Search results for: estimations of probability distributions

Authors: Marcin Szlachetka, Konrad Pietrykowski

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Modeling of a combustion process in a 9-cylinder aircraft engine is presented. The simulations of the combustion process in the IC engine have provided the information on the spatial and time distributions of selected quantities within the combustion chamber of the engine. The numerical analysis results have been compared with the results of indication process of the engine on the test stand. Modeling of combustion process an auto-ignited IC engine in the AVL Fire was carried out within the study. For the calculations, a ECFM-3Z model was used. Verification of simulation results was carried out by comparison of the pressure in the cylinder. The courses of indicated pressure, obtained from the simulations and during the engine tests mounted on a test stand were compared. The engine was braked by the propeller, which results in an adequate external power characteristics. The test object is a modified ASz-62IR engine with the injection system. The engine was running at take-off power. To check the optimum ignition timing regarding power, calculations, tests were performed for 7 different moments of ignition. The analyses of temperature distribution in the cylinder depending on the moments of ignition were carried out. Additional the course of pressure in the cylinder at different angles of ignition delays of the second spark plug were examined. The swirling of the mixture in the combustion chamber was also analysed. It has been shown that the largest vortexes occur in the middle of the chamber, and gets smaller, closer to the combustion chamber walls. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under Grant Agreement No. INNOLOT/I/1/NCBR/2013.

Keywords: CFD, combustion, internal combustion engine, aircraft engine

Procedia PDF Downloads 372

Authors: Sunmyeng Kim

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IEEE 802.11a/b/g standards provide multiple transmission rates, which can be changed dynamically according to the channel condition.Cooperative communications we reintroduced to improve the overallperformance of wireless LANs with the help of relay nodes with higher transmission rates. The cooperative communications are based on the fact that the transmission is much faster when sending data packets to a destination node through a relay node with higher transmission rate, rather than sending data directly to the destination node at low transmission rate. To apply the cooperative communications in wireless LAN, several MAC protocols have been proposed. Some of them can result in collisions among relay nodes in a dense network. In order to solve this problem, we propose a new protocol. Relay nodes are grouped based on their transmission rates. And then, relay nodes only in the highest group try to get channel access. Performance evaluation is conducted using simulation, and shows that the proposed protocol significantly outperforms the previous protocol in terms of throughput and collision probability.

Keywords: cooperative communications, MAC protocol, relay node, WLAN

Procedia PDF Downloads 466

Authors: Rafia Rafique, Arifa Khadim

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This research investigates the moderating role of job satisfaction between organizational learning and work performance among nurses. Correlation research design was used. Non-probability purposive sampling technique was utilized to recruit a sample of 110 nurses from public hospitals situated in the city of Lahore. The construct of organizational learning was measured using subscale of Integrated Scale for Measuring Organizational Learning. Job satisfaction was measured with the help of Job Satisfaction Survey. Performance of employees (task performance, contextual performance and counterproductive work behavior) was assessed by Individual Work Performance Questionnaire. Job satisfaction negatively moderates the relationship between organizational learning and counterproductive work behavior. Education has a significant positive relationship with organizational learning. Age, current hospital experience, marital satisfaction and salary of the nurses have positive relationship while number of children has significant negative relationship with counterproductive work behavior. These outcomes can be insightful in understanding the dynamics involved in work performance. Based on the result of this study relevant solutions can be proposed to improve the work performance of nurses.

Keywords: counterproductive work behavior, nurses, organizational learning, work performance

Procedia PDF Downloads 445

Authors: Hechmi Saidi, Noureddine Hamdi

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The performance of Decode and Forward (DF) multihop Free Space Optical ( FSO) scheme deploying Multiple Input Multiple Output (MIMO) configuration under Gamma-Gamma (GG) statistical distribution, that adopts M-ary Pulse Position Modulation (MPPM) coding, is investigated. We have extracted exact and estimated values of Symbol-Error Rates (SERs) respectively. A closed form formula related to the Probability Density Function (PDF) is expressed for our designed system. Thanks to the use of DF multihop MIMO FSO configuration and MPPM signaling, atmospheric turbulence is combatted; hence the transmitted signal quality is improved.

Keywords: free space optical, multiple input multiple output, M-ary pulse position modulation, multihop, decode and forward, symbol error rate, gamma-gamma channel

Procedia PDF Downloads 198

Authors: Sukritta Larsen, Kevin Wongleedee

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The purposes of this research were to study tourists’ destination loyalty from the perspective of international tourists in Bangkok and to study the level of interest to revisit Bangkok in the near future. A probability random sampling of 200 international tourists was utilized. Half of the sample group was male and the other half was female. A Likert-five-scale questionnaire was designed to collect the data and small in-depth interviews were also used to obtain their opinions. The findings revealed that the majority of respondents had a medium level of loyalty. When examined in detail, the destination loyalty indicators can be ranked according to the mean average from high to low as follows: to recommend the visit, to say positive things, to revisit in the next three years, to refer the information, and to plan to visit regularly. Finally, the findings from the in-depth interviews with small group of international tourists revealed that the major obstacles that prevented many international tourists who may interested in revisiting Thailand included traffic congestions, high crime rate, and political instability.

