Search results for: sand production prediction

Authors: Femy M. Makkar, S. Chandrakaran, N. Sankar

Abstract:

The concept of reinforced earth has been used in the field of geotechnical engineering since 1960s, for many applications such as, construction of road and rail embankments, pavements, retaining walls, shallow foundations, soft ground improvement and so on. Conventionally, planar geosynthetic materials such as geotextiles and geogrids were used as the reinforcing elements. Recently, the use of three dimensional reinforcements becomes one of the emerging trends in this field. So, in the present investigation, three dimensional geogrid is proposed as a reinforcing material. Laboratory scaled plate load tests are conducted on a model square footing resting on 3D geogrid reinforced sand bed. The performance of 3D geogrids in triangular and square pattern was compared with conventional geogrids and the improvement in bearing capacity and reduction in settlement and heave are evaluated. When single layer of reinforcement was placed at an optimum depth of 0.25B from the bottom of the footing, the bearing capacity of conventional geogrid reinforced soil improved by 1.85 times compared to unreinforced soil, where as 3D geogrid reinforced soil with triangular pattern and square pattern shows 2.69 and 3.05 times improvement respectively compared to unreinforced soil. Also, 3D geogrids performs better than conventional geogrids in reducing the settlement and heave of sand bed around the model footing.

Keywords: 3D reinforcing elements, bearing capacity, heavy, settlement

Procedia PDF Downloads 296

Authors: Seun Mayowa Sunday

Abstract:

Loan prediction is one of the most significant and recognised fields of research in the banking, insurance, and the financial security industries. Some prediction systems on the market include the construction of static software. However, due to the fact that static software only operates with strictly regulated rules, they cannot aid customers beyond these limitations. Application of many machine learning (ML) techniques are required for loan prediction. Four separate machine learning models, random forest (RF), decision tree (DT), k-nearest neighbour (KNN), and logistic regression, are used to create the loan prediction model. Using the anaconda navigator and the required machine learning (ML) libraries, models are created and evaluated using the appropriate measuring metrics. From the finding, the random forest performs with the highest accuracy of 80.17% which was later implemented into the Django framework. For real-time testing, the web application is deployed on the Alibabacloud which is among the top 4 biggest cloud computing provider. Hence, to the best of our knowledge, this research will serve as the first academic paper which combines the model development and the Django framework, with the deployment into the Alibaba cloud computing application.

Keywords: k-nearest neighbor, random forest, logistic regression, decision tree, django, cloud computing, alibaba cloud

Procedia PDF Downloads 125

Authors: V. Jamuna, A. K. Chakravarty, C. S. Patil, Vijay Kumar, M. A. Mir, Rakesh Kumar

Abstract:

Intense selection of buffaloes for milk production at organized herds of the country without giving due attention to fertility traits viz. pregnancy rate has lead to deterioration in their performances. Aim of study is to develop an optimum model for predicting pregnancy rate and to assess the level of pregnancy rate with respect to milk production Murrah buffaloes. Data pertaining to 1224 lactation records of Murrah buffaloes spread over a period 21 years were analyzed and it was observed that pregnancy rate depicted negative phenotypic association with lactation milk yield (-0.08 ± 0.04). For developing optimum model for pregnancy rate in Murrah buffaloes seven simple and multiple regression models were developed. Among the seven models, model II having only Service period as an independent reproduction variable, was found to be the best prediction model, based on the four statistical criterions (high coefficient of determination (R 2), low mean sum of squares due to error (MSSe), conceptual predictive (CP) value, and Bayesian information criterion (BIC). For standardizing the level of fertility with milk production, pregnancy rate was classified into seven classes with the increment of 10% in all parities, life time and their corresponding average pregnancy rate in relation to the average lactation milk yield (MY).It was observed that to achieve around 2000 kg MY which can be considered optimum for Indian Murrah buffaloes, level of pregnancy rate should be in between 30-50%.

