analysis on the basis of the annual sales statistics which has been published by the American Wind Energy Association (AWEA) since 2001 up to 2012. The estimation of the US average market potential of small wind turbines (for adoption purchases) without account of price changes is 57080 (confidence interval from 49294 to 64866 at P = 0.95) under average lifetime of wind turbines 15 years, and 62402 (confidence interval from 54154 to 70648 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 90,7%, while in the second - 91,8%. The effect of the wind turbines price changes on their sales was estimated using generalized Bass model. This required a price forecast. To do this, the polynomial regression function, which is based on the Berkeley Lab statistics, was used. The estimation of the US average market potential of small wind turbines (for adoption purchases) in that case is 42542 (confidence interval from 32863 to 52221 at P = 0.95) under average lifetime of wind turbines 15 years, and 47426 (confidence interval from 36092 to 58760 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 95,3%, while in the second – 95,3%.

Keywords: Bass model, generalized Bass model, replacement purchases, sales forecasting of innovations, statistics of sales of small wind turbines in the United States.

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930 The Experience of Iranian Architecture in Direction of Urban Passages and Forming of Urban Structures to Increase Climatic Comfort

Authors: N. Utaberta, N. Sharifi, M. Surat, A. I. Che-Ani, N.M. Tawil

Abstract:

Iran has diverse climates and each have established distinct properties in their area. The extent and intensity of climatic factors effects on the lives of people living in various regions of Iran is so great that it cannot be simply ignored. In a large part of Iran known as the Central Plateau there is no precipitation for more than half of the year and dry weather and scarcity of fresh water pose an ever present problem for the people of these regions while in north of Iran upon the southern shores of the Caspian Sea the people face 80% humidity caused by the sea and 2 meters of annual precipitation. This article tries to review the past experiences of local architecture of Iran-s various regions so that they can be used to reshape and redirect the urban areas and structure of Iran-s current cities to provide environmental comfort by minimum use of fossil fuels.

Keywords: Urban Passage, Architecture in Iran, Urban Structure, Climatic Comfort

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929 Disaggregating and Forecasting the Total Energy Consumption of a Building: A Case Study of a High Cooling Demand Facility

Authors: Juliana Barcelos Cordeiro, Khashayar Mahani, Farbod Farzan, Mohsen A. Jafari

Abstract:

Energy disaggregation has been focused by many energy companies since energy efficiency can be achieved when the breakdown of energy consumption is known. Companies have been investing in technologies to come up with software and/or hardware solutions that can provide this type of information to the consumer. On the other hand, not all people can afford to have these technologies. Therefore, in this paper, we present a methodology for breaking down the aggregate consumption and identifying the highdemanding end-uses profiles. These energy profiles will be used to build the forecast model for optimal control purpose. A facility with high cooling load is used as an illustrative case study to demonstrate the results of proposed methodology. We apply a high level energy disaggregation through a pattern recognition approach in order to extract the consumption profile of its rooftop packaged units (RTUs) and present a forecast model for the energy consumption.  

Keywords: Energy consumption forecasting, energy efficiency, load disaggregation, pattern recognition approach.

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928 Investigating Climate Change Trend Based on Data Simulation and IPCC Scenario during 2010-2030 AD: Case Study of Fars Province

Authors: Leila Rashidian, Abbas Ebrahimi

Abstract:

The development of industrial activities, increase in fossil fuel consumption, vehicles, destruction of forests and grasslands, changes in land use, and population growth have caused to increase the amount of greenhouse gases especially CO2 in the atmosphere in recent decades. This has led to global warming and climate change. In the present paper, we have investigated the trend of climate change according to the data simulation during the time interval of 2010-2030 in the Fars province. In this research, the daily climatic parameters such as maximum and minimum temperature, precipitation and number of sunny hours during the 1977-2008 time interval for synoptic stations of Shiraz and Abadeh and during 1995-2008 for Lar stations and also the output of HADCM3 model in 2010-2030 time interval have been used based on the A2 propagation scenario. The results of the model show that the average temperature will increase by about 1 degree centigrade and the amount of precipitation will increase by 23.9% compared to the observational data. In conclusion, according to the temperature increase in this province, the amount of precipitation in the form of snow will be reduced and precipitations often will occur in the form of rain. This 1-degree centigrade increase during the season will reduce production by 6 to 10% because of shortening the growing period of wheat.

Keywords: Climate change, Lars.WG, HADCM3 model, Fars province, climatic parameters, A2 scenario.

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