Search results for: network communities and weighted load balancing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9852

Search results for: network communities and weighted load balancing

8502 Constructing a Physics Guided Machine Learning Neural Network to Predict Tonal Noise Emitted by a Propeller

Authors: Arthur D. Wiedemann, Christopher Fuller, Kyle A. Pascioni

Abstract:

With the introduction of electric motors, small unmanned aerial vehicle designers have to consider trade-offs between acoustic noise and thrust generated. Currently, there are few low-computational tools available for predicting acoustic noise emitted by a propeller into the far-field. Artificial neural networks offer a highly non-linear and adaptive model for predicting isolated and interactive tonal noise. But neural networks require large data sets, exceeding practical considerations in modeling experimental results. A methodology known as physics guided machine learning has been applied in this study to reduce the required data set to train the network. After building and evaluating several neural networks, the best model is investigated to determine how the network successfully predicts the acoustic waveform. Lastly, a post-network transfer function is developed to remove discontinuity from the predicted waveform. Overall, methodologies from physics guided machine learning show a notable improvement in prediction performance, but additional loss functions are necessary for constructing predictive networks on small datasets.

Keywords: aeroacoustics, machine learning, propeller, rotor, neural network, physics guided machine learning

Procedia PDF Downloads 188
8501 Optimization Method of Dispersed Generation in Electrical Distribution Systems

Authors: Mahmoud Samkan

Abstract:

Dispersed Generation (DG) is a promising solution to many power system problems such as voltage regulation and power loss. This paper proposes a heuristic two-step method to optimize the location and size of DG for reducing active power losses and, therefore, improve the voltage profile in radial distribution networks. In addition to a DG placed at the system load gravity center, this method consists in assigning a DG to each lateral of the network. After having determined the central DG placement, the location and size of each lateral DG are predetermined in the first step. The results are then refined in the second step. This method is tested for 33-bus system for 100% DG penetration. The results obtained are compared with those of other methods found in the literature.

Keywords: optimal location, optimal size, dispersed generation (DG), radial distribution networks, reducing losses

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8500 Dynamic Test for Stability of Bar Loaded by a Compression Force Directed Towards the Pole

Authors: Elia Efraim, Boris Blostotsky

Abstract:

The phenomenon of buckling of structural elements under compression is revealed in many cases of loading and found consideration in many structures and mechanisms. In the present work the method and results of dynamic test for buckling of bar loaded by a compression force directed towards the pole are considered. Experimental determination of critical force for such system has not been made previously. The tested object is a bar with semi-rigid connection to the base at one of its ends, and with a hinge moving along a circle at the other. The test includes measuring the natural frequency of the bar at different values of compression load. The lateral stiffness is calculated based on natural frequency and reduced mass on the bar's movable end. The critical load is determined by extrapolation the values of lateral stiffness up to zero value. For the experimental investigation the special test-bed was created that allows the stability testing at positive and negative curvature of the movable end's trajectory, as well as varying the rotational stiffness of the other end connection. Decreasing a friction at the movable end allows extend the diapason of applied compression force. The testing method includes : - methodology of the experiment planning, that allows determine the required number of tests under various loads values in the defined range and the type of extrapolating function; - methodology of experimental determination of reduced mass at the bar's movable end including its own mass; - methodology of experimental determination of lateral stiffness of uncompressed bar rotational semi-rigid connection at the base. For planning the experiment and for comparison of the experimental results with the theoretical values of critical load, the analytical dependencies of lateral stiffness of the bar with defined end conditions on compression load. In the particular case of perfectly rigid connection of the bar to the base, the critical load value corresponds to solution by S.P. Timoshenko. Correspondence of the calculated and experimental values was obtained.

Keywords: buckling, dynamic method, end-fixity factor, force directed towards a pole

Procedia PDF Downloads 326
8499 A Review on Disaster Risk Reduction and Sustainable Development in Nigeria

Authors: Kudu Dangana

Abstract:

The occurrences of disaster often call for the support of both government and non-government organization. Consequently, disaster relief remains extremely important in disaster management. However, this approach alone does not proactively address the need to adduce the human and environment impacts of future disasters. Recent thinking in the area of disaster management is indicative of the need for a new paradigm that focuses on reducing the risk of disasters with the involvement and participation of communities. This paper reviews the need for communities to place more emphasis on a holistic approach to disaster risk reduction. This approach involves risk assessment, risk reduction, early warning and disaster preparedness in order to effectively address the reduction of social, economic, and environmental costs of disasters nationally and at the global level.

Keywords: disaster, early, management, warning, relief, risk vulnerability

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8498 Mechanical Behaviours of Ti/GFRP/Ti Laminates with Different Surface Treatments of Titanium Sheets

Authors: Amit Kumar Haldar, Mark Simms, Ian McDevitt, Anthony Comer

Abstract:

Interface properties of fiber metal laminates (FML) affects the integrity and deformation failure modes. In this paper, the mechanical behaviours of Ti/GFRP/Ti laminates were experimentally investigated through low-velocity impact tests. Two different surface treatments of Titanium (Ti-6Al-4V) alloy sheets were prepared to obtain the composite interface properties based on annealing and sandblast surface treatment processes. The deformation failure modes, impact load sustaining ability and energy absorption capacity of FMLs were analysed. The impact load and modulus were shown to be dependent on the surface treatments of Titanium (Ti-6Al-4V) alloy sheets. It was demonstrated that the impact load performance was enhanced when titanium surfaces were annealed and sandblasted. It has also been shown that the values of the strength and energy absorption were slightly higher when the tests conducted at relatively higher loading rate, as a result of the rate-sensitive effects on the damage resistance of the FML.