Keywords: life time, pregnancy rate, production, service period, standardization

Procedia PDF Downloads 630

Authors: Lei Zhu, Nan Li

Abstract:

Cold stamping has been widely applied in the automotive industry for the mass production of a great range of automotive panels. Predicting the springback to ensure the dimensional accuracy of the cold-stamped components is a critical step. The main approaches for the prediction and compensation of springback in cold stamping include running Finite Element (FE) simulations and conducting experiments, which require forming process expertise and can be time-consuming and expensive for the design of cold stamping tools. Machine learning technologies have been proven and successfully applied in learning complex system behaviours using presentative samples. These technologies exhibit the promising potential to be used as supporting design tools for metal forming technologies. This study, for the first time, presents a novel application of a Convolutional Neural Network (CNN) based surrogate model to predict the springback fields for variable U-shape cold bending geometries. A dataset is created based on the U-shape cold bending geometries and the corresponding FE simulations results. The dataset is then applied to train the CNN surrogate model. The result shows that the surrogate model can achieve near indistinguishable full-field predictions in real-time when compared with the FE simulation results. The application of CNN in efficient springback prediction can be adopted in industrial settings to aid both conceptual and final component designs for designers without having manufacturing knowledge.

Keywords: springback, cold stamping, convolutional neural networks, machine learning

Procedia PDF Downloads 143

Authors: Ramon Erasmo Verdin Rodriguez

Abstract:

Many has been the ways that historically the managers and gurus has been trying to get closer to the perfect supply chain, but since this topic is so vast and very complex the bigger the companies are, the duty has not been certainly easy. On this research, you are going to see thru the entrails of the logistics that happens at a glass manufacturing company with the number one raw material of the process that is the silica sand. After a very quick passage thru the supply chain, this document is going to focus on the way that raw materials flow thru the system, so after that, an analysis and research can take place to improve the logistics. Thru Operations Research techniques, it will be analyzed the current scheme of distribution and inventories of raw materials at a glass company’s plants, so after a mathematical conceptualization process, the supply chain could be optimized with the purpose of reducing the uncertainty of supply and obtaining an economic benefit at the very end of this research.

Keywords: inventory management, operations research, optimization, supply chain

Procedia PDF Downloads 323

Authors: Zatil Afifah Omar, Siti Nur Izati Azmi, Kathi Swaran, Navin Kumar

Abstract:

Lost circulation has always been one of the greatest problems faced by drilling companies during drilling operations due to excessive drilling Fluids losses. Loss of circulation leads to Huge cost and non-productive time. The objective of this study is to evaluate the sealing efficiency of a proprietary blend of synthetic rubber as loss circulation material in comparison with a conventional product such as calcium carbonate, graphite, cellulosic, and nutshells. Sand Bed Tester with a different proprietary blend of synthetic rubber compositions has been used to determine the effectiveness of the LCM in preventing drilling fluids losses in a lab scale. Test results show the proprietary blend of synthetic rubber have good bridging properties and sealing Off fractures of various sizes. The finish product is environmentally friendly with lower production lead time and lower production cost compared to current conventional loss circulation materials used in current drilling operations.

Keywords: loss circulation materials, drilling operation, sealing efficiency, LCM

Procedia PDF Downloads 177

Authors: Mostafa M. Abo Elsoud, Heba I. Elkhouly, Nagwa M. Sidkey

Abstract:

Production of rhamnolipids by Pseudomonas aeruginosa has attracted a growing interest during the last few decades due to its high productivity compared with other microorganisms. In the current work, rhamnolipids production by P. aeruginosa PAO1 was statistically modeled using Taguchi orthogonal array, numerically optimized and validated. Prickly Pear Peel (Opuntia ficus-indica) has been used as a carbon source for production of rhamnolipid. Finally, the optimum conditions for rhamnolipid production were applied in 5L working volume bioreactors at different aerations, agitation and controlled pH for maximum rhamnolipid production. In addition, kinetic studies of rhamnolipids production have been reported. At the end of the batch bioreactor optimization process, rhamnolipids production by P. aeruginosa PAO1 has reached the worldwide levels and can be applied for its industrial production.