Keywords: destination loyalty, international tourists, revisit, Bangkok

Procedia PDF Downloads 338

Authors: Francesco Pandolfi, Georgios Baltzopoulos, Iunio Iervolino

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The impact of extreme winds on industrial assets and the built environment is gaining increasing attention from stakeholders, including the corporate insurance industry. This has led to a progressively more in-depth study of building vulnerability and fragility to wind. Wind vulnerability models are used in probabilistic risk assessment to relate a loss metric to an intensity measure of the natural event, usually a gust or a mean wind speed. In fact, vulnerability models can be integrated with the wind hazard, which consists of associating a probability to each intensity level in a time interval (e.g., by means of return periods) to provide an assessment of future losses due to extreme wind. This has also given impulse to the world- and regional-scale wind hazard studies.Another approach often adopted for the probabilistic description of building vulnerability to the wind is the use of fragility functions, which provide the conditional probability that selected building components will exceed certain damage states, given wind intensity. In fact, in wind engineering literature, it is more common to find structural system- or component-level fragility functions rather than wind vulnerability models for an entire building. Loss assessment based on component fragilities requires some logical combination rules that define the building’s damage state given the damage state of each component and the availability of a consequence model that provides the losses associated with each damage state. When risk calculations are based on numerical simulation of a structure’s behavior during extreme wind scenarios, the interaction of component fragilities is intertwined with the computational procedure. However, simulation-based approaches are usually computationally demanding and case-specific. In this context, the present work introduces the ExtReMe wind risk assESsment prototype Software, ERMESS, which is being developed at the University of Naples Federico II. ERMESS is a wind risk assessment tool for insurance applications to industrial facilities, collecting a wide assortment of available wind vulnerability models and fragility functions to facilitate their incorporation into risk calculations based on in-built or user-defined wind hazard data. This software implements an alternative method for building-specific risk assessment based on existing component-level fragility functions and on a number of simplifying assumptions for their interactions. The applicability of this alternative procedure is explored by means of an illustrative proof-of-concept example, which considers four main building components, namely: the roof covering, roof structure, envelope wall and envelope openings. The application shows that, despite the simplifying assumptions, the procedure can yield risk evaluations that are comparable to those obtained via more rigorous building-level simulation-based methods, at least in the considered example. The advantage of this approach is shown to lie in the fact that a database of building component fragility curves can be put to use for the development of new wind vulnerability models to cover building typologies not yet adequately covered by existing works and whose rigorous development is usually beyond the budget of portfolio-related industrial applications.

Keywords: component wind fragility, probabilistic risk assessment, vulnerability model, wind-induced losses

Procedia PDF Downloads 181

Authors: Daehyoung Kim, Pervez Khan, Hoon Kim

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Efficient utilization of spectrum resources is a fundamental issue of wireless communications due to its scarcity. To improve the efficiency of spectrum utilization, the spectrum sharing for unlicensed bands is being regarded as one of key technologies in the next generation wireless networks. A number of schemes such as Listen-Before-Talk(LBT) and carrier sensor adaptive transmission (CSAT) have been suggested from this aspect, but more efficient sharing schemes are required for improving spectrum utilization efficiency. This work considers an opportunistic transmission approach and a dynamic Contention Window (CW) adjustment scheme for LTE-U users sharing the unlicensed spectrum with Wi-Fi, in order to enhance the overall system throughput. The decision criteria for the dynamic adjustment of CW are based on the collision evaluation, derived from the collision probability of the system. The overall performance can be improved due to the adaptive adjustment of the CW. Simulation results show that our proposed scheme outperforms the Distributed Coordination Function (DCF) mechanism of IEEE 802.11 MAC.

Keywords: spectrum sharing, adaptive opportunistic transmission, unlicensed bands, heterogeneous networks

Procedia PDF Downloads 350

Authors: Mohamed Dakki, Genevieve Robin, Marie Suet, Abdeljebbar Qninba, Mohamed A. El Agbani, Asmâa Ouassou, Rhimou El Hamoumi, Hichem Azafzaf, Sami Rebah, Claudia Feltrup-Azafzaf, Nafouel Hamouda, Wed a.L. Ibrahim, Hosni H. Asran, Amr A. Elhady, Haitham Ibrahim, Khaled Etayeb, Essam Bouras, Almokhtar Saied, Ashrof Glidan, Bakar M. Habib, Mohamed S. Sayoud, Nadjiba Bendjedda, Laura Dami, Clemence Deschamps, Elie Gaget, Jean-Yves Mondain-Monval, Pierre Defos Du Rau

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In biodiversity monitoring, large datasets are becoming more and more widely available and are increasingly used globally to estimate species trends and con- servation status. These large-scale datasets challenge existing statistical analysis methods, many of which are not adapted to their size, incompleteness and heterogeneity. The development of scalable methods to impute missing data in incomplete large-scale monitoring datasets is crucial to balance sampling in time or space and thus better inform conservation policies. We developed a new method based on penalized Poisson models to impute and analyse incomplete monitoring data in a large-scale framework. The method al- lows parameterization of (a) space and time factors, (b) the main effects of predic- tor covariates, as well as (c) space–time interactions. It also benefits from robust statistical and computational capability in large-scale settings. The method was tested extensively on both simulated and real-life waterbird data, with the findings revealing that it outperforms six existing methods in terms of missing data imputation errors. Applying the method to 16 waterbird species, we estimated their long-term trends for the first time at the entire North African scale, a region where monitoring data suffer from many gaps in space and time series. This new approach opens promising perspectives to increase the accuracy of species-abundance trend estimations. We made it freely available in the r package ‘lori’ (https://CRAN.R-project.org/package=lori) and recommend its use for large- scale count data, particularly in citizen science monitoring programmes.