Keywords: fiber metal laminates, metal composite interface, indentation, low velocity impact

Procedia PDF Downloads 171
8497 Performance of the Aptima® HIV-1 Quant Dx Assay on the Panther System

Authors: Siobhan O’Shea, Sangeetha Vijaysri Nair, Hee Cheol Kim, Charles Thomas Nugent, Cheuk Yan William Tong, Sam Douthwaite, Andrew Worlock

Abstract:

The Aptima® HIV-1 Quant Dx Assay is a fully automated assay on the Panther system. It is based on Transcription-Mediated Amplification and real time detection technologies. This assay is intended for monitoring HIV-1 viral load in plasma specimens and for the detection of HIV-1 in plasma and serum specimens. Nine-hundred and seventy nine specimens selected at random from routine testing at St Thomas’ Hospital, London were anonymised and used to compare the performance of the Aptima HIV-1 Quant Dx assay and Roche COBAS® AmpliPrep/COBAS® TaqMan® HIV-1 Test, v2.0. Two-hundred and thirty four specimens gave quantitative HIV-1 viral load results in both assays. The quantitative results reported by the Aptima Assay were comparable those reported by the Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 Test, v2.0 with a linear regression slope of 1.04 and an intercept on -0.097. The Aptima assay detected HIV-1 in more samples than the Roche assay. This was not due to lack of specificity of the Aptima assay because this assay gave 99.83% specificity on testing plasma specimens from 600 HIV-1 negative individuals. To understand the reason for this higher detection rate a side-by-side comparison of low level panels made from the HIV-1 3rd international standard (NIBSC10/152) and clinical samples of various subtypes were tested in both assays. The Aptima assay was more sensitive than the Roche assay. The good sensitivity, specificity and agreement with other commercial assays make the HIV-1 Quant Dx Assay appropriate for both viral load monitoring and detection of HIV-1 infections.

Keywords: HIV viral load, Aptima, Roche, Panther system

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8496 Parametric Analysis and Optimal Design of Functionally Graded Plates Using Particle Swarm Optimization Algorithm and a Hybrid Meshless Method

Authors: Foad Nazari, Seyed Mahmood Hosseini, Mohammad Hossein Abolbashari, Mohammad Hassan Abolbashari

Abstract:

The present study is concerned with the optimal design of functionally graded plates using particle swarm optimization (PSO) algorithm. In this study, meshless local Petrov-Galerkin (MLPG) method is employed to obtain the functionally graded (FG) plate’s natural frequencies. Effects of two parameters including thickness to height ratio and volume fraction index on the natural frequencies and total mass of plate are studied by using the MLPG results. Then the first natural frequency of the plate, for different conditions where MLPG data are not available, is predicted by an artificial neural network (ANN) approach which is trained by back-error propagation (BEP) technique. The ANN results show that the predicted data are in good agreement with the actual one. To maximize the first natural frequency and minimize the mass of FG plate simultaneously, the weighted sum optimization approach and PSO algorithm are used. However, the proposed optimization process of this study can provide the designers of FG plates with useful data.

Keywords: optimal design, natural frequency, FG plate, hybrid meshless method, MLPG method, ANN approach, particle swarm optimization

Procedia PDF Downloads 338
8495 A Decision Support System to Detect the Lumbar Disc Disease on the Basis of Clinical MRI

Authors: Yavuz Unal, Kemal Polat, H. Erdinc Kocer

Abstract:

In this study, a decision support system comprising three stages has been proposed to detect the disc abnormalities of the lumbar region. In the first stage named the feature extraction, T2-weighted sagittal and axial Magnetic Resonance Images (MRI) were taken from 55 people and then 27 appearance and shape features were acquired from both sagittal and transverse images. In the second stage named the feature weighting process, k-means clustering based feature weighting (KMCBFW) proposed by Gunes et al. Finally, in the third stage named the classification process, the classifier algorithms including multi-layer perceptron (MLP- neural network), support vector machine (SVM), Naïve Bayes, and decision tree have been used to classify whether the subject has lumbar disc or not. In order to test the performance of the proposed method, the classification accuracy (%), sensitivity, specificity, precision, recall, f-measure, kappa value, and computation times have been used. The best hybrid model is the combination of k-means clustering based feature weighting and decision tree in the detecting of lumbar disc disease based on both sagittal and axial MR images.