Keywords: rhamnolipids, pseudomonas aeruginosa, statistical optimization, tagushi, opuntia ficus-indica

Procedia PDF Downloads 174

Authors: Milad Alizadeh Galdiani, Navid Sabet, Mohamad Ali Mohit, Fatemeh Palizdar

Abstract:

Railway as one of the most important transportation modes, passes through ‎various areas with different conditions ‎inevitably, and in many countries such as ‎China, United States, Australia, and Iran, it passes through sandy ‎desert areas. One ‎of the main problems in these areas is the movement of sand, causing various ‎damages ‎to ballasted railway track such as corrosion in the railway fastening system. ‎The soil composition of some desert areas like Fahraj in Iran consists of sand ‎and ‎salt. Due to the movement of sand and corrosive ions of salt, the fastening system ‎of the railway is ‎corroded, which, in turn, reduces the thickness of the components ‎and their life span.‎ In this research, the Nano-coating for fastening system of ‎the railway is ‎introduced, and its performance has been investigated in both ‎laboratory and field tests. The Nano-coating of ‎the fastening system consists of zinc-rich, epoxy, polyurethane, and additive, which is produced through ‎Nano ‎technology. This layer covers the surface of the fastening system and ‎prohibits the chemical reactions, which result in ‎corrosion. The results of ‎Electrochemical Impedance Spectroscopy (EIS) ‎indicate that corrosion resistance ‎increases 315 times by using nano-coating, salt spray test results demonstrate that ‎nano-coated components remained intact after 1000 hours.‎

Keywords: ballasted railway, Nano-coating, railway fastening system, sandy desert

Procedia PDF Downloads 120

Authors: Edwaldo R. B. Monteiro, Patricia D. M. Plentz, Edson R. De Pieri

Abstract:

Mobile robotics is gaining an increasingly important role in modern society. Several potentially dangerous or laborious tasks for human are assigned to mobile robots, which are increasingly capable. Many of these tasks need to be performed within a specified period, i.e., meet a deadline. Missing the deadline can result in financial and/or material losses. Mechanisms for predicting the missing of deadlines are fundamental because corrective actions can be taken to avoid or minimize the losses resulting from missing the deadline. In this work we propose a simple but reliable deadline missing prediction mechanism for mobile robots through the use of historical data and we use the Pioneer 3-DX robot for experiments and simulations, one of the most popular robots in academia.

Keywords: deadline missing, historical data, mobile robots, prediction mechanism

Procedia PDF Downloads 398

Authors: Chang Su Woo, Hyun Sung Park

Abstract:

Useful lifetime evaluations of rail-pads were very important in design procedure to assure the safety and reliability. It is, therefore, necessary to establish a suitable criterion for the replacement period of rail pads. In this study, we performed properties and accelerated heat aging tests of rail pads considering degradation factors and all environmental conditions including operation, and then derived a lifetime prediction equation according to changes in hardness, thickness, and static spring constants in the Arrhenius plot to establish how to estimate the aging of rail pads. With the useful lifetime prediction equation, the lifetime of e-clip pads was 2.5 years when the change in hardness was 10% at 25°C; and that of f-clip pads was 1.7 years. When the change in thickness was 10%, the lifetime of e-clip pads and f-clip pads is 2.6 years respectively. The results obtained in this study to estimate the useful lifetime of rail pads for high speed trains can be used for determining the maintenance and replacement schedule for rail pads.

Keywords: rail pads, accelerated test, Arrhenius plot, useful lifetime prediction, mechanical engineering design

Procedia PDF Downloads 318

Authors: Ayodeji O. Falade, Leonard V. Mabinya, Uchechukwu U. Nwodo, Anthony I. Okoh

Abstract:

Given the high utility of peroxidase in several industrial processes, the search for novel microorganisms with enhanced peroxidase production capacity is of keen interest. This study investigated the process conditions for optimum peroxidase production by Ensifer sp, new ligninolytic proteobacteria with peroxidase production potential. Also, some agricultural residues were valorized for peroxidase production under solid state fermentation. Peroxidase production was optimum at an initial medium pH 7, incubation temperature of 30 °C and agitation speed of 100 rpm using alkali lignin fermentation medium supplemented with guaiacol as the most effective inducer and ammonium sulphate as the best inorganic nitrogen. Optimum peroxidase production by Ensifer sp. was attained at 48 h with specific productivity of 12.76 ± 1.09 U mg⁻¹. Interestingly, probable laccase production was observed with optimum specific productivity of 12.76 ± 0.45 U mg⁻¹ at 72 h. The highest peroxidase yield was observed with sawdust as solid substrate under solid state fermentation. In conclusion, Ensifer sp. possesses the capacity for enhanced peroxidase production that can be exploited for various biotechnological applications.