Keywords: biodiversity monitoring, high-dimensional statistics, incomplete count data, missing data imputation, waterbird trends in North-Africa

Procedia PDF Downloads 156

Authors: Kahlil Fredrick Cui, Marissa Pastor

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Earthquakes are complex phenomena, exhibiting complex correlations in space, time, and magnitude. Recently, the concept of complex networks has been used to shed light on the statistical and dynamical characteristics of regional seismicity. In this work, we study the relationships and interactions of seismic regions in Chile, Japan, and the Philippines through weighted and directed complex network analysis. Geographical areas are digitized into cells of fixed dimensions which in turn become the nodes of the network when an earthquake has occurred therein. Nodes are linked if a correlation exists between them as determined and measured by a correlation metric. The networks are found to be scale-free, exhibiting power-law behavior in the distributions of their different centrality measures: the in- and out-degree and the in- and out-strength. The evidence is also found of preferential interaction between seismically active regions through their degree-degree correlations suggesting that seismicity is dictated by the activity of a few active regions. The importance of a seismic region to the overall seismicity is measured using a generalized centrality metric taken to be an indicator of its activity or passivity. The spatial distribution of earthquake activity indicates the areas where strong earthquakes have occurred in the past while the passivity distribution points toward the likely locations an earthquake would occur whenever another one happens elsewhere. Finally, we propose a method that would project the location of the next possible earthquake using the generalized centralities coupled with correlations calculated between the latest earthquakes and a geographical point in the future.

Keywords: complex networks, correlations, earthquake, hazard assessment

Procedia PDF Downloads 212

Authors: Zsolt János Viharos, Krisztián Balázs Kis, Imre Paniti, Gábor Belső, Péter Németh, János Farkas

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The paper presents the results and industrial applications in the production setup period estimation based on industrial data inherited from the field of polymer cutting. The literature of polymer cutting is very limited considering the number of publications. The first polymer cutting machine is known since the second half of the 20th century; however, the production of polymer parts with this kind of technology is still a challenging research topic. The products of the applying industrial partner must met high technical requirements, as they are used in medical, measurement instrumentation and painting industry branches. Typically, 20% of these parts are new work, which means every five years almost the entire product portfolio is replaced in their low series manufacturing environment. Consequently, it requires a flexible production system, where the estimation of the frequent setup periods' lengths is one of the key success factors. In the investigation, several (input) parameters have been studied and grouped to create an adequate training information set for an artificial neural network as a base for the estimation of the individual setup periods. In the first group, product information is collected such as the product name and number of items. The second group contains material data like material type and colour. In the third group, surface quality and tolerance information are collected including the finest surface and tightest (or narrowest) tolerance. The fourth group contains the setup data like machine type and work shift. One source of these parameters is the Manufacturing Execution System (MES) but some data were also collected from Computer Aided Design (CAD) drawings. The number of the applied tools is one of the key factors on which the industrial partners’ estimations were based previously. The artificial neural network model was trained on several thousands of real industrial data. The mean estimation accuracy of the setup periods' lengths was improved by 30%, and in the same time the deviation of the prognosis was also improved by 50%. Furthermore, an investigation on the mentioned parameter groups considering the manufacturing order was also researched. The paper also highlights the manufacturing introduction experiences and further improvements of the proposed methods, both on the shop floor and on the quotation preparation fields. Every week more than 100 real industrial setup events are given and the related data are collected.

Keywords: artificial neural network, low series manufacturing, polymer cutting, setup period estimation

Procedia PDF Downloads 245

Authors: Nicole Merkle, Stefan Zander

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Ambient Assisted Living (AAL) describes a technological and methodological stack of (e.g. formal model-theoretic semantics, rule-based reasoning and machine learning), different aspects regarding the behavior, activities and characteristics of humans. Hence, a semantic representation of the user environment and its relevant elements are required in order to allow assistive agents to recognize situations and deduce appropriate actions. Furthermore, the user and his/her characteristics (e.g. physical, cognitive, preferences) need to be represented with a high degree of expressiveness in order to allow software agents a precise evaluation of the users’ context models. The correct interpretation of these context models highly depends on temporal, spatial circumstances as well as individual user preferences. In most AAL approaches, model representations of real world situations represent the current state of a universe of discourse at a given point in time by neglecting transitions between a set of states. However, the AAL domain currently lacks sufficient approaches that contemplate on the dynamic adaptions of context-related representations. Semantic representations of relevant real-world excerpts (e.g. user activities) help cognitive, rule-based agents to reason and make decisions in order to help users in appropriate tasks and situations. Furthermore, rules and reasoning on semantic models are not sufficient for handling uncertainty and fuzzy situations. A certain situation can require different (re-)actions in order to achieve the best results with respect to the user and his/her needs. But what is the best result? To answer this question, we need to consider that every smart agent requires to achieve an objective, but this objective is mostly defined by domain experts who can also fail in their estimation of what is desired by the user and what not. Hence, a smart agent has to be able to learn from context history data and estimate or predict what is most likely in certain contexts. Furthermore, different agents with contrary objectives can cause collisions as their actions influence the user’s context and constituting conditions in unintended or uncontrolled ways. We present an approach for dynamically updating a semantic model with respect to the current user context that allows flexibility of the software agents and enhances their conformance in order to improve the user experience. The presented approach adapts rules by learning sensor evidence and user actions using probabilistic reasoning approaches, based on given expert knowledge. The semantic domain model consists basically of device-, service- and user profile representations. In this paper, we present how this semantic domain model can be used in order to compute the probability of matching rules and actions. We apply this probability estimation to compare the current domain model representation with the computed one in order to adapt the formal semantic representation. Our approach aims at minimizing the likelihood of unintended interferences in order to eliminate conflicts and unpredictable side-effects by updating pre-defined expert knowledge according to the most probable context representation. This enables agents to adapt to dynamic changes in the environment which enhances the provision of adequate assistance and affects positively the user satisfaction.