Keywords: lumbar disc abnormality, lumbar MRI, lumbar spine, hybrid models, hybrid features, k-means clustering based feature weighting

Procedia PDF Downloads 499
8494 Seismic Assessment of Flat Slab and Conventional Slab System for Irregular Building Equipped with Shear Wall

Authors: Muhammad Aji Fajari, Ririt Aprilin Sumarsono

Abstract:

Particular instability of structural building under lateral load (e.g earthquake) will rise due to irregularity in vertical and horizontal direction as stated in SNI 03-1762-2012. The conventional slab has been considered for its less contribution in increasing the stability of the structure, except special slab system such as flat slab turned into account. In this paper, the analysis of flat slab system at Sequis Tower located in South Jakarta will be assessed its performance under earthquake. It consists of 6 floors of the basement where the flat slab system is applied. The flat slab system will be the main focus in this paper to be compared for its performance with conventional slab system under earthquake. Regarding the floor plan of Sequis Tower basement, re-entrant corner signed for this building is 43.21% which exceeded the allowable re-entrant corner is 15% as stated in ASCE 7-05 Based on that, the horizontal irregularity will be another concern for analysis, otherwise vertical irregularity does not exist for this building. Flat slab system is a system where the slabs use drop panel with shear head as their support instead of using beams. Major advantages of flat slab application are decreasing dead load of structure, removing beams so that the clear height can be maximized, and providing lateral resistance due to lateral load. Whilst, deflection at middle strip and punching shear are problems to be detail considered. Torsion usually appears when the structural member under flexure such as beam or column dimension is improper in ratio. Considering flat slab as alternative slab system will keep the collapse due to torsion down. Common seismic load resisting system applied in the building is a shear wall. Installation of shear wall will keep the structural system stronger and stiffer affecting in reduced displacement under earthquake. Eccentricity of shear wall location of this building resolved the instability due to horizontal irregularity so that the earthquake load can be absorbed. Performing linear dynamic analysis such as response spectrum and time history analysis due to earthquake load is suitable as the irregularity arise so that the performance of structure can be significantly observed. Utilization of response spectrum data for South Jakarta which PGA 0.389g is basic for the earthquake load idealization to be involved in several load combinations stated on SNI 03-1726-2012. The analysis will result in some basic seismic parameters such as period, displacement, and base shear of the system; besides the internal forces of the critical member will be presented. Predicted period of a structure under earthquake load is 0.45 second, but as different slab system applied in the analysis then the period will show a different value. Flat slab system will probably result in better performance for the displacement parameter compare to conventional slab system due to higher contribution of stiffness to the whole system of the building. In line with displacement, the deflection of the slab will result smaller for flat slab than a conventional slab. Henceforth, shear wall will be effective to strengthen the conventional slab system than flat slab system.

Keywords: conventional slab, flat slab, horizontal irregularity, response spectrum, shear wall

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8493 Impact of Agroforestry Practices on Biodiversity Management and Livelihoods of Communities Adjacent Magamba Nature Reserve(MNR), Tanzania

Authors: P. J. Kagosi, M. Mndolwa, E. Japhate

Abstract:

The study was conducted to communities adjacent MNR, Lushoto district, Tanzania. The MNR is one of the nine nature reserves in the Eastern Arc Mountains of Tanzania with an area of 8,700ha with high biological diversity. However, biodiversity in MNR have been threatened by increasing human activities for livelihood in 1970s. The AF systems in the study area was practised since 1980s however, no study was conducted on AF impacts. This paper presents the influence of AF on livelihood of communities adjacent MNR and biodiversity conservation. Qualitative and quantitative data were collected using socio-economic survey and botanical surveys. Data were analysed using Statistical Packages for Social Sciences and content analysis. The study found that in 1970s free livestock grazing caused considerable surface runoff, soil erosion and reduction of crop production. Since 1980s, the study area received various interventions based on the land conservations and improved livelihood through practising AF systems. It was further found that the AF farming improved crop productivity, reduced soil erosion, increased firewood (80.2%) and other forest products availability and AF encouraged community members practicing indoor livestock keeping.The dominant agroforestry tree found in the study area is grevillea reported by 74.1% of respondents planting an average of 40 trees. The study found that the AF reduced pressure to MNR as forest products and fodders were obtained from community's farms in turn, currently water flow from MNR has been increased. Thus AF products support livelihood needs and conserve biodiversity. The study recommends continuity education on new AF technology packages.

Keywords: impact of agroforestry, biodiversity management, communities’ livelihoods, Magamba nature reserve

Procedia PDF Downloads 320
8492 Sensor Validation Using Bottleneck Neural Network and Variable Reconstruction

Authors: Somia Bouzid, Messaoud Ramdani

Abstract:

The success of any diagnosis strategy critically depends on the sensors measuring process variables. This paper presents a detection and diagnosis sensor faults method based on a Bottleneck Neural Network (BNN). The BNN approach is used as a statistical process control tool for drinking water distribution (DWD) systems to detect and isolate the sensor faults. Variable reconstruction approach is very useful for sensor fault isolation, this method is validated in simulation on a nonlinear system: actual drinking water distribution system. Several results are presented.