Keywords: catalase-peroxidase, enzyme production, peroxidase, polymerase chain reaction, proteobacteria

Procedia PDF Downloads 304

Authors: G. P. Gunasinghe, Lilani Ruhunage, N. P. Ratnayake, G. V. I. Samaradivakara, H. M. R. Premasiri, A. S. Ratnayake, Nimila Dushantha, W. A. P. Weerakoon, K. B. A. Silva

Abstract:

Sri Lanka is affected by different natural disasters such as tsunami, landslides, lightning, and riverine flood. Out of them, riverine floods act as a major disaster in the country. Different strategies are applied to control the impacts of flood hazards, and the expansion of river mouth is considered as one of the main activities for flood mitigation and disaster reduction. However, due to this expansion process, natural sand barriers including sand spits, barrier islands, and tidal planes are destroyed or subjected to change. This, in turn, can change the hydrodynamics and sediment dynamics of the area leading to other damages to the natural coastal features. The removal of a considerable portion of naturally formed sand barrier at Kaluganga River outlet (Calido Beach), Sri Lanka to control flooding event at Kaluthara urban area on May 2017, has become a serious issue in the area causing complete collapse of river mouth barrier spit bar system leading to rapid coastal erosion Kaluganga river outlet area and saltwater intrusion into the Kaluganga River. The present investigation is focused on assessing effects due to the removal of a considerable portion of naturally formed sand barrier at Kaluganga river mouth. For this study, the beach profiles, the bathymetric surveys, and Google Earth historical satellite images, before and after the flood event were collected and analyzed. Furthermore, a beach boundary survey was also carried out in October 2018 to support the satellite image data. The results of Google Earth satellite images and beach boundary survey data analyzed show a chronological breakdown of the sand barrier at the river outlet. The comparisons of pre and post-disaster bathymetric maps and beach profiles analysis revealed a noticeable deepening of the sea bed at the nearshore zone as well. Such deepening in the nearshore zone can cause the sea waves to break very near to the coastline. This might also lead to generate new diffraction patterns resulting in differential coastal accretion and erosion scenarios. Unless immediate mitigatory measures were not taken, the impacts may cause severe problems to the sensitive Kaluganag river mouth system.

Keywords: bathymetry, beach profiles, coastal features, river outlet, sand barrier, Sri Lanka

Procedia PDF Downloads 134

Authors: Shreya Asthana

Abstract:

Testers know that the feature they tested on stage is working perfectly in production only after release went live. Sometimes something breaks in production and testers get to know through the end user’s bug raised. The panic mode starts when your staging test results do not reflect current production behavior. And you started doubting your testing skills when finally the user reported a bug to you. Testers can deploy their confidence on release day by testing on production. Once you start doing testing in production, you will see test result accuracy because it will be running on real time data and execution will be a little faster as compared to staging one due to elimination of bad data. Feature flagging, canary releases, and data cleanup can help to achieve this technique of testing. By this paper it will be easier to understand the steps to achieve production testing before making your feature live, and to modify IT company’s testing procedure, so testers can provide the bug free experience to the end users. This study is beneficial because too many people think that testing should be done in staging but not in production and now this is high time to pull out people from their old mindset of testing into a new testing world. At the end of the day, it all just matters if the features are working in production or not.