Keywords: ambient intelligence, machine learning, semantic web, software agents

Procedia PDF Downloads 281

Authors: Chia-Chun Wu, Pei-Shan Lee

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Gender equality is an important issue in the workplace today. This study aimed to explore whether female naval with agreeableness personality traits can increase bystander attitudes towards sexual harassment by reducing sexism. A total of 281 female navalin Taiwan participated in this study and completed the BFI-10 scale and questionnaires on sexism and bystander attitudes towards sexual harassment. Path analysis was performed using AMOS 23 version. The results demonstrated that female naval with an agreeableness personality predicted bystander attitudes towards sexual harassment, and when sexism was reduced, it was more helpful to increase bystander attitudes toward sexual harassment. These results informed the perspectives of female naval. It is suggested that when promoting gender equality in the military in the future, people with agreeableness personality can be selected to attend gender equality courses to improve bystander attitudes towards sexual harassment. This provided the Navy with strategies to reduce the probability of sexual harassment.

Keywords: semism, agreeableness, female, bystander attitude

Procedia PDF Downloads 91

Authors: Akshat Kumar, Vidushi

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This paper identifies 27 KOIs, 26 of which are currently classified as candidates and one as false positives that have a high probability of being confirmed. For this purpose, 11 machine learning algorithms were implemented on the cumulative kepler dataset sourced from the NASA exoplanet archive; it was observed that the best-performing model was HistGradientBoosting and XGBoost with a test accuracy of 93.5%, and the lowest-performing model was Gaussian NB with a test accuracy of 54%, to test model performance F1, cross-validation score and RUC curve was calculated. Based on the learned models, the significant characteristics for confirm exoplanets were identified, putting emphasis on the object’s transit and stellar properties; these characteristics were namely koi_count, koi_prad, koi_period, koi_dor, koi_ror, and koi_smass, which were later considered to filter out the potential KOIs. The paper also calculates the Earth similarity index based on the planetary radius and equilibrium temperature for each KOI identified to aid in their classification.

Keywords: Kepler objects of interest, exoplanets, space exploration, machine learning, earth similarity index, transit photometry

Procedia PDF Downloads 75

Authors: Alok Madan, Arshad K. Hashmi

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Performance based design (PBD) is an iterative exercise in which a preliminary trial design of the building structure is selected and if the selected trial design of the building structure does not conform to the desired performance objective, the trial design is revised. In this context, development of a fundamental approach for performance based seismic design of masonry infilled frames with minimum number of trials is an important objective. The paper presents a plastic design procedure based on the energy balance concept for PBD of multi-story multi-bay masonry infilled reinforced concrete (R/C) frames subjected to near-field earthquakes. The proposed energy based plastic design procedure was implemented for trial performance based seismic design of representative masonry infilled reinforced concrete frames with various practically relevant distributions of masonry infill panels over the frame elevation. Non-linear dynamic analyses of the trial PBD of masonry infilled R/C frames was performed under the action of near-field earthquake ground motions. The results of non-linear dynamic analyses demonstrate that the proposed energy method is effective for performance based design of masonry infilled R/C frames under near-field as well as far-field earthquakes.

Keywords: masonry infilled frame, energy methods, near-fault ground motions, pushover analysis, nonlinear dynamic analysis, seismic demand

Procedia PDF Downloads 292

Authors: Mohammad H. Almomani

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In this paper, we argue the effect of the initial sample size, and the increment in simulation samples on the performance of a sequential approach that used in selecting the top m designs when the number of alternative designs is very large. The sequential approach consists of two stages. In the first stage the ordinal optimization is used to select a subset that overlaps with the set of actual best k% designs with high probability. Then in the second stage the optimal computing budget is used to select the top m designs from the selected subset. We apply the selection approach on a generic example under some parameter settings, with a different choice of initial sample size and the increment in simulation samples, to explore the impacts on the performance of this approach. The results show that the choice of initial sample size and the increment in simulation samples does affect the performance of a selection approach.

