Search results for: demand estimate

Authors: Shourav Ahmed, M. Gulam Kibria, Kais Zaman

Abstract:

Control charts graphically verify variation in quality parameters. Attribute type control charts deal with quality parameters that can only hold two states, e.g., good or bad, yes or no, etc. At present, p-control chart is most commonly used to deal with attribute type data. In construction of p-control chart using binomial distribution, the value of proportion non-conforming must be known or estimated from limited sample information. As the probability distribution of fraction non-conforming (p) is considered in hyperbinomial distribution unlike a constant value in case of binomial distribution, it reduces the risk of false detection. In this study, a statistical control chart is proposed based on hyperbinomial distribution when prior estimate of proportion non-conforming is unavailable and is estimated from limited sample information. We developed the control limits of the proposed modified p-chart using the mean and variance of hyperbinomial distribution. The proposed modified p-chart can also utilize additional sample information when they are available. The study also validates the use of modified p-chart by comparing with the result obtained using cumulative distribution function of hyperbinomial distribution. The study clearly indicates that the use of hyperbinomial distribution in construction of p-control chart yields much accurate estimate of quality parameters than using binomial distribution.

Keywords: binomial distribution, control charts, cumulative distribution function, hyper binomial distribution

Procedia PDF Downloads 273

Authors: P. Brinks, O. Kornadt, R. Oly

Abstract:

This research focuses on the optimization of glazed surfaces and the assessment of possible solar gains in industrial buildings. Existing window rating methods for single windows were evaluated and a new method for a simple analysis of energy gains and losses by single windows was introduced. Furthermore extensive transient building simulations were carried out to appraise the performance of low cost polycarbonate multi-cell sheets in interaction with typical buildings for industrial applications. Mainly, energy-saving potential was determined by optimizing the orientation and area of such glazing systems in dependency on their thermal qualities. Moreover the impact on critical aspects such as summer overheating and daylight illumination was considered to ensure the user comfort and avoid additional energy demand for lighting or cooling. Hereby the simulated heating demand could be reduced by up to 1/3 compared to traditional architecture of industrial halls using mainly skylights.

Keywords: solar architecture, Passive Solar Building Design, glazing, Low-Energy Buildings, industrial buildings

Procedia PDF Downloads 231

Authors: Sylvain Amailland, Jean-Hugh Thomas, Charles Pézerat, Romuald Boucheron, Jean-Claude Pascal

Abstract:

The noise requirements for naval and research vessels have seen an increasing demand for quieter ships in order to fulfil current regulations and to reduce the effects on marine life. Hence, new methods dedicated to the characterization of propeller noise, which is the main source of noise in the far-field, are needed. The study of cavitating propellers in closed-section is interesting for analyzing hydrodynamic performance but could involve significant difficulties for hydroacoustic study, especially due to reverberation and boundary layer noise in the tunnel. The aim of this paper is to present a numerical methodology for the identification of hydroacoustic sources on marine propellers using hydrophone arrays in a large hydrodynamic tunnel. The main difficulties are linked to the reverberation of the tunnel and the boundary layer noise that strongly reduce the signal-to-noise ratio. In this paper it is proposed to estimate the reflection coefficients using an inverse method and some reference transfer functions measured in the tunnel. This approach allows to reduce the uncertainties of the propagation model used in the inverse problem. In order to reduce the boundary layer noise, a cleaning algorithm taking advantage of the low rank and sparse structure of the cross-spectrum matrices of the acoustic and the boundary layer noise is presented. This approach allows to recover the acoustic signal even well under the boundary layer noise. The improvement brought by this method is visible on acoustic maps resulting from beamforming and DAMAS algorithms.

Keywords: acoustic imaging, boundary layer noise denoising, inverse problems, model adaptation

Procedia PDF Downloads 327

Authors: Joseph Thomas Eghwerido, Julian I. Mbegbu

Abstract:

In modelling environment processes, we apply multidisciplinary knowledge to explain, explore and predict the Earth's response to natural human-induced environmental changes. Thus, the analysis of spatial-time ecological and environmental studies, the spatial parameters of interest are always heterogeneous. This often negates the assumption of stationarity. Hence, the dispersion of the transportation of atmospheric pollutants, landscape or topographic effect, weather patterns depends on a good estimate of spatial covariance. The generalized linear mixed model, although linear in the expected value parameters, its likelihood varies nonlinearly as a function of the covariance parameters. As a consequence, computing estimates for a linear mixed model requires the iterative solution of a system of simultaneous nonlinear equations. In other to predict the variables at unsampled locations, we need to know the estimate of the present sampled variables. The geostatistical methods for solving this spatial problem assume covariance stationarity (locally defined covariance) and uniform in space; which is not apparently valid because spatial processes often exhibit nonstationary covariance. Hence, they have globally defined covariance. We shall consider different existing methods of solutions of spatial covariance of a space-time processes at unsampled locations. This stationary covariance changes with locations for multiple time set with some asymptotic properties.