Keywords: bug free production, new testing mindset, testing strategy, testing approach

Procedia PDF Downloads 70

Authors: Mohamed Boualem Salah

Abstract:

This work involves an experimental study of the behavior of chlef sand under effect of various parameters influencing on shear strength. Because of their distinct nature, sands, silts and clays exhibit completely different behavior (shear strength, the contracting and dilatancy, the angle of internal friction and cohesion etc.). By cons when these materials are mixed, their behavior will become different from each considered alone. The behavior of these mixtures (silty sands etc.) is currently the state of several studies to better use. We studied in this work: The influence of the following factors on the shear strength: (The density, the fines content, the water content). The apparatus used for the tests is the shear box casagrande. This device, although one may have some disadvantages and modern instrumentation is appropriate used to study the shear strength of soils.

Keywords: behavior, shear strength, sand, silt, friction angle, cohesion, fines content, moisture content

Procedia PDF Downloads 403

Authors: J. Balaraju, M. Govinda Raj, C. S. N. Murthy

Abstract:

Every industry is constantly looking for enhancement of its day to day production and productivity. This can be possible only by maintaining the men and machinery at its adequate level. Prediction of performance characteristics plays an important role in performance evaluation of the equipment. Analytical and statistical approaches will take a bit more time to solve complex problems such as performance estimations as compared with software-based approaches. Keeping this in view the present study deals with an Artificial Neural Network (ANN) modelling of a Load-Haul-Dump (LHD) machine to predict the performance characteristics such as reliability, availability and preventive maintenance (PM). A feed-forward-back-propagation ANN technique has been used to model the Levenberg-Marquardt (LM) training algorithm. The performance characteristics were computed using Isograph Reliability Workbench 13.0 software. These computed values were validated using predicted output responses of ANN models. Further, recommendations are given to the industry based on the performed analysis for improvement of equipment performance.

Keywords: load-haul-dump, LHD, artificial neural network, ANN, performance, reliability, availability, preventive maintenance

Procedia PDF Downloads 144

Authors: Marta Ribo, Ian D. Goodwin, Thomas Mortlock, Phil O’Brien

Abstract:

Coastal behavior is best investigated using a sediment budget approach, based on the identification of sediment sources and sinks. Grain size distribution over the New South Wales (NSW) continental shelf has been widely characterized since the 1970’s. Coarser sediment has generally accumulated on the outer shelf, and/or nearshore zones, with the latter related to the presence of nearshore reef and bedrocks. The central part of the NSW shelf is characterized by the presence of fine sediments distributed parallel to the coastline. This study presents new grain size distribution maps along the NSW continental shelf, built using all available NSW and Commonwealth Government holdings. All available seabed bathymetric data form prior projects, single and multibeam sonar, and aerial LiDAR surveys were integrated into a single bathymetric surface for the NSW continental shelf. Grain size information was extracted from the sediment sample data collected in more than 30 studies. The information extracted from the sediment collections varied between reports. Thus, given the inconsistency of the grain size data, a common grain size classification was her defined using the phi scale. The new sediment distribution maps produced, together with new detailed seabed bathymetric data enabled us to revise the delineation of sediment compartments to more accurately reflect the true nature of sediment movement on the inner shelf and nearshore. Accordingly, nine primary mega coastal compartments were delineated along the NSW coast and shelf. The sediment compartments are bounded by prominent nearshore headlands and reefs, and major river and estuarine inlets that act as sediment sources and/or sinks. The new sediment grain size distribution was used as an input in the morphological modelling to quantify the sediment transport patterns (and indicative rates of transport), used to investigate sand supply rates and processes from the lower shoreface to the NSW coast. The rate of sand supply to the NSW coast from deep water is a major uncertainty in projecting future coastal response to sea-level rise. Offshore transport of sand is generally expected as beaches respond to rising sea levels but an onshore supply from the lower shoreface has the potential to offset some of the impacts of sea-level rise, such as coastline recession. Sediment exchange between the lower shoreface and sub-aerial beach has been modelled across the south, central, mid-north and far-north coast of NSW. Our model approach is that high-energy storm events are the primary agents of sand transport in deep water, while non-storm conditions are responsible for re-distributing sand within the beach and surf zone.