Keywords: Large Scale Problems, Optimal Computing Budget Allocation, ordinal optimization, simulation optimization

Procedia PDF Downloads 355

Authors: Chong Zhang, Guoming Tang, Bin Ge, Jiuyang Tang

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With the fast growing road traffic and increasingly severe traffic congestion, more and more citizens choose to use the public transportation for daily travelling. Meanwhile, the shared bike provides a convenient option for the first and last mile to the public transit. As of 2016, over one thousand cities around the world have deployed the bike-sharing system. The combination of these two transportations have stimulated the development of each other and made significant contribution to the reduction of carbon footprint. A lot of work has been done on mining the riding behaviors in various bike-sharing systems. Most of them, however, treated the bike-sharing system as an isolated system and thus their results provide little reference for the public transit construction and optimization. In this work, we treat the bike-sharing and public transit as a whole and investigate the customers’ bike-and-ride behaviors. Specifically, we develop a spatio-temporal traffic delivery model to study the riding patterns between the two transportation systems and explore the traffic characteristics (e.g., distributions of customer arrival/departure and traffic peak hours) from the time and space dimensions. During the model construction and evaluation, we make use of large open datasets from real-world bike-sharing systems (the CitiBike in New York, GoBike in San Francisco and BIXI in Montreal) along with corresponding public transit information. The developed two-dimension traffic model, as well as the mined bike-and-ride behaviors, can provide great help to the deployment of next-generation intelligent transportation systems.

Keywords: riding pattern mining, bike-sharing system, public transportation, bike-and-ride behavior

Procedia PDF Downloads 780

Authors: V. Makis, L. Jafari

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In this paper, we develop an optimal Bayesian chart to control the expected number of defects per inspection unit in production processes with long production runs. We formulate this control problem in the optimal stopping framework. The objective is to determine the optimal stopping rule minimizing the long-run expected average cost per unit time considering partial information obtained from the process sampling at regular epochs. We prove the optimality of the control limit policy, i.e., the process is stopped and the search for assignable causes is initiated when the posterior probability that the process is out of control exceeds a control limit. An algorithm in the semi-Markov decision process framework is developed to calculate the optimal control limit and the corresponding average cost. Numerical examples are presented to illustrate the developed optimal control chart and to compare it with the traditional u-chart.

Keywords: Bayesian u-chart, economic design, optimal stopping, semi-Markov decision process, statistical process control

Procedia PDF Downloads 573

Authors: M. Bahgat, H. A. Hanafy, S. Lakdawala

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Clustering phenomenon of pellets was observed frequently in shaft processes operating at higher temperatures. Clustering is a result of the growth of fibrous iron precipitates (iron whiskers) that become hooked to each other and finally become crystallized during the initial stages of metallization. If the pellet clustering is pronounced, sometimes leads to blocking inside the furnace and forced shutdown takes place. This work clarifies further the relation between metallic iron whisker growth and iron ore mineralogy. Various pellet sizes (6 – 12.0 & +12.0 mm) from three different ores (A, B & C) were (completely and partially) reduced at 985 ^oC with H₂/CO gas mixture using thermos-gravimetric technique. It was found that reducibility increases by decreasing the iron ore pellet’s size. Ore (A) has the highest reducibility than ore (B) and ore (C). Increasing the iron ore pellet’s size leads to increase the probability of metallic iron whisker formation. Ore (A) has the highest tendency for metallic iron whisker formation than ore (B) and ore (C). The reduction reactions for all iron ores A, B and C are mainly controlled by diffusion reaction mechanism.

Keywords: shaft furnace, cluster, metallic iron whisker, mineralogy, ferrous metallurgy

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Authors: Asad Naeem, Minsung Kim, Jinkoo Kim

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In this work, the effectiveness of damped cable systems (DCS) on the mitigation of earthquake-induced response of a framed structure is investigated. The seismic performance of DCS is investigated using fragility analysis and life cycle cost evaluation of an existing building retrofitted with DCS, and the results are compared with those of the structure retrofitted with viscous dampers. The comparison of the analysis results reveals that, due to the self-centering capability of the DCS, residual displacement becomes nearly zero in the structure retrofitted with the DCS. According to the fragility analysis, the structure retrofitted with the DCS has smaller probability of reaching a limit states compared to the structure with viscous dampers. It is also observed that both the initial and life cycle costs of the DCS method required for the seismic retrofit is smaller than those of the structure retrofitted with viscous dampers. Acknowledgment: This research was supported by a grant (17CTAP-C132889-01) from Technology Advancement Research Program (TARP) funded by Ministry of Land, Infrastructure, and Transport of Korean government.

Keywords: damped cable system, seismic retrofit, self centering, fragility analysis