Keywords: parametric, nonstationary, Kernel, Kriging

Procedia PDF Downloads 249

Authors: Nursel Koyuncu, Nihal Ata Tutkun

Abstract:

Frailty model is a survival model that takes into account the unobserved heterogeneity for exploring the relationship between the survival of an individual and several covariates. In the recent years, proposed survival models become more complex and this feature causes convergence problems especially in large data sets. Therefore selection of sample from these big data sets is very important for estimation of parameters. In sampling literature, some authors have defined new sampling schemes to predict the parameters correctly. For this aim, we try to see the effect of sampling design in semi-parametric frailty model. We conducted a simulation study in R programme to estimate the parameters of semi-parametric frailty model for different sample sizes, censoring rates under classical simple random sampling and ranked set sampling schemes. In the simulation study, we used data set recording 17260 male Civil Servants aged 40–64 years with complete 10-year follow-up as population. Time to death from coronary heart disease is treated as a survival-time and age, systolic blood pressure are used as covariates. We select the 1000 samples from population using different sampling schemes and estimate the parameters. From the simulation study, we concluded that ranked set sampling design performs better than simple random sampling for each scenario.

Keywords: frailty model, ranked set sampling, efficiency, simple random sampling

Procedia PDF Downloads 206

Authors: Lien Fa Lin, Yung Ming Li, Hsin Chen Hsieh

Abstract:

The rise of smartphones brings new concept So-Lo-Mo (social-local-mobile) in mobile commerce area in recent years. However, current So-Lo-Mo services only focus on individual users but not a group of users, and the development of group commerce is not enough to satisfy the demand of real-time group buying and less to think about the social relationship between customers. In this research, we integrate mobile intelligence with group commerce and consider customers' preference, real-time context, and social influence as components in the mechanism. With the support of this mechanism, customers are able to gather near customers with the same potential purchase willingness through mobile devices when he/she wants to purchase products or services to have a real-time group-buying. By matching the demand and supply of mobile group-buying market, this research improves the business value of mobile commerce and group commerce further.

Keywords: group formation, group commerce, mobile commerce, So-Lo-Mo, social influence

Procedia PDF Downloads 409

Authors: Chelly Souhir, Harizi Chahida, Hachaichi Aicha, Aissaoui Sihem, Chahed Mohamed Kouni

Abstract:

Introduction: In Tunisia, few studies have attempted to describe the demand for primary care in a standardized and systematic way. The purpose of this study is to describe the main reasons for demand for care in primary health care, through a survey of the Ariana Governorate PHC and to identify their evolutionary trend compared to last 30 years, reported by studies of the same type. Materials and methods: This is a cross-sectional descriptive study which concerns the study of consultants in the first line of the governorate of Ariana and their use of care recorded during 2 days in the same week during the month of May 2016, in each of these PHC. The same data collection sheet was used in all CSBs. The coding of the information was done according to the International Classification of Primary Care (ICPC). The data was entered and analyzed by the EPI Info 7 software. Results: Our study found that the most common ICPC chapters are respiratory (42%) and digestive (13.2%). In 1996 were the respiratory (43.5%) and circulatory (7.8%). In 2000, we found also the respiratory (39,6%) and circulatory (10,9%). In 2002, respiratory (43%) and digestive (10.1%) motives were the most frequent. According to the ICPC, the pathologies in our study were acute angina (19%), acute bronchitis and bronchiolitis (8%). In 1996, it was tonsillitis ( 21.6%) and acute bronchitis (7.2%). For Ben Abdelaziz in 2000, tonsillitis (14.5%) follow by acute bronchitis (8.3%). In 2002, acute angina (15.7%), acute bronchitis and bronchiolitis (11.2%) were the most common. Conclusion: Acute angina and tonsillitis are the most common in all studies conducted in Tunisia.

Keywords: acute angina, classification of primary care, primary health care, tonsillitis, Tunisia

Procedia PDF Downloads 520

Authors: Liu Yi-Hui, Chiu Fan-Yun, Lin Yu Fang, Jhang Yu Cih, He You Jing

Abstract:

The demand for care support has been rising with the aging of society and the advancement of medical science and technology. To meet rising demand, the Taiwanese government promoted the “Long Term Care Ten-Year Plan 2.0” in 2017. However, this policy and its related services failed to be fully implemented because of the ignorance of the public, and their lack of desire, fear, or discomfort in using them, which is a major obstacle to the promotion of long-term care services. Given the above context, this research objectives included the following: (1) to understand the current situation and predicament of family caregivers; (2) to reveal the actual use and assistance of government’s long-term care resources for family caregivers; and (3) to explore the support and impact of social capital on family caregivers. A semi-structured in-depth interview with five family caregivers to understand long-term care networks and social capital for family caregivers.