Keywords: New South Wales coast, off-shore transport, sand supply, sediment distribution maps

Procedia PDF Downloads 224

Authors: H. A. Mansour

Abstract:

The objective of this research work is studying the water use prediction, prediction technology for water use by action agencies, and others involved in conservation, planning, and environmental assessment of the Water Erosion Prediction Project (WEPP) simulation model. Models the important physical, processes governing erosion in Egypt (climate, infiltration, runoff, ET, detachment by raindrops, detachment by flowing water, deposition, etc.). Simulation of the non-uniform slope, soils, cropping/management., and Egyptian databases for climate, soils, and crops. The study included important parameters in Egyptian conditions as follows: Water Balance & Percolation, Soil Component (Tillage impacts), Plant Growth & Residue Decomposition, Overland Flow Hydraulics. It could be concluded that we can adapt the WEPP simulation model to determining the previous important parameters under Egyptian conditions.

Keywords: WEPP, adaptation, soil properties, tillage impacts, water balance, soil percolation

Procedia PDF Downloads 295

Authors: Joseph C. Chen, Venkata Mohan Kudapa

Abstract:

Development of two real-time surface roughness (Ra) prediction systems for milling operations was attempted. The systems used not only cutting parameters, such as feed rate and spindle speed, but also the cutting current generated and corrected by a clamp type energy sensor. Two different approaches were developed. First, a fuzzy inference system (FIS), in which the fuzzy logic rules are generated by experts in the milling processes, was used to conduct prediction modeling using current cutting data. Second, a neuro-fuzzy system (ANFIS) was explored. Neuro-fuzzy systems are adaptive techniques in which data are collected on the network, processed, and rules are generated by the system. The inference system then uses these rules to predict Ra as the output. Experimental results showed that the parameters of spindle speed, feed rate, depth of cut, and input current variation could predict Ra. These two systems enable the prediction of Ra during the milling operation with an average of 91.83% and 94.48% accuracy by FIS and ANFIS systems, respectively. Statistically, the ANFIS system provided better prediction accuracy than that of the FIS system.

Keywords: surface roughness, input current, fuzzy logic, neuro-fuzzy, milling operations

Procedia PDF Downloads 137

Authors: Vuk M. Popovic, Dunja D. Popovic

Abstract:

Software maintenance phase is started once a software project has been developed and delivered. After that, any modification to it corresponds to maintenance. Software maintenance involves modifications to keep a software project usable in a changed or a changing environment, to correct discovered faults, and modifications, and to improve performance or maintainability. Software maintenance and management of software maintenance are recognized as two most important and most expensive processes in a life of a software product. This research is basing the prediction of maintenance, on risks and time evaluation, and using them as data sets for working with neural networks. The aim of this paper is to provide support to project maintenance managers. They will be able to pass the issues planned for the next software-service-patch to the experts, for risk and working time evaluation, and afterward to put all data to neural networks in order to get software maintenance prediction. This process will lead to the more accurate prediction of the working hours needed for the software-service-patch, which will eventually lead to better planning of budget for the software maintenance projects.

Keywords: laboratory information system, maintenance engineering, neural networks, software maintenance, software maintenance costs

Procedia PDF Downloads 353

Authors: Jeff Clarine, Chang-Shyh Peng, Daisy Sang

Abstract:

Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.

Keywords: bioassay, machine learning, preprocessing, virtual screen

Procedia PDF Downloads 272

Authors: Anne-Lena Kampen, Øivind Kure

Abstract:

Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.

Keywords: central machine learning, embedded machine learning, energy consumption, local machine learning, wireless sensor networks, WSN

Procedia PDF Downloads 148

Authors: Mansoureh Naderipour, Susan Bastani, Mohammad Fazel Zarandi

Abstract:

Predicting links that may occur in the future and missing links in social networks is an attractive problem in social network analysis. Granular computing can help us to model the relationships between human-based system and social sciences in this field. In this paper, we present a model based on granular computing approach and Type-2 fuzzy logic to predict links regarding nodes’ activity and the relationship between two nodes. Our model is tested on collaboration networks. It is found that the accuracy of prediction is significantly higher than the Type-1 fuzzy and crisp approach.