Keywords: fault detection, localization, PCA, NLPCA, auto-associative neural network

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8491 The Ability of Consortium Wastewater Protozoan and Bacterial Species to Remove Chemical Oxygen Demand in the Presence of Nanomaterials under Varying pH Conditions

Authors: Anza-Vhudziki Mboyi, Ilunga Kamika, Maggy Momba

Abstract:

The aim of this study was to ascertain the survival limit and capability of commonly found wastewater protozoan (Aspidisca sp, Trachelophyllum sp, and Peranema sp) and bacterial (Bacillus licheniformis, Brevibacillus laterosporus, and Pseudomonas putida) species to remove COD while exposed to commercial nanomaterials under varying pH conditions. The experimental study was carried out in modified mixed liquor media adjusted to various pH levels (pH 2, 7 and 10), and a comparative study was performed to determine the difference between the cytotoxicity effects of commercial zinc oxide (nZnO) and silver (nAg) nanomaterials (NMs) on the target wastewater microbial communities using standard methods. The selected microbial communities were exposed to lethal concentrations ranging from 0.015 g/L to 40 g/L for nZnO and from 0.015 g/L to 2 g/L for nAg for a period of 5 days of incubation at 30°C (100 r/min). Compared with the absence of NMs in wastewater mixed liquor, the relevant environmental concentration ranging between 10 µg/L and 100 µg/L, for both nZnO and nAg caused no adverse effects, but the presence of 20 g of nZnO/L and 0.65 g of nAg/L significantly inhibited microbial growth. Statistical evidence showed that nAg was significantly more toxic compared to nZnO, but there was an insignificant difference in toxicity between microbial communities and pH variations. A significant decrease in the removal of COD by microbial populations was observed in the presence of NMs with a moderate correlation of r = 0.3 to r = 0.7 at all pH levels. It was evident that there was a physical interaction between commercial NMs and target wastewater microbial communities; although not quantitatively assessed, cell morphology and cell death were observed. Such phenomena suggest the high resilience of the microbial community, but it is the accumulation of NMs that will have adverse effects on the performance in terms of COD removal.

Keywords: bacteria, biological treatment, chemical oxygen demand (COD) and nanomaterials, consortium, pH, protozoan

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8490 Population Stereotype Production, User Factors, and Icon Design for Underserved Communities of Rural India

Authors: Avijit Sengupta, Klarissa Ting Ting Cheng, Maffee Peng-Hui Wan

Abstract:

This study investigates the influence of user factors and referent characteristics on representation types generated using the stereotype production method for designing icons. Sixty-eight participants of farming communities were asked to draw images based on sixteen feature referents. Significant statistical differences were found between the types of representations generated for contextual and context-independent referents. Strong correlations were observed between years of formal education and total number of abstract representations produced for both contextual and context-independent referents. However, representation characteristics were not influenced by other user factors such as participants’ experience with mobile phone and years of farming experience. A statistically significant tendency of making concrete representations was observed for both contextual and context-independent referents. These findings provide insights on community members’ involvement in icon design and suggest a consolidated icon design strategy based on population stereotype, particularly for under-served rural communities of India.

Keywords: abstract representation, concrete representation, participatory design, population stereotype

Procedia PDF Downloads 357
8489 Enhancement Effect of Superparamagnetic Iron Oxide Nanoparticle-Based MRI Contrast Agent at Different Concentrations and Magnetic Field Strengths

Authors: Bimali Sanjeevani Weerakoon, Toshiaki Osuga, Takehisa Konishi

Abstract:

Magnetic Resonance Imaging Contrast Agents (MRI-CM) are significant in the clinical and biological imaging as they have the ability to alter the normal tissue contrast, thereby affecting the signal intensity to enhance the visibility and detectability of images. Superparamagnetic Iron Oxide (SPIO) nanoparticles, coated with dextran or carboxydextran are currently available for clinical MR imaging of the liver. Most SPIO contrast agents are T2 shortening agents and Resovist (Ferucarbotran) is one of a clinically tested, organ-specific, SPIO agent which has a low molecular carboxydextran coating. The enhancement effect of Resovist depends on its relaxivity which in turn depends on factors like magnetic field strength, concentrations, nanoparticle properties, pH and temperature. Therefore, this study was conducted to investigate the impact of field strength and different contrast concentrations on enhancement effects of Resovist. The study explored the MRI signal intensity of Resovist in the physiological range of plasma from T2-weighted spin echo sequence at three magnetic field strengths: 0.47 T (r1=15, r2=101), 1.5 T (r1=7.4, r2=95), and 3 T (r1=3.3, r2=160) and the range of contrast concentrations by a mathematical simulation. Relaxivities of r1 and r2 (L mmol-1 Sec-1) were obtained from a previous study and the selected concentrations were 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 2.0, and 3.0 mmol/L. T2-weighted images were simulated using TR/TE ratio as 2000 ms /100 ms. According to the reference literature, with increasing magnetic field strengths, the r1 relaxivity tends to decrease while the r2 did not show any systematic relationship with the selected field strengths. In parallel, this study results revealed that the signal intensity of Resovist at lower concentrations tends to increase than the higher concentrations. The highest reported signal intensity was observed in the low field strength of 0.47 T. The maximum signal intensities for 0.47 T, 1.5 T and 3 T were found at the concentration levels of 0.05, 0.06 and 0.05 mmol/L, respectively. Furthermore, it was revealed that, the concentrations higher than the above, the signal intensity was decreased exponentially. An inverse relationship can be found between the field strength and T2 relaxation time, whereas, the field strength was increased, T2 relaxation time was decreased accordingly. However, resulted T2 relaxation time was not significantly different between 0.47 T and 1.5 T in this study. Moreover, a linear correlation of transverse relaxation rates (1/T2, s–1) with the concentrations of Resovist can be observed. According to these results, it can conclude that the concentration of SPIO nanoparticle contrast agents and the field strengths of MRI are two important parameters which can affect the signal intensity of T2-weighted SE sequence. Therefore, when MR imaging those two parameters should be considered prudently.