Keywords: family caregivers, long-term care, social capital

Procedia PDF Downloads 147

Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

Abstract:

Time history seismic analysis is supposed to be the most accurate method to predict the seismic demand of structures. On the other hand, the required computational time of this method toward achieving the result is its main deficiency. While being applied in optimization process, in which the structure must be analyzed thousands of time, reducing the required computational time of seismic analysis of structures makes the optimization algorithms more practical. Apparently, the invented approximate methods produce some amount of errors in comparison with exact time history analysis but the recently proposed method namely, Complete Quadratic Combination (CQC) and Sum Root of the Sum of Squares (SRSS) drastically reduces the computational time by combination of peak responses in each mode. In the present research, the Basic Modal Displacement (BMD) method is introduced and applied towards estimation of seismic demand of main structure. Seismic demand of sampled structure is estimated by calculation of modal displacement of basic structure (in which the modal displacement has been calculated). Shear steel sampled structures are selected as case studies. The error applying the introduced method is calculated by comparison of the estimated seismic demands with exact time history dynamic analysis. The efficiency of the proposed method is demonstrated by application of three types of earthquakes (in view of time of peak ground acceleration).

Keywords: time history dynamic analysis, basic modal displacement, earthquake-induced demands, shear steel structures

Procedia PDF Downloads 351

Authors: O. Abiodun Adeyinka, B. Adeyemo Adesesan

Abstract:

The forensic use of handwriting depends on the analysis, comparison, and evaluation decisions made by forensic document examiners. When using biometric technology in forensic applications, it is necessary to compute Likelihood Ratio (LR) for quantifying strength of evidence under two competing hypotheses, namely the prosecution and the defense hypotheses wherein a set of assumptions and methods for a given data set will be made. It is therefore important to know how repeatable and reproducible our estimated LR is. This paper evaluated the accuracy and reproducibility of examiners' decisions. Confidence interval for the estimated LR were presented so as not get an incorrect estimate that will be used to deliver wrong judgment in the court of Law. The estimate of LR is fundamentally a Bayesian concept and we used two LR estimators, namely Logistic Regression (LoR) and Kernel Density Estimator (KDE) for this paper. The repeatability evaluation was carried out by retesting the initial experiment after an interval of six months to observe whether examiners would repeat their decisions for the estimated LR. The experimental results, which are based on handwriting dataset, show that LR has different confidence intervals which therefore implies that LR cannot be estimated with the same certainty everywhere. Though the LoR performed better than the KDE when tested using the same dataset, the two LR estimators investigated showed a consistent region in which LR value can be estimated confidently. These two findings advance our understanding of LR when used in computing the strength of evidence in handwriting using forensics.

Keywords: confidence interval, handwriting, kernel density estimator, KDE, logistic regression LoR, repeatability, reproducibility

Procedia PDF Downloads 120

Authors: Ahmad Hashim, Zarizi Ab Rahman

Abstract:

Measurement of body composition via a field method has the most popular instruments which are used to estimate the percentage of body fat. Among the instruments used are the Body Mass Index, Bio Impedance Analysis and Skinfold Test. All three of these instruments do not involve high costs, do not require high technical skills, are mobile, save time, and are suitable for use in large populations. Because all three instruments can estimate the percentage of body fat, but it is important to identify the most appropriate instruments and have high reliability. Hence, this study was conducted to determine the reliability and convergent validity of the instruments. A total of 40 students, males and females aged between 13 and 14 years participated in this study. The study found that the test retest and Pearson correlation coefficient of reliability for the three instruments is very high, r = .99. While the inter class reliability also are at high level with r = .99 for Body Mass Index and Bio Impedance Analysis, r = .96 for Skin fold test. Intra class reliability coefficient for these three instruments is too high for Body Mass Index r = .99, Bio Impedance Analysis r = .97, and Skin fold Test r = .90. However, Standard Error of Measurement value for all three instruments indicates the Body Mass Index is the most appropriate instrument with a mean value of .000672 compared with other instruments. The findings show that the Body Mass Index is an instrument which is the most accurate and reliable in estimating body fat percentage for the population studied.

Keywords: reliability, validity, body mass index, bio impedance analysis and skinfold test

Procedia PDF Downloads 326

Authors: Amjad Ali Khan, Muhammad Ishaq Saqi, Kashif Ali

Abstract:

The focus of hydrocarbon exploration in Pakistan has been primarily on conventional hydrocarbon resources. Directorate General Petroleum Concessions (DGPC) has taken the lead on the assessment of indigenous unconventional oil and gas resources, which has resulted in a ‘Shale Oil/Gas Resource Assessment Study’ conducted with the help of USAID. This was critically required in the energy-starved Pakistan, where the gap between indigenous oil & gas production and demand continues to widen for a long time. Exploration & exploitation of indigenous unconventional resources of Pakistan have become vital to meet our energy demand and reduction of oil and gas import bill of the country. This study has attempted to bridge a critical gap in geological information about the potential of shale gas & oil in Pakistan in the four formations, i.e., Sembar, Lower Goru, Ranikot and Ghazij in the Middle and Lower Indus Basins, which were selected for the study as for resource assessment for shale gas & oil. The primary objective of the study was to estimate and establish shale oil/gas resource assessment of the study area by carrying out extensive geological analysis of exploration, appraisal and development wells drilled in the Middle and Lower Indus Basins, along with identification of fairway(s) and sweet spots in the study area. The Study covers the Lower parts of the Middle Indus basins located in Sindh, southern Punjab & eastern parts of the Baluchistan provinces, with a total sedimentary area of 271,795 km2. Initially, 1611 wells were reviewed, including 1324 wells drilled through different shale formations. Based on the availability of required technical data, a detailed petrophysical analysis of 124 wells (21 Confidential & 103 in the public domain) has been conducted for the shale gas/oil potential of the above-referred formations. The core & cuttings samples of 32 wells and 33 geochemical reports of prospective Shale Formations were available, which were analyzed to calibrate the results of petrophysical analysis with petrographic/ laboratory analyses to increase the credibility of the Shale Gas Resource assessment. This study has identified the most prospective intervals, mainly in Sembar and Lower Goru Formations, for shale gas/oil exploration in the Middle and Lower Indus Basins of Pakistan. The study recommends seven (07) sweet spots for undertaking pilot projects, which will enable to evaluate of the actual production capability and production sustainability of shale oil/gas reservoirs of Pakistan for formulating future strategies to explore and exploit shale/oil resources of Pakistan including fiscal incentives required for developing shale oil/gas resources of Pakistan. Some E&P Companies are being persuaded to make a consortium for undertaking pilot projects that have shown their willingness to participate in the pilot project at appropriate times. The location for undertaking the pilot project has been finalized as a result of a series of technical sessions by geoscientists of the potential consortium members after the review and evaluation of available studies.