Keywords: social network, link prediction, granular computing, type-2 fuzzy sets

Procedia PDF Downloads 322

Authors: Zahra Ali Lawan, Ali Abdulhakim

Abstract:

The stomach contents of 100 Oreochromis niloticus, sampled between April and August, 2011 in Alau Lake, northeastern Nigeria, were examined. Herbs and algae were the main contents representing 40.15%, 23.36% followed by some mud / sand components, insect parts and fish remains representing 14.60%, 13.87% and 8.03% respectively. Oreochromis niloticus was affirmed as an herbivore and a benthic feeder due to the presence of both herbs and mud/sand among its stomach content. The mean stomach fullness percentage was 70.94% and stomach emptiness was 29.06%. The average condition factor of the fishes was 1.69 with the best conditions recorded in the dry months of April and May at 1.74 and 1.94 respectively. The general trend in the condition factor for this species in this study is that relatively higher condition factors were recorded for relatively higher lengths.

Keywords: stomach contents, oreochromis niloticus, herbivores, Lake Alau

Procedia PDF Downloads 381

Authors: Adnan F. Sheikh, Fayaz A. Mir

Abstract:

After the recent devastating flood in Kashmir in 2014, dredging of the local water bodies, especially Jhelum River has become a priority for the government. Local government under the project name of 'Comprehensive Flood Management Programme' plans to undertake an increase in discharge of existing flood channels by removal of encroachments and acquisition of additional land, dredging and other works of the water bodies. The total quantity of soil to be dredged will be 16.15 lac cumecs. Dredged soil is a major component that would result from the project which requires disposal/utilization. This study analyses the effect of cement and sand on the engineering properties of soil. The tests were conducted with variable additions of sand (10%, 20% and 30%), whereas cement was added at 12%. Samples with following compositions: soil-cement (12%) and soil-sand (30%) were tested as well. Laboratory experiments were conducted to determine the engineering characteristics of soil, i.e., compaction, strength, and CBR characteristics. The strength characteristics of the soil were determined by unconfined compressive strength test and direct shear test. Unconfined compressive strength of the soil was tested immediately and for a curing period of seven days. CBR test was performed for unsoaked, soaked (worst condition- 4 days) and cured (4 days) samples.

Keywords: comprehensive flood management programme, dredge soil, strength characteristics, flood

Procedia PDF Downloads 173

Authors: Yuguang Wang, Chuanjun Wang

Abstract:

At present, many coastal areas around the world suffer from seawater intrusion. Seawater intrusion is the superimposed result of two factors which are nature and human social economical activities in particular area. In recent years, due to excessive exploitation of groundwater, the seawater intrusion phenomenon aggravate in coastal zone of the Bohai and Huanghai seas in our country. Moreover, with sea-level rising, the original hydrodynamic equilibrium between saltwater and freshwater has been damaged to a certain extent, and it will further aggravate seawater intrusion in the land plains. In addition, overexploitation of groundwater declined groundwater level and increase saltwater intrusion in coastal areas. Therefore, in view of the sensitivity and vulnerability of the impact of sea-level rise in the future, the risk of sea-level rise in coastal zone should be considered, reasonable exploitation, utilization and management of coastal zone’s groundwater should be formulated. The response mechanism of sea-level rise should be studied to prevent and reduce the harm of seawater intrusion, which has important theoretical and realistic significances. In this paper, through the long-term monitoring of groundwater level and conductibility in the transition region of seawater intrusion for the sand coast area, realtimely master the situation of seawater intrusion. Combined with the seasonal exploitation station of groundwater and sea level variation, early alert the seawater intrusion to prevent and reduce the harm of seawater intrusion.

Keywords: groundwater level, sea level, seawater intrusion, sand coast

Procedia PDF Downloads 463

Authors: Gunasekaran Raja, Rajakumar Arul, Kottilingam Kottursamy, Ramkumar Jayaraman, Sathya Pavithra, Swaminathan Venkatraman

Abstract:

Wireless Interoperability for Microwave Access (WiMAX) utilizes the IEEE 802.1X mechanism for authentication. However, this mechanism incurs considerable delay during handoffs. This delay during handoffs results in service disruption which becomes a severe bottleneck. To overcome this delay, our article proposes a key caching mechanism based on user path prediction. If the user mobility follows that path, the user bypasses the normal IEEE 802.1X mechanism and establishes the necessary authentication keys directly. Through analytical and simulation modeling, we have proved that our mechanism effectively decreases the handoff delay thereby achieving fast authentication.