Procedia PDF Downloads 453

Authors: O. D. Ohijeagbon, Oluseyi O. Ajayi, M. Ogbonnaya, Ahmeh Attabo

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This study analyzed the electricity generation potential from wind at seven sites spread across seven states of the North-Central region of Nigeria. Twenty-one years (1987 to 2007) wind speed data at a height of 10m were assessed from the Nigeria Meteorological Department, Oshodi. The data were subjected to different statistical tests and also compared with the two-parameter Weibull probability density function. The outcome shows that the monthly average wind speeds ranged between 2.2 m/s in November for Bida and 10.1 m/s in December for Jos. The yearly average ranged between 2.1m/s in 1987 for Bida and 11.8 m/s in 2002 for Jos. Also, the power density for each site was determined to range between 29.66 W/m2 for Bida and 864.96 W/m2 for Jos, Two parameters (k and c) of the Weibull distribution were found to range between 2.3 in Lokoja and 6.5 in Jos for k, while c ranged between 2.9 in Bida and 9.9m/s in Jos. These outcomes points to the fact that wind speeds at Jos, Minna, Ilorin, Makurdi and Abuja are compatible with the cut-in speeds of modern wind turbines and hence, may be economically feasible for wind-to-electricity at and above the height of 10 m. The study further assessed the potential and economic viability of standalone wind generation systems for off-grid rural communities located in each of the studied sites. A specific electric load profile was developed to suite hypothetic communities, each consisting of 200 homes, a school and a community health center. Assessment of the design that will optimally meet the daily load demand with a loss of load probability (LOLP) of 0.01 was performed, considering 2 stand-alone applications of wind and diesel. The diesel standalone system (DSS) was taken as the basis of comparison since the experimental locations have no connection to a distribution network. The HOMER® software optimizing tool was utilized to determine the optimal combination of system components that will yield the lowest life cycle cost. Sequel to the analysis for rural community utilization, a Distributed Generation (DG) analysis that considered the possibility of generating wind power in the MW range in order to take advantage of Nigeria’s tariff regime for embedded generation was carried out for each site. The DG design incorporated each community of 200 homes, freely catered for and offset from the excess electrical energy generated above the minimum requirement for sales to a nearby distribution grid. Wind DG systems were found suitable and viable in producing environmentally friendly energy in terms of life cycle cost and levelised value of producing energy at Jos ($0.14/kWh), Minna ($0.12/kWh), Ilorin ($0.09/kWh), Makurdi ($0.09/kWh), and Abuja ($0.04/kWh) at a particluar turbine hub height. These outputs reveal the value retrievable from the project after breakeven point as a function of energy consumed Based on the results, the study demonstrated that including renewable energy in the rural development plan will enhance fast upgrade of the rural communities.

Keywords: wind speed, wind power, distributed generation, cost per kilowatt-hour, clean energy, North-Central Nigeria

Procedia PDF Downloads 512

Authors: Cristina Galiana Carballo, Ibon Doval Martínez

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Urban boundaries often result in a controversial limit between countryside and city in Europe. This territory is normally defined by the very limited land uses and the abundance of open space. The dimension and dynamics of peri-urbanization in the last decades have increased this land stock, which has influenced/impacted in several factors in terms of economic costs (maintenance, transport), ecological disturbances of the territory and changes in inhabitant´s behaviour. In an increasingly urbanised world and a growing urban population, cities also face challenges such as Climate Change. In this context, new near-future corrective trends including circular economies for local food supply or decentralised waste management became key strategies towards more sustainable urban models. Those new solutions need to be planned and implemented considering the potential conflict with current land uses. The city of Vitoria-Gasteiz (Basque Country, Spain) has triplicated land consumption per habitant in 10 years, resulting in a vast extension of low-density urban type confronting rural land and threatening agricultural uses, landscape and urban sustainability. Urban planning allows managing and optimum use allocation based on soil vocation and socio-ecosystem needs, while peri-urban space arises as an opportunity for developing different uses which do not match either within the compact city, not in open agricultural lands, such as medium-size agrocomposting systems or biomass plants. Therefore, a qualitative multi-criteria methodology has been developed for Vitoria-Gasteiz city to assess the spatial definition of peri-urban land. Therefore, a qualitative multi-criteria methodology has been developed for Vitoria-Gasteiz city to assess the spatial definition of peri-urban land. Climate change and circular economy were identified as frameworks where to determine future land, soil vocation and urban planning requirements which eventually become estimations of required local food and renewable energy supply along with alternative waste management system´s implementation. By means of it, it has been developed an urban planning proposal which overcomes urban-non urban dichotomy in Vitoria-Gasteiz. The proposal aims to enhance rural system and improve urban sustainability performance through the normative recognition of an agricultural peri-urban belt.

Keywords: landscape ecology, land-use management, periurban, urban planning

Procedia PDF Downloads 163

Authors: Sayed Ahmed El Sayed, Osama M. Mesalhy, Mohamed A. Abdelatief

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A numerical study has been conducted to clarify fluid flow characteristics, pressure distributions, and skin friction coefficient over a wing-shaped tubes bundle in staggered arrangement with the placement of longitudinal fins (LF) at downstream position of the tube. The air-side Rea were at 1.8 x 103 to 9.7 x 103. The tubes bundle were employed with various fin height [hf] and fin thickness (δ) from (2 mm ≤ hf ≤ 12 mm) and (1.5 mm ≤ δ ≤ 3.5 mm) respectively at the considered Rea range. The flow pattern around the staggered wing-shaped tubes bundle was predicted using the commercial CFD FLUENT 6.3.26 software package. The distribution of average skin friction coefficient around wing-shaped tubes bundle is studied. Correlation of pressure drop coefficient Pdc and skin friction coefficient (Cf) in terms of Rea, design parameters for the studied cases were presented. Results indicated that the values of Pdc for hf = 6 mm are lower than these of NOF and hf = 2 mm by about 11 % and 13 % respectively for considered Rea range. Cf decreases as Rea increases. LFTH with hf = 6 mm offers lower form drag than that with hf = 12 mm and that of NOF. The lowest values of the pumping power are achieved for arrangements of hf = 6 mm for the considered Rea range. δ has negligible effect on skin friction coefficient, while has a slightly variation in ∆Pa. The wing-shaped tubes bundle heat exchanger with hf = 6 mm has the lowest values of ∆Pa, Pdc, Cf, and pumping power and hence the best performance comparing with the other bundles. Comparisons between the experimental and numerical results of the present study and those obtained by similar previous studies showed good agreements.