Keywords: conventional resources, petrographic analysis, petrophysical analysis, unconventional resources, shale gas & oil, sweet spots

Procedia PDF Downloads 36

Authors: Gadisa Demie, Mesele Negash, Zerihun Asrat, Lojka Bohdan

Abstract:

Deforestation and forest degradation in the tropics have led to significant carbon (C) emissions. Agroforestry (AF) is a suitable land-use option for tackling such declines in ecosystem services, including climate change mitigation. However, it is unclear how biomass models, AF practices, and socio-ecological factors determine these roles, which hinders the implementation of climate change mitigation initiatives. This study aimed to estimate the ecosystem C stocks of the studied AF practices in relation to socio-ecological variables in central Ethiopia. Out of 243 AF farms inventoried, 108 were chosen at random from three AF practices to estimate their biomass and soil organic carbon. A total of 432 soil samples were collected from 0–30 and 30–60 cm soil depths; 216 samples were taken for each soil organic carbon fraction (%C) and bulk density computation. The study found that the currently developed allometric equations were the most accurate to estimate biomass C for trees growing in the landscape when compared to previous models. The study found higher overall biomass C in woodlots (165.62 Mg ha-¹) than in homegardens (134.07 Mg ha-¹) and parklands (19.98 Mg ha-¹). Conversely, overall, SOC was higher for homegardens (143.88 Mg ha-¹), but lower for parklands (53.42 Mg ha-¹). The ecosystem C stock was comparable between homegardens (277.95 Mg ha-¹) and woodlots (275.44 Mg ha-¹). The study found that elevation, wealthy levels, AF farm age, and size have a positive and significant (P < 0.05) effect on overall biomass and ecosystem C stocks but non-significant with slope (P > 0.05). Similarly, SOC increased with increasing elevation, AF farm age, and wealthy status but decreased with slope and non-significant with AF farm size. The study also showed that species diversity had a positive (P <0.05) effect on overall biomass C stocks in homegardens. The overall study highlights that AF practices have a great potential to lock up more carbon in biomass and soils; however, these potentials were determined by socioecological variables. Thus, these factors should be considered in management strategies that preserve trees in agricultural landscapes in order to mitigate climate change and support the livelihoods of farmers.

Keywords: agricultural landscape, biomass, climate change, soil organic carbon

Procedia PDF Downloads 45

Authors: Rajinder Singh, Ram Valluru

Abstract:

Chain Ladder (CL) method, Expected Loss Ratio (ELR) method and Bornhuetter-Ferguson (BF) method, in addition to more complex transition-rate modeling, are commonly used actuarial reserving methods in general insurance. There is limited published research about their relative performance in the context of Mortgage Insurance (MI). In our experience, these traditional techniques pose unique challenges and do not provide stable claim estimates for medium to longer term liabilities. The relative strengths and weaknesses among various alternative approaches revolve around: stability in the recent loss development pattern, sufficiency and reliability of loss development data, and agreement/disagreement between reported losses to date and ultimate loss estimate. CL method results in volatile reserve estimates, especially for accident periods with little development experience. The ELR method breaks down especially when ultimate loss ratios are not stable and predictable. While the BF method provides a good tradeoff between the loss development approach (CL) and ELR, the approach generates claim development and ultimate reserves that are disconnected from the ever-to-date (ETD) development experience for some accident years that have more development experience. Further, BF is based on subjective a priori assumption. The fundamental shortcoming of these methods is their inability to model exogenous factors, like the economy, which impact various cohorts at the same chronological time but at staggered points along their life-time development. This paper proposes an alternative approach of parametrizing the loss development curve and using logistic regression to generate the ultimate loss estimate for each homogeneous group (accident year or delinquency period). The methodology was tested on an actual MI claim development dataset where various cohorts followed a sigmoidal trend, but levels varied substantially depending upon the economic and operational conditions during the development period spanning over many years. The proposed approach provides the ability to indirectly incorporate such exogenous factors and produce more stable loss forecasts for reserving purposes as compared to the traditional CL and BF methods.