Keywords: Concentration, resovist, field strength, relaxivity, signal intensity

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8488 A Post-Occupancy Evaluation of LEED-Certified Residential Communities Using Structural Equation Modeling

Authors: Mohsen Goodarzi, George Berghorn

Abstract:

Despite the rapid growth in the number of green building and community development projects, the long-term performance of these projects has not yet been sufficiently evaluated from the users’ points of view. This is partially due to the lack of post-occupancy evaluation tools available for this type of project. In this study, a post-construction evaluation model is developed to evaluate the relationship between the perceived performance and satisfaction of residents in LEED-certified residential buildings and communities. To develop this evaluation model, a primary five-factor model was developed based on the existing models and residential satisfaction theories. Each factor of the model included several measures that were adopted from LEED certification systems such as LEED-BD+C New Construction, LEED-BD+C Multifamily Midrise, LEED-ND, as well as the UC Berkeley’s Center for the Built Environment survey tool. The model included four predictor variables (factors), including perceived building performance (8 measures), perceived infrastructure performance (9 measures), perceived neighborhood design (6 measures), and perceived economic performance (4 measures), and one dependent variable (factor), which was residential satisfaction (6 measures). An online survey was then conducted to collect the data from the residents of LEED-certified residential communities (n=192) and the validity of the model was tested through Confirmatory Factor Analysis (CFA). After modifying the CFA model, 26 measures, out of the initial 33 measures, were retained to enter into a Structural Equation Model (SEM) and to find the relationships between the perceived buildings performance, infrastructure performance, neighborhood design, economic performance and residential Satisfaction. The results of the SEM showed that the perceived building performance was the most influential factor in determining residential satisfaction in LEED-certified communities, followed by the perceived neighborhood design. On the other hand, perceived infrastructure performance and perceived economic performance did not show any significant relationship with residential satisfaction in these communities. This study can benefit green building researchers by providing a model for the evaluation of the long-term performance of these projects. It can also provide opportunities for green building practitioners to determine priorities for future residential development projects.

Keywords: green building, residential satisfaction, perceived performance, confirmatory factor analysis, structural equation modeling

Procedia PDF Downloads 212
8487 Optimizing Protection of Medieval Glass Mosaic

Authors: J. Valach, S. Pospisil, S. Kuznecov

Abstract:

The paper deals with experimental estimation of future environmental load on medieval mosaic of Last Judgement on entrance to St. Vitus cathedral on Prague castle. The mosaic suffers from seasonal changes of weather pattern, as well as rains, their acidity, deposition of dust and sooth particles from polluted air and also from freeze-thaw cycles. These phenomena influence state of the mosaic. The mosaic elements, tesserae are mostly made from glass prone to weathering. To estimate future procedure of the best maintenance, relation between various weather scenarios and their effect on the mosaic was investigated. At the same time local method for evaluation of protective coating was developed. Together both methods will contribute to better care for the mosaic and also visitors aesthetical experience.

Keywords: environmental load, cultural heritage, glass mosaic, protection

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8486 Transport Related Air Pollution Modeling Using Artificial Neural Network

Authors: K. D. Sharma, M. Parida, S. S. Jain, Anju Saini, V. K. Katiyar

Abstract:

Air quality models form one of the most important components of an urban air quality management plan. Various statistical modeling techniques (regression, multiple regression and time series analysis) have been used to predict air pollution concentrations in the urban environment. These models calculate pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. Artificial neural network (ANN) is increasingly used as an alternative tool for modeling the pollutants from vehicular traffic particularly in urban areas. In the present paper, an attempt has been made to model traffic air pollution, specifically CO concentration using neural networks. In case of CO concentration, two scenarios were considered. First, with only classified traffic volume input and the second with both classified traffic volume and meteorological variables. The results showed that CO concentration can be predicted with good accuracy using artificial neural network (ANN).