Keywords: longitudinal fins, skin friction, flow characteristics, FLUENT, wing-shaped tubes

Procedia PDF Downloads 539

Authors: Shima Soltanzadeh, Mohammad Hosain Fazel Zarandi, Mojtaba Barzegar Astanjin

Abstract:

Diagnosis of male infertility by the laboratory tests is expensive and, sometimes it is intolerable for patients. Filling out the questionnaire and then using classification method can be the first step in decision-making process, so only in the cases with a high probability of infertility we can use the laboratory tests. In this paper, we evaluated the performance of four classification methods including naive Bayesian, neural network, logistic regression and fuzzy c-means clustering as a classification, in the diagnosis of male infertility due to environmental factors. Since the data are unbalanced, the ROC curves are most suitable method for the comparison. In this paper, we also have selected the more important features using a filtering method and examined the impact of this feature reduction on the performance of each methods; generally, most of the methods had better performance after applying the filter. We have showed that using fuzzy c-means clustering as a classification has a good performance according to the ROC curves and its performance is comparable to other classification methods like logistic regression.

Keywords: classification, fuzzy c-means, logistic regression, Naive Bayesian, neural network, ROC curve

Procedia PDF Downloads 336

Authors: Tegan H. Emerson, Colin C. Olson, George Stantchev, Jason A. Edelberg, Michael Wilson

Abstract:

Detecting small targets at range is difficult because there is not enough spatial information present in an image sub-region containing the target to use correlation-based methods to differentiate it from dynamic confusers present in the scene. Moreover, this lack of spatial information also disqualifies the use of most state-of-the-art deep learning image-based classifiers. Here, we use characteristics of target tracks extracted from video sequences as data from which to derive distinguishing topological features that help robustly differentiate targets of interest from confusers. In particular, we calculate persistent homology from time-delayed embeddings of dynamic statistics calculated from motion tracks extracted from a wide field-of-view video stream. In short, we use topological methods to extract features related to target motion dynamics that are useful for classification and disambiguation and show that small targets can be detected at range with high probability.

Keywords: motion tracks, persistence images, time-delay embedding, topological data analysis

Procedia PDF Downloads 114

Authors: Ritika Jain, Rajnish Kumar

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The Department of Public Enterprises had made submissions of Self Evaluation Reports, for the purpose of corporate governance, mandatory for all central government owned enterprises. Despite this, an alarming 40% of the enterprises did not do so. This study examines the impact of external policy tools and internal firm-specific factors on corporate governance of central public sector enterprises (CPSEs). We use a dataset of all manufacturing and non-financial services owned by the central government of India for the year 2010-11. Using probit, ordered logit and Heckman’s sample selection models, the study finds that the probability and quality of corporate governance is positively influenced by the CPSE getting into a Memorandum of Understanding (MoU) with the central government of India, and hence, enjoying more autonomy in terms of day to day operations. Besides these, internal factors, including bigger size and lower debt size contribute significantly to better corporate governance.

Keywords: corporate governance, central public sector enterprises (CPSEs), sample selection, Memorandum of Understanding (MoU), ordered logit, disinvestment

Procedia PDF Downloads 257

Authors: Richard Nyanzi, Maupi E. Letsoalo, Jacobus N. Eloff, Piet J. Jooste

Abstract:

Candida albicans naturally occurs in the gastrointestinal tract (GIT) of more than 50% of humans. Overgrowth of the fungus causes several forms of candidiasis including oral thrush. Overgrowth tends to occur in immunocompromised humans such as diabetic, cancer and HIV patients. Antifungal treatment is available, but not without shortcomings. In this study, inhibitory activity of five probiotic Lactobacillus strains was demonstrated against the growth of seven clinical strains of Candida albicans by co-culturing of the organisms in a maize gruel (MG) medium. Phenotypic tests, molecular techniques and phylogenetic analysis have enabled precise identification of the organisms used in the study. The quantitative pour plate technique was used to enumerate colonies of the yeasts and the lactobacilli and the Kruskal-Wallis test and ANOVA tests were employed to compare the distributions of the colonies of the organisms. The cereal medium, containing added carbon sources, was inoculated with a Candida and a Lactobacillus strain in combination and incubated at 37 °C for 168 h. Aliquots were regularly taken and subjected to pH determination and colony enumeration. Certain Lactobacillus strains proved to be inhibitory and also lethal to some Candida albicans strains. A low pH due to Lactobacillus acid production resulted in significant low Candida colony counts. Higher Lactobacillus colony counts did not necessarily result in lower Candida counts suggesting that inhibitory factors besides low pH and competitive growth by lactobacilli contributed to the reduction in Candida counts. Such anti-Candida efficacy however needs to be confirmed by in vivo studies.