Keywords: actuarial loss reserving techniques, logistic regression, parametric function, volatility

Procedia PDF Downloads 123

Authors: T. Parhizkar, H. Jafarian, F. Aramoun, Y. Saboohi

Abstract:

Applying motorized shades have substantial effect on reducing energy consumption in building sector. Moreover, the combination of motorized shades with lighting systems and PV panels can lead to considerable reduction in the energy demand of buildings. In this paper, a model is developed to assess and find an optimum combination from shade designs, lighting control systems (dimming and on/off) and implementing PV panels in shades point of view. It is worth mentioning that annual saving for all designs is obtained during hourly simulation of lighting, solar heat flux and electricity generation with the use of PV panel. From 12 designs in general, three designs, two lighting control systems and PV panel option is implemented for a case study. The results illustrate that the optimum combination causes a saving potential of 792kW.hr per year.

Keywords: motorized shades, daylight, cooling load, shade control, hourly simulation

Procedia PDF Downloads 168

Authors: Mary Anne Roa

Abstract:

Congestion in network occurs due to exceed in aggregate demand as compared to the accessible capacity of the resources. Network congestion will increase as network speed increases and new effective congestion control methods are needed, especially for today’s very high speed networks. To address this undeniably global issue, the study focuses on the development of a fuzzy-based congestion control model concerned with allocating the resources of a computer network such that the system can operate at an adequate performance level when the demand exceeds or is near the capacity of the resources. Fuzzy logic based models have proven capable of accurately representing a wide variety of processes. The model built is based on bandwidth, the aggregate incoming traffic and the waiting time. The theoretical analysis and simulation results show that the proposed algorithm provides not only good utilization but also low packet loss.

Keywords: congestion control, queue management, computer networks, fuzzy logic

Procedia PDF Downloads 391

Authors: Bjørn Salskov, Nicolaj Bang, Charlotte Falko

Abstract:

Future labour markets demand employees that can carry out a non-linear task which is still not possible for computers. This means that employees must have well-developed soft-skills to perform at high levels in such a work environment. One of these soft-skills is presenting a message effectively. To be able to present a message effectively, one needs to practice this. To practice effectively, the trainee needs feedback on the current performance. Here VR environments can be used as a practice tool because it gives the trainee a sense of presence and reality. VR environments are becoming a cost-effective training method since it does not demand the presence of an expert to provide this feedback. The research article analysed in this study suggests that VR environment can be used and are able to provide the necessary feedback to the trainee which in turn will help the trainee become better at the task. The research analysed in this review does, however, show that there is a need for a study with larger sample size and a study which runs over a longer period.

Keywords: training, presentation, presentation skills, VR training, VR as a training tool, VR and presentation

Procedia PDF Downloads 117

Authors: S. Farid F. Mojtahedi, Ali Khosravi, Behnaz Naeimian, S. Adel A. Hosseini

Abstract:

Land subsidence is a gradual settling or sudden sinking of the land surface from changes that take place underground. There are different causes of land subsidence; most notably, ground-water overdraft and severe weather conditions. Subsidence of the land surface due to ground water overdraft is caused by an increase in the intergranular pressure in unconsolidated aquifers, which results in a loss of buoyancy of solid particles in the zone dewatered by the falling water table and accordingly compaction of the aquifer. On the other hand, exploitation of underground water may result in significant changes in degree of saturation of soil layers above the water table, increasing the effective stress in these layers, and considerable soil settlements. This study focuses on estimation of soil moisture at surface using different methods. Specifically, different methods for the estimation of moisture content at the soil surface, as an important term to solve Richard’s equation and estimate soil moisture profile are presented, and their results are discussed through comparison with field measurements obtained from Yanco1 station in south-eastern Australia. Surface soil moisture is not easy to measure at the spatial scale of a catchment. Due to the heterogeneity of soil type, land use, and topography, surface soil moisture may change considerably in space and time.

Keywords: artificial neural network, empirical method, remote sensing, surface soil moisture, unsaturated soil

Procedia PDF Downloads 356

Authors: Marriette Sakah, Christoph Kuhn, Samuel Gyamfi

Abstract:

Global electricity demand of households in 2005 is estimated to double by 2025 and nearly double again in 2030. The residential sector promises considerable demand growth through infrastructural and equipment investments, the majority of which is projected to occur in developing countries. This lays bare the urgency for enhanced efficiency in all energy systems combined with exploitation of local potential for renewable energy systems. This study explores options for reducing energy consumption, particularly in residential buildings and providing robust, decentralized and renewable energy supply for African cities. The potential of energy efficiency measures and the potential of harnessing local resources for renewable energy supply are quantitatively assessed. The scale of research specifically addresses the city level, which is regulated by local authorities. Local authorities can actively promote the transition to a renewable-based energy supply system by promoting energy efficiency and the use of alternative renewable fuels in existing buildings, and particularly in planning and development of new settlement areas through the use of incentives, regulations, and demonstration projects. They can also support a more sustainable development by shaping local land use and development patterns in such ways that reduce per capita energy consumption and are benign to the environment. The subject of the current case study, Tema, is Ghana´s main industrial hub, a port city and home to 77,000 families. Residential buildings in Tema consumed 112 GWh of electricity in 2013 or 1.45 MWh per household. If average household electricity demand were to decline at an annual rate of just 2 %, by 2035 Tema would consume only 134 GWh of electricity despite an expected increase in the number of households by 84 %. The work is based on a ground survey of the city’s residential sector. The results show that efficient technologies and decentralized renewable energy systems have great potential for meeting the rapidly growing energy demand of cities in developing countries.