Keywords: air quality management, artificial neural network, meteorological variables, statistical modeling

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8485 Quantitative Analysis of the Quality of Housing and Land Use in the Built-up area of Croatian Coastal City of Zadar

Authors: Silvija Šiljeg, Ante Šiljeg, Branko Cavrić

Abstract:

Housing is considered as a basic human need and important component of the quality of life (QoL) in urban areas worldwide. In contemporary housing studies, the concept of the quality of housing (QoH) is considered as a multi-dimensional and multi-disciplinary field. It emphasizes connection between various aspects of the QoL which could be measured by quantitative and qualitative indicators at different spatial levels (e.g. local, city, metropolitan, regional). The main goal of this paper is to examine the QoH and compare results of quantitative analysis with the clutter land use categories derived for selected local communities in Croatian Coastal City of Zadar. The qualitative housing analysis based on the four housing indicators (out of total 24 QoL indicators) has provided identification of the three Zadar’s local communities with the highest estimated QoH ranking. Furthermore, by using GIS overlay techniques, the QoH was merged with the urban environment analysis and introduction of spatial metrics based on the three categories: the element, class and environment as a whole. In terms of semantic-content analysis, the research has also generated a set of indexes suitable for evaluation of “housing state of affairs” and future decision making aiming at improvement of the QoH in selected local communities.

Keywords: housing, quality, indicators, indexes, urban environment, GIS, element, class

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8484 Finding a Redefinition of the Relationship between Rural and Urban Knowledge

Authors: Bianca Maria Rulli, Lenny Valentino Schiaretti

Abstract:

The considerable recent urbanization has increasingly sharpened environmental and social problems all over the world. During the recent years, many answers to the alarming attitudes in modern cities have emerged: a drastic reduction in the rate of growth is becoming essential for future generations and small scale economies are considered more adaptive and sustainable. According to the concept of degrowth, cities should consider surpassing the centralization of urban living by redefining the relationship between rural and urban knowledge; growing food in cities fundamentally contributes to the increase of social and ecological resilience. Through an innovative approach, this research combines the benefits of urban agriculture (increase of biological diversity, shorter and thus more efficient supply chains, food security) and temporary land use. They stimulate collaborative practices to satisfy the changing needs of communities and stakeholders. The concept proposes a coherent strategy to create a sustainable development of urban spaces, introducing a productive green-network to link specific areas in the city. By shifting the current relationship between architecture and landscape, the former process of ground consumption is deeply revised. Temporary modules can be used as concrete tools to create temporal areas of innovation, transforming vacant or marginal spaces into potential laboratories for the development of the city. The only permanent ground traces, such as foundations, are minimized in order to allow future land re-use. The aim is to describe a new mindset regarding the quality of space in the metropolis which allows, in a completely flexible way, to bring back the green and the urban farming into the cities. The wide possibilities of the research are analyzed in two different case-studies. The first is a regeneration/connection project designated for social housing, the second concerns the use of temporary modules to answer to the potential needs of social structures. The intention of the productive green-network is to link the different vacant spaces to each other as well as to the entire urban fabric. This also generates a potential improvement of the current situation of underprivileged and disadvantaged persons.

Keywords: degrowth, green network, land use, temporary building, urban farming

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8483 The Green Propaganda: Paradoxes of Costa Rica as the Poster Child for Sustainable Tourism

Authors: Maria Jose Ramos Villagra

Abstract:

Since the boom of tourism in the late 80s and 90s, Costa Rica is considered as one of the leading countries for tourism. The size and geography of its territory, its low population density, and its image of being one of the most stable Latin American democracies make Costa Rica an attractive and safe target for foreign investors. Land ownership by foreign investors has increased as the natural resources in rural communities have been exhausted. When nature becomes an instrument to increase profit, it loses its communal value contributing to local communities losing their sovereignty and access to basic resources. The rural regions in proximity to the most tourist areas are often the most marginalized. The purpose of this research is to use the case of the rural community Sardinal and its struggle to protect its aquifer to investigate the economic and cultural consequences of the tourism boom in Costa Rican rural communities. The process of reclaiming the access to and the preservation of the aquifer enabled individuals to redefine their political views and their political power. The case of Sardinal broke the stereotypes about rural individuals and their ability to politically educate themselves and organize. Sardinal´s conflict brought to light the necessity of questioning the role of modern tourism as part of Costa Rica’s national identity, and as a tool for development

Keywords: Costa Rica, tourism, rural development, economy, ecotourism, environment, water, Sardinal

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8482 MegaProjects and the Governing Processes That Lead to Success and Failure: A Literature Review

Authors: Fangwei Zhu, Wei Tian, Linzhuo Wang, Miao Yu

Abstract:

Megaproject has long been a critical issue in project governance, for its low success rate and large impact on society. Although the extant literature on megaproject governance is vast, to our best knowledge, the lacking of a thorough literature review makes it hard for us to gain a holistic view on current scenario of megaproject governance. The study conducts a systematic literature review process to analyze the existing literatures on megaproject governance. The finding indicates that mega project governance needs to be handled at network level and forming a network level governance provides a holistic framework for governing megaproject towards sustainable development of the projects. Theoretical and practical implications, as well as future studies and limitations, were discussed.