Keywords: candida albicans, oral thrush, candidiasis, lactobacillus, probiotics

Procedia PDF Downloads 399

Authors: Sana Dridi, Jalel Aouissi, Rafla Attia, Taoufik Hermassi, Thouraya Sahli

Abstract:

Soil erosion is an increasing issue in Mediterranean countries. In Tunisia, the capacity of dam reservoirs continues to decrease as a consequence of soil erosion. This study aims to predict sediment yield to enrich soil management practices using Soil and Water Assessment Tools model (SWAT) in the Siliana watershed (1041.6 km²), located in the northwest of Tunisia. A database was constructed using remote sensing and Geographical Information System. Climatic and flow data were collected from water resources directorates in Tunisia. The SWAT model was built to simulate hydrological processes and sediment transport. A sensitivity analysis, calibration, and validation were performed using SWAT-CUP software. The model calibration of stream flow simulations shows a good performance with NSE and R² values of 0.77 and 0.79, respectively. The model validation shows a very good performance with values of NSE and R² for 0.8 and 0.88, respectively. After calibration and validation of stream flow simulation, the model was used to simulate the soil erosion and sediment load transport. The spatial distributions of soil loss rate for determining the critical sediment source areas show that 63 % of the study area has a low soil loss rate less than 7 t ha⁻¹y⁻¹. The annual average soil loss rate simulated with the SWAT model in the Siliana watershed is 4.62 t ha⁻¹y⁻¹.

Keywords: water erosion, SWAT model, streamflow, SWATCUP, sediment yield

Procedia PDF Downloads 101

Authors: Farhad Aalizadeh, Ali Moosavi

Abstract:

This paper presents a two-dimensional Computational Fluid Dynamics (CFDs) simulation for the steady, particle tracking. The purpose of this paper is applied magnetic field effect on Magnetic Nanoparticles velocities distribution. It is shown that the permeability of the particles determines the effect of the magnetic field on the deposition of the particles and the deposition of the particles is inversely proportional to the Reynolds number. Using MHD and its property it is possible to control the flow velocity, remove the fouling on the walls and return the system to its original form. we consider a channel 2D geometry and solve for the resulting spatial distribution of particles. According to obtained results when only magnetic fields are applied perpendicular to the flow, local particles velocity is decreased due to the direct effect of the magnetic field return the system to its original fom. In the method first, in order to avoid mixing with blood, the ferromagnetic particles are covered with a gel-like chemical composition and are injected into the blood vessels. Then, a magnetic field source with a specified distance from the vessel is used and the particles are guided to the affected area. This paper presents a two-dimensional Computational Fluid Dynamics (CFDs) simulation for the steady, laminar flow of an incompressible magnetorheological (MR) fluid between two fixed parallel plates in the presence of a uniform magnetic field. The purpose of this study is to develop a numerical tool that is able to simulate MR fluids flow in valve mode and determineB0, applied magnetic field effect on flow velocities and pressure distributions.

Keywords: MHD, channel clots, magnetic nanoparticles, simulations

Procedia PDF Downloads 368

Authors: Van Chung Nguyen

Abstract:

The purpose of this study is to study the current status of the value chain for fish distribution at Quang Binh Fishing Port with 360 research samples in which the research subjects are fishermen, traders, retailers, and businesses. The research uses the approach of applying the value chain theoretical framework of Kaplinsky and Morris to quantify and describe market channels and actors participating in the value chain and analyze the value-added process of these companies according to market channels. The analysis results show that fishermen directly catch fish with high economic efficiency, but processing enterprises and, especially retailers, are the agents to obtain higher added value. Processing enterprises play a role that is not really clear due to outdated processing technology; in contrast, retailers have the highest added value. This shows that the added value of the fish supply chain at Quang Binh fishing port is still limited, leading to low output quality. Therefore, the selling price of fish to the market is still high compared to the abundant fish resources, leading to low consumption and limiting exports due to the quality of processing enterprises. This reduces demand and fishing capacity, and productivity is lower than potential. To improve the fish value chain at fishing ports, it is necessary to focus on improving product quality, strengthening linkages between actors, building brands and product consumption markets at the same time, improving the capacity of export processing enterprises.

Keywords: Quang Binh fishing port, value chain, market, distributions channel

Procedia PDF Downloads 73

Authors: Ahmed Alagha, Belkacem Lamri, Abdelhak Kada.

Abstract:

Steel-wood assemblies often have complex geometric configurations whose overall behavior under the effect of a fire is conditioned by the thermal response, by combining the two materials steel and wood, whose thermal characteristics are greatly influenced by high temperatures. The objective of this work is to study the thermal behavior of a steel-wood connection, with or without insulating material, subjected to an ISO834 standard fire model. The analysis is developed by the analytical approach using the Eurocode, and numerically, by the finite element method, through the ANSYS calculation code. The design of the connections is evaluated at room temperature taking the cases of single shear and double shear. The thermal behavior of the connections is simulated in transient state while taking into account the modes of heat transfer by convection and by radiation. The variation of temperature as a function of time is evaluated in different positions of the connections while talking about the heat produced and the formation of the carbon layer. The results relate to the temperature distributions in the connection elements as a function of the duration of the fire. The results of the thermal analysis show that the temperature increases rapidly and reaches more than 260 °C in the steel material for an hour of exposure to fire. The temperature development in wood material is different from that in steel because of its thermal properties. Wood heats up on the outside and burns, its surface can reach very high temperatures in points on the surface.

Keywords: Eurocode 5, finite elements, ISO834, simple shear, thermal behaviour, wood-steel connection

Procedia PDF Downloads 85