Keywords: energy efficiency, energy saving potential, renewable energy integration, residential buildings, urban Africa

Procedia PDF Downloads 281

Authors: N. Brahmia

Abstract:

The growing needs of displacements led advanced countries in this field install new specific transport systems, able to palliate any deficiencies, especially when regular public transport does not adequately meet the requests of users. In this context, on-demand transport systems (ODT) are very efficient; they rely on techniques based on the location of trip generators which should be assured effectively with the use of operators responsible of the advance reservation, planning and organization, and studying the different ODT criteria. As the advanced countries in the field of transport, some developing countries are involved in the adaptation of the new technologies to reduce the deficit in their communication system. This communication presents the study of an ODT implementation in the west of Algeria, by developing the Geomatics side of the study. This part requires the use of specific systems such as Geographic Information System (GIS), Road Database Management System (RDBMS)… so we developed the process through an application in an environment of mobility by using the computer tools dedicated to the management of the entities related to the transport field.

Keywords: geomatics, GIS, ODT, transport systems

Procedia PDF Downloads 595

Authors: Tsion Tekalegn

Abstract:

In Ethiopia, improved potato varieties are essential for food security, but smallholders' adoption of improved technologies limits their productivity. For this study, data was collected based on a structured questionnaire randomly collected from the 329 sample farmers (158 adopters and 171 non-adopters). We estimate the adoption of improved variety and causal impact using Endogenous Switching Regression (ESR), and a propensity Score Matching (PSM) was used to test the treatment effect. This helps us estimate the effect of improved potato variety on smallholder farmer income by controlling for the role of the selection bias problem stemming from both observed and unobserved heterogeneity. According to the result, key determinants influencing adoption include livestock ownership, access to extension services, and farming experience, which positively affect the likelihood of adopting improved varieties. In contrast, access to irrigation negatively correlates with adoption, suggesting that farmers with reliable water sources perceive less need for improved varieties. The ESR model result confirmed that improved potato variety adoption increases the smallholder farmer income with an estimated gain of 8.77%. Thus, to improve the potato variety of the farming households, the government should give due emphasis to potato production, and the extension services need to be strengthened.

Keywords: adoption, improved potato varieties, endogenous switching regression, Ethiopia

Procedia PDF Downloads 17

Authors: Heewon Jeong, Seongpyo Kim, Joon Ha Kim

Abstract:

Over the last few tens of years, the coastal regions of Korea have experienced red tide algal blooms, which are harmful and toxic to both humans and marine organisms due to their potential threat. It was accelerated owing to eutrophication by human activities, certain oceanic processes, and climate change. Previous studies have tried to monitoring and predicting the algae concentration of the ocean with the bio-optical algorithms applied to color images of the satellite. However, the accurate estimation of algal blooms remains problems to challenges because of the complexity of coastal waters. Therefore, this study suggests a new method to identify the concentration of red tide algal bloom from images of geostationary ocean color imager (GOCI) which are representing the water environment of the sea in Korea. The method employed GOCI images, which took the water leaving radiances centered at 443nm, 490nm and 660nm respectively, as well as observed weather data (i.e., humidity, temperature and atmospheric pressure) for the database to apply optical characteristics of algae and train deep learning algorithm. Convolution neural network (CNN) was used to extract the significant features from the images. And then artificial neural network (ANN) was used to estimate the concentration of algae from the extracted features. For training of the deep learning model, backpropagation learning strategy is developed. The established methods were tested and compared with the performances of GOCI data processing system (GDPS), which is based on standard image processing algorithms and optical algorithms. The model had better performance to estimate algae concentration than the GDPS which is impossible to estimate greater than 5mg/m³. Thus, deep learning model trained successfully to assess algae concentration in spite of the complexity of water environment. Furthermore, the results of this system and methodology can be used to improve the performances of remote sensing. Acknowledgement: This work was supported by the 'Climate Technology Development and Application' research project (#K07731) through a grant provided by GIST in 2017.

Keywords: deep learning, algae concentration, remote sensing, satellite

Procedia PDF Downloads 181

Authors: Rafael Zhindon Almeida

Abstract:

Surface water quality is an important concern for the evaluation and prediction of water quality conditions. The objective of this study is to develop a statistical model that can accurately predict the water quality of the El Macho estuary in the city of Machala, El Oro province. The methodology employed in this study is of a basic type that involves a thorough search for theoretical foundations to improve the understanding of statistical modeling for water quality analysis. The research design is correlational, using a multivariate statistical model involving multiple linear regression and principal component analysis. The results indicate that water quality parameters such as fecal coliforms, biochemical oxygen demand, chemical oxygen demand, iron and dissolved oxygen exceed the allowable limits. The water of the El Macho estuary is determined to be below the required water quality criteria. The multiple linear regression model, based on chemical oxygen demand and total dissolved solids, explains 99.9% of the variance of the dependent variable. In addition, principal component analysis shows that the model has an explanatory power of 86.242%. The study successfully developed a statistical model to evaluate the water quality of the El Macho estuary. The estuary did not meet the water quality criteria, with several parameters exceeding the allowable limits. The multiple linear regression model and principal component analysis provide valuable information on the relationship between the various water quality parameters. The findings of the study emphasize the need for immediate action to improve the water quality of the El Macho estuary to ensure the preservation and protection of this valuable natural resource.