Keywords: megaproject, governance, literature review, network

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8481 Unfolding Global Biodiversity Patterns of Marine Planktonic Diatom Communities across the World's Oceans

Authors: Shruti Malviya, Chris Bowler

Abstract:

Analysis of microbial eukaryotic diversity is fundamental to understanding ecosystems’ structure, biology, and ecology. Diatoms (Stramenopiles, Bacillariophyceae) are one of the most diverse and ecologically prominent groups of phytoplankton. This study was performed to enhance the understanding of global biodiversity patterns and structure of planktonic diatom communities across the world's oceans. We used the metabarcoding data set generated from the biological samples and associated environmental data collected during the Tara Oceans (2009-2013) global circumnavigation covering all major oceanic provinces. A total of ~18 million diatom V9-18S rDNA tags from 126 sampling stations, constituting 631 size-fractionated plankton communities were generated. Using ~250,000 unique diatom metabarcodes, the global diatom distribution and diversity across size classes, genus and ecological niches was assessed. Notably, our analysis revealed: (i) a new estimate of the total number of planktonic diatom species, (ii) a considerable unknown diversity and exceptionally high diversity in the open ocean, and (iii) complex diversity patterns across oceanic provinces. Also, co-occurrence of several ribotypes in locations separated by great geographic distances (equatorial stations) demonstrated a widespread but not ubiquitous distribution. This work provides a comprehensive perspective on diatom distribution and diversity in the world’s oceans and elaborates interconnections between associated theories and underlying drivers. It shows how meta-barcoding approaches can provide a framework to investigate environmental diversity at a global scale, which is deemed as an essential step in answering various ecological research questions. Consequently, this work also provides a reference point to explore how microbial communities will respond to environmental conditions.

Keywords: diatoms, Tara Oceans, biodiversity, metabarcoding

Procedia PDF Downloads 119
8480 Machine Learning Prediction of Compressive Damage and Energy Absorption in Carbon Fiber-Reinforced Polymer Tubular Structures

Authors: Milad Abbasi

Abstract:

Carbon fiber-reinforced polymer (CFRP) composite structures are increasingly being utilized in the automotive industry due to their lightweight and specific energy absorption capabilities. Although it is impossible to predict composite mechanical properties directly using theoretical methods, various research has been conducted so far in the literature for accurate simulation of CFRP structures' energy-absorbing behavior. In this research, axial compression experiments were carried out on hand lay-up unidirectional CFRP composite tubes. The fabrication method allowed the authors to extract the material properties of the CFRPs using ASTM D3039, D3410, and D3518 standards. A neural network machine learning algorithm was then utilized to build a robust prediction model to forecast the axial compressive properties of CFRP tubes while reducing high-cost experimental efforts. The predicted results have been compared with the experimental outcomes in terms of load-carrying capacity and energy absorption capability. The results showed high accuracy and precision in the prediction of the energy-absorption capacity of the CFRP tubes. This research also demonstrates the effectiveness and challenges of machine learning techniques in the robust simulation of composites' energy-absorption behavior. Interestingly, the proposed method considerably condensed numerical and experimental efforts in the simulation and calibration of CFRP composite tubes subjected to compressive loading.

Keywords: CFRP composite tubes, energy absorption, crushing behavior, machine learning, neural network

Procedia PDF Downloads 121
8479 Predicting the Success of Bank Telemarketing Using Artificial Neural Network

Authors: Mokrane Selma

Abstract:

The shift towards decision making (DM) based on artificial intelligence (AI) techniques will change the way in which consumer markets and our societies function. Through AI, predictive analytics is being used by businesses to identify these patterns and major trends with the objective to improve the DM and influence future business outcomes. This paper proposes an Artificial Neural Network (ANN) approach to predict the success of telemarketing calls for selling bank long-term deposits. To validate the proposed model, we uses the bank marketing data of 41188 phone calls. The ANN attains 98.93% of accuracy which outperforms other conventional classifiers and confirms that it is credible and valuable approach for telemarketing campaign managers.

Keywords: bank telemarketing, prediction, decision making, artificial intelligence, artificial neural network

Procedia PDF Downloads 120
8478 Forecast of Polyethylene Properties in the Gas Phase Polymerization Aided by Neural Network

Authors: Nasrin Bakhshizadeh, Ashkan Forootan

Abstract:

A major problem that affects the quality control of polymer in the industrial polymerization is the lack of suitable on-line measurement tools to evaluate the properties of the polymer such as melt and density indices. Controlling the polymerization in ordinary method is performed manually by taking samples, measuring the quality of polymer in the lab and registry of results. This method is highly time consuming and leads to producing large number of incompatible products. An online application for estimating melt index and density proposed in this study is a neural network based on the input-output data of the polyethylene production plant. Temperature, the level of reactors' bed, the intensity of ethylene mass flow, hydrogen and butene-1, the molar concentration of ethylene, hydrogen and butene-1 are used for the process to establish the neural model. The neural network is taught based on the actual operational data and back-propagation and Levenberg-Marquart techniques. The simulated results indicate that the neural network process model established with three layers (one hidden layer) for forecasting the density and the four layers for the melt index is able to successfully predict those quality properties.