Keywords: authentication, authorization, and accounting (AAA), handoff, mobile, user path prediction (UPP) and user pattern

Procedia PDF Downloads 399

Authors: Hasan Şahan Arel

Abstract:

In this study, literature related to the replacement of cement with waste marble and the use of waste marble as an aggregate in concrete production was examined. Workability of the concrete decreased when marble powder was used as a substitute for fine aggregate. Marble powder contributed to the compressive strength of concrete because of the CaCO₃ and SiO₂ present in the chemical structure of the marble. Additionally, the use of marble pieces in place of coarse aggregate revealed that this contributed to the workability and mechanical properties of the concrete. When natural standard sand was replaced with marble dust at a ratio of 15% and 75%, the compressive strength and splitting tensile strength of the concrete increased by 20%-26% and 10%-15%, respectively. However, coarse marble aggregates exhibited the best performance at a 100% replacement ratio. Additionally, there was a greater improvement in the mechanical properties of concrete when waste marble was used in a coarse aggregate form when compared to that of when marble was used in a dust form. If the cement was replaced with marble powder in proportions of 20% or more, then adverse effects were observed on the compressive strength and workability of the concrete. This study indicated that marble dust at a cement-replacement ratio of 5%-10% affected the mechanical properties of concrete by decreasing the global annual CO₂ emissions by 12% and also lowering the costs from US$40/m³ to US$33/m³.

Keywords: cement production, concrete, CO2 emission, marble, mechanical properties

Procedia PDF Downloads 314

Authors: Ashot Navasardian, Mariam Vardanian, Vladik Vardanian

Abstract:

The photovoltaic and the semiconductor industries are in growth and it is necessary to supply a large amount of silicon to maintain this growth. Since silicon is still the best material for the manufacturing of solar cells and semiconductor components so the pure silicon like solar grade and semiconductor grade materials are demanded. There are two main routes for silicon production: metallurgical and chemical. In this article, we reviewed the electrotecnological installations and systems for semiconductor manufacturing. The main task is to design the installation which can produce SOG Silicon from river sand by one work unit.

Keywords: metallurgical grade silicon, solar grade silicon, impurity, refining, plasma

Procedia PDF Downloads 489

Authors: Kiyoumars Roushangar, Saeid Sadaghian

Abstract:

Although accurate sediment load prediction is very important in planning, designing, operating and maintenance of water resources structures, the transport mechanism is complex, and the deterministic transport models are based on simplifying assumptions often lead to large prediction errors. In this research, firstly, two intelligent ANN methods, Radial Basis and General Regression Neural Networks, are adopted to model of total sediment load transport into Madani Dam reservoir (north of Iran) using the measured data and then applicability of the sediment transport methods developed by Engelund and Hansen, Ackers and White, Yang, and Toffaleti for predicting of sediment load discharge are evaluated. Based on comparison of the results, it is found that the GRNN model gives better estimates than the sediment rating curve and mentioned classic methods.

Keywords: sediment transport, dam reservoir, RBF, GRNN, prediction

Procedia PDF Downloads 494

Authors: Ahmed M. Eltohamy

Abstract:

In this paper, an experimental and numerical study was adopted to investigate the effect geogrid soil reinforcement pre-stressing on the pressure settlement relation of sand bed supporting a strip foundation. The studied parameters include foundation depth and pre-stress ratio for the cases of one and two pre-stressed reinforcement layers. The study reflected that pre-stressing of soil reinforcement resulted in a marked enhancement in reinforced bed soil stiffness compared to the reinforced soil without pre-stress. The best benefit of pre-stressing reinforcement was obtained as the overburden pressure and pre-straining ratio increase. Pre-stressing of double reinforcement topmost layers results in further enhancement of stress strain relation of bed soil.

Keywords: geogrid reinforcement, prestress, strip footing, bearing capacity

Procedia PDF Downloads 302