Keywords: statistical modeling, water quality, multiple linear regression, principal components, statistical models

Procedia PDF Downloads 85

Authors: Mohamed Ghorab

Abstract:

Local generated and distributed system for thermal and electrical energy is sighted in the near future to reduce transmission losses instead of the centralized system. Distributed Energy Resources (DER) is designed at different sizes (small and medium) and it is incorporated in energy distribution between the hubs. The energy generated from each technology at each hub should meet the local energy demands. Economic and environmental enhancement can be achieved when there are interaction and energy exchange between the hubs. Network energy system and CO₂ optimization between different six hubs presented Canadian community level are investigated in this study. Three different scenarios of technology systems are studied to meet both thermal and electrical demand loads for the six hubs. The conventional system is used as the first technology system and a reference case study. The conventional system includes boiler to provide the thermal energy, but the electrical energy is imported from the utility grid. The second technology system includes combined heat and power (CHP) system to meet the thermal demand loads and part of the electrical demand load. The third scenario has integration systems of CHP and Organic Rankine Cycle (ORC) where the thermal waste energy from the CHP system is used by ORC to generate electricity. General Algebraic Modeling System (GAMS) is used to model DER system optimization based on energy economics and CO₂ emission analyses. The results are compared with the conventional energy system. The results show that scenarios 2 and 3 provide an annual total cost saving of 21.3% and 32.3 %, respectively compared to the conventional system (scenario 1). Additionally, Scenario 3 (CHP & ORC systems) provides 32.5% saving in CO₂ emission compared to conventional system subsequent case 2 (CHP system) with a value of 9.3%.  

Keywords: distributed energy resources, network energy system, optimization, microgeneration system

Procedia PDF Downloads 187

Authors: S. S. Chong, A. R. Abdul Aziz, S. W. Harun, H. Arof

Abstract:

A miniaturized non-adiabatic silica microfiber is proposed for biological oxygen demand (BOD) ratio chemical oxygen demand (COD) sensing for the first time. BOD and COD are two main parameters to justify quality of wastewater. A ratio, BOD:COD can usually be established between the two analytical methods once COD and BOD value has been gathered. This ratio plays a vital role to determine appropriate strategy in wastewater treatment. A non-adiabatic microfiber sensor was formed by tapering the SMF to generate evanescent field where sensitive to perturbation of sensing medium. Because difference ratio BOD and COD contain in solution, this may induced changes of effective refractive index between microfiber and sensing medium. Attenuation wavelength shift to right with 0.5 nm and 3.5 nm while BOD:COD equal to 0.09 and 0.18 respectively. Significance difference wavelength shift may relate with the biodegradability of analyte. This proposed sensor is compact, reliable and feasible to determine the BOD:COD. Further research and investigation should be proceeded to enhance sensitivity and precision of the sensor for several of wastewater online monitoring.

Keywords: non-adiabatic fiber sensor, environmental sensing, biodegradability, evanescent field

Procedia PDF Downloads 652

Authors: Tasir Khan, Yejuan Wan, Kalim Ullah

Abstract:

Hydrological frequency analysis has been conducted to estimate the minimum flow elevation of the Indus River in Pakistan to protect the ecosystem. The Maximum likelihood estimation (MLE) technique is used to estimate the best-fitted distribution for Minimum Ecological Flows at nine stations of the Indus River in Pakistan. The four selected distributions, Generalized Extreme Value (GEV) distribution, Generalized Logistics (GLO) distribution, Generalized Pareto (GPA) distribution, and Pearson type 3 (PE3) are fitted in all sites, usually used in hydro frequency analysis. Compare the performance of these distributions by using the goodness of fit tests, such as the Kolmogorov Smirnov test, Anderson darling test, and chi-square test. The study concludes that the Maximum Likelihood Estimation (MLE) method recommended that GEV and GPA are the most suitable distributions which can be effectively applied to all the proposed sites. The quantiles are estimated for the return periods from 5 to 1000 years by using MLE, estimations methods. The MLE is the robust method for larger sample sizes. The results of these analyses can be used for water resources research, including water quality management, designing irrigation systems, determining downstream flow requirements for hydropower, and the impact of long-term drought on the country's aquatic system.