Keywords: polyethylene, polymerization, density, melt index, neural network

Procedia PDF Downloads 122
8477 Implementation of the Recursive Formula for Evaluation of the Strength of Daniels' Bundle

Authors: Vaclav Sadilek, Miroslav Vorechovsky

Abstract:

The paper deals with the classical fiber bundle model of equal load sharing, sometimes referred to as the Daniels' bundle or the democratic bundle. Daniels formulated a multidimensional integral and also a recursive formula for evaluation of the strength cumulative distribution function. This paper describes three algorithms for evaluation of the recursive formula and also their implementations with source codes in high-level programming language Python. A comparison of the algorithms are provided with respect to execution time. Analysis of orders of magnitudes of addends in the recursion is also provided.

Keywords: equal load sharing, mpmath, python, strength of Daniels' bundle

Procedia PDF Downloads 380
8476 Analysis and Prediction of COVID-19 by Using Recurrent LSTM Neural Network Model in Machine Learning

Authors: Grienggrai Rajchakit

Abstract:

As we all know that coronavirus is announced as a pandemic in the world by WHO. It is speeded all over the world with few days of time. To control this spreading, every citizen maintains social distance and self-preventive measures are the best strategies. As of now, many researchers and scientists are continuing their research in finding out the exact vaccine. The machine learning model finds that the coronavirus disease behaves in an exponential manner. To abolish the consequence of this pandemic, an efficient step should be taken to analyze this disease. In this paper, a recurrent neural network model is chosen to predict the number of active cases in a particular state. To make this prediction of active cases, we need a database. The database of COVID-19 is downloaded from the KAGGLE website and is analyzed by applying a recurrent LSTM neural network with univariant features to predict the number of active cases of patients suffering from the corona virus. The downloaded database is divided into training and testing the chosen neural network model. The model is trained with the training data set and tested with a testing dataset to predict the number of active cases in a particular state; here, we have concentrated on Andhra Pradesh state.

Keywords: COVID-19, coronavirus, KAGGLE, LSTM neural network, machine learning

Procedia PDF Downloads 137
8475 Influence of Pressure from Compression Textile Bands: Their Using in the Treatment of Venous Human Leg Ulcers

Authors: Bachir Chemani, Rachid Halfaoui

Abstract:

The aim of study was to evaluate pressure distribution characteristics of the elastic textile bandages using two instrumental techniques: a prototype Instrument and a load Transference. The prototype instrument which simulates shape of real leg has pressure sensors which measure bandage pressure. Using this instrument, the results show that elastic textile bandages presents different pressure distribution characteristics and none produces a uniform distribution around lower limb. The load transference test procedure is used to determine whether a relationship exists between elastic textile bandage structure and pressure distribution characteristics. The test procedure assesses degree of load, directly transferred through a textile when loads series are applied to bandaging surface. A range of weave fabrics was produced using needle weaving machine and a sewing technique. A textile bandage was developed with optimal characteristics far superior pressure distribution than other bandages. From results, we find that theoretical pressure is not consistent exactly with practical pressure. It is important in this study to make a practical application for specialized nurses in order to verify the results and draw useful conclusions for predicting the use of this type of elastic band.

Keywords: textile, cotton, pressure, venous ulcers, elastic

Procedia PDF Downloads 338
8474 Video-On-Demand QoE Evaluation across Different Age-Groups and Its Significance for Network Capacity

Authors: Mujtaba Roshan, John A. Schormans

Abstract:

Quality of Experience (QoE) drives churn in the broadband networks industry, and good QoE plays a large part in the retention of customers. QoE is known to be affected by the Quality of Service (QoS) factors packet loss probability (PLP), delay and delay jitter caused by the network. Earlier results have shown that the relationship between these QoS factors and QoE is non-linear, and may vary from application to application. We use the network emulator Netem as the basis for experimentation, and evaluate how QoE varies as we change the emulated QoS metrics. Focusing on Video-on-Demand, we discovered that the reported QoE may differ widely for users of different age groups, and that the most demanding age group (the youngest) can require an order of magnitude lower PLP to achieve the same QoE than is required by the most widely studied age group of users. We then used a bottleneck TCP model to evaluate the capacity cost of achieving an order of magnitude decrease in PLP, and found it be (almost always) a 3-fold increase in link capacity that was required.

Keywords: network capacity, packet loss probability, quality of experience, quality of service

Procedia PDF Downloads 245
8473 Performance Evaluation of DSR and OLSR Routing Protocols in MANET Using Varying Pause Time

Authors: Yassine Meraihi, Dalila Acheli, Rabah Meraihi

Abstract:

MANET for Mobile Ad hoc NETwork is a collection of wireless mobile nodes that communicates with each other without using any existing infrastructure, access point or centralized administration, due to the higher mobility and limited radio transmission range, routing is an important issue in ad hoc network, so in order to ensure reliable and efficient route between to communicating nodes quickly, an appropriate routing protocol is needed. In this paper, we present the performance analysis of two mobile ad hoc network routing protocols namely DSR and OLSR using NS2.34, the performance is determined on the basis of packet delivery ratio, throughput, average jitter and end to end delay with varying pause time.

Keywords: DSR, OLSR, quality of service, routing protocols, MANET

Procedia PDF Downloads 528