Keywords: minimum ecological flow, frequency distribution, indus river, maximum likelihood estimation

Procedia PDF Downloads 72

Authors: Daniel Llanes, Alfredo Reyes, Sonia E. Ruiz, Federico Valenzuela Beltran

Abstract:

Steel frames have been used in building construction for more than one hundred years. Beam-column may be connected to columns using either stiffened or unstiffened angles at the top and bottom beam flanges. Designers often assume that these assemblies acted as “pinned” connections for gravity loads and that the stiffened connections would act as “fixed” connections for lateral loads. Observation of damages sustained by buildings during the 1994 Northridge earthquake indicated that, contrary to the intended behavior, in many cases, brittle fractures initiated within the connections at very low levels of plastic demand, and in some cases, while the structures remained essentially elastic. Due to the damage presented in these buildings other type of alternative connections have been proposed. According to a research funded by the Federal Emergency Management Agency (FEMA), the screwed connections have better performance when they are subjected to cyclic loads, but at the same time, these connections have some degree of flexibility. Due to this situation, some researchers ventured into the study of semi-rigid connections. In the present study three steel buildings, constituted by regular frames are analyzed. Two types of connections are considered: pinned and semi-rigid connections. With the aim to estimate their structural capacity, a number of incremental dynamic analyzes are performed. 3D structural models are used for the analyses. The seismic ground motions were recorded on sites near Los Angeles, California, where the structures are supposed to be located. The vulnerability curves of the building are obtained in terms of maximum inter-story drifts. The vulnerability curves (which correspond to the models with two different types of connections) are compared, and its implications on its structural design and performance is discussed.

Keywords: steel frame Buildings, vulnerability curves, semi-rigid connections, pinned connections

Procedia PDF Downloads 221

Authors: Daniel Fundi Murithi

Abstract:

Missing data is a real bane in many surveys. To overcome the problems caused by missing data, partial deletion, and single imputation methods, among others, have been proposed. However, problems such as discarding usable data and inaccuracy in reproducing known population parameters and standard errors are associated with them. For regression and stochastic imputation, it is assumed that there is a variable with complete cases to be used as a predictor in estimating missing values in the other variable, and the relationship between the two variables is linear, which might not be realistic in practice. In this project, we estimate population total in presence of missing values in two-phase sampling. Instead of regression or stochastic models, non-parametric model based regression model is used in imputing missing values. Empirical study showed that nonparametric model-based regression imputation is better in reproducing variance of population total estimate obtained when there were no missing values compared to mean, median, regression, and stochastic imputation methods. Although regression and stochastic imputation were better than nonparametric model-based imputation in reproducing population total estimates obtained when there were no missing values in one of the sample sizes considered, nonparametric model-based imputation may be used when the relationship between outcome and predictor variables is not linear.

Keywords: finite population total, missing data, model-based imputation, two-phase sampling

Procedia PDF Downloads 124

Authors: Yuxiao Jiang, Lingjun Meng, Mengyu Zhan, Lichunyi Zhang, Yingxia Yun

Abstract:

On August 8th of 2015, a serious explosion occurred in Binhai New Area of Tianjin. This explosion led to the suspension of Tianjin-Binhai Light Rail Line 9 which was an important transportation mean connecting the old and new urban areas and the suspension causes inconvenience to commuters traveling from Tianjin to Binhai or Binhai to Tianjin and residents living by Line 9. On this regard, this paper intends to give suggestions on how to develop multi-mode transportation system rapidly and effectively after a disaster and tackle with the problems in terms of transportation infrastructure facilities. The paper proposes the idea of traffic resilience which refers to the city’s ability to restore its transportation system and reduce risks when the transportation system is destroyed by a disaster. By doing questionnaire research, on the spot study and collecting data from the internet, a GIS model is established so as to analyze the alternative traffic means used by different types of residents and study the transportation supply and demand. The result shows that along the Line 9, there is a larger demand for alternative traffic means in the place which is nearer to the downtown area. Also, the distribution of bus stations is more reasonable in the place nearer to downtown area, however, the traffic speed in the area is slower. Based on traffic resilience, the paper raises strategies to develop post-disaster multi-mode transportation system such as establishing traffic management mechanism timely and effectively, building multi-mode traffic networks, improving intelligent traffic systems and so on.

Keywords: traffic resilience, multi-mode transportation system, public traffic, transportation demand

Procedia PDF Downloads 339

Authors: Lali Khurtsia, Vano Tsertsvadze

Abstract:

Georgian drug policy is directed to reduce the supply of drugs. Retrospective analysis has shown that law enforcement activities have been followed by the expulsion of particular injecting drugs. The demand remains unchanged and drugs are substituted by the hand-made, even more dangerous homemade drugs entered the market. To find out expected new trends on the Georgian drug market, qualitative study was conducted with Georgian drug users to determine drug supply routes. It turned out that drug suppliers and consumers for safety reasons and to protect their anonymity, use Skype to make deals. IT in illegal drug trade is even more sophisticated in the worldwide. Trading with Bitcoins in the Darknet ensures high confidentiality of money transactions and the safe circulation of drugs. In 2014 largest Bitcoin mining enterprise in the world was built in Georgia. We argue that the use of Bitcoins and Darknet by Georgian drug consumers and suppliers will be an incentive to response adequately to the government's policy of restricting supply in order to satisfy market demand for drugs.

Keywords: bitcoin, darknet, drugs, policy

Procedia PDF Downloads 434