Search results for: Large Wind Turbine

Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

Abstract:

As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms.

Keywords: resource scheduling, deep reinforcement learning, distributed system, artificial intelligence

Procedia PDF Downloads 111

Authors: Seyedtaghi Mirmohammadi, Jamshid Yazdani, Syavash Etemadi Nejad

Abstract:

One of the main indoor air parameters in classrooms is dust pollution and it depends on the particle size and exposure duration. However, there is a lake of data about the exposure level to PM2.5 concentrations in rural area classrooms. The objective of the current study was exposure assessment for PM2.5 for students in the classrooms. One year monitoring was carried out for fifteen schools by time-series sampling to evaluate the indoor air PM2.5 in the rural district of Sari city, Iran. A hygrometer and thermometer were used to measure some psychrometric parameters (temperature, relative humidity, and wind speed) and Real-Time Dust Monitor, (MicroDust Pro, Casella, UK) was used to monitor particulate matters (PM2.5) concentration. The results show the mean indoor PM2.5 concentration in the studied classrooms was 135µg/m3. The regression model indicated that a positive correlation between indoor PM2.5 concentration and relative humidity, also with distance from city center and classroom size. Meanwhile, the regression model revealed that the indoor PM2.5 concentration, the relative humidity, and dry bulb temperature was significant at 0.05, 0.035, and 0.05 levels, respectively. A statistical predictive model was obtained from multiple regressions modeling for indoor PM2.5 concentration and indoor psychrometric parameters conditions.

Keywords: classrooms, concentration, humidity, particulate matters, regression

Procedia PDF Downloads 335

Authors: T. Nishido, S. Fukumoto

Abstract:

The functions of movable bearings decline due to corrosion and sediments. As the result, they cannot move or rotate according to the behaviors of girders. Because of the constraints, the bending moments are generated by the horizontal reaction forces and the heights of girders. Under these conditions, the authors obtained the following results by analysis and experiment. Tensile stresses due to the moments occurred at temperature fluctuations. The large tensile stresses on concrete slabs around the bearings caused cracks. Even if concrete slabs are newly replaced, cracks will come out again with function declined bearings. The functional declines of bearings are generally found by using displacement gauges. However the method is not suitable for long-term measurements. We focused on the change in the strains at the bearings and the lower flanges near them at temperature fluctuations. It was found that their strains were particularly large when the movements of the bearings were constrained. Therefore, we developed a long-term health monitoring wireless system with FBG (Fiber Bragg Grating) sensors which were attached to bearings and lower flanges. The FBG sensors have the characteristics such as non-electrical influence, resistance to weather, and high strain sensitivity. Such characteristics are suitable for long-term measurements. The monitoring system was inexpensive because it was limited to the purpose of measuring strains and temperature. Engineers can monitor the behaviors of bearings in real time with the wireless system. If an office is away from bridge sites, the system will save traveling time and cost.

Keywords: bridge bearing, concrete slab, 　FBG sensor, health monitoring

Procedia PDF Downloads 221

Authors: Rahul Paliwal, Gulshan Maheshwari, Anant S. Jhaveri, Channamallikarjun S. Mathpati

Abstract:

Large pumping facility is the necessary requirement of the cooling water systems for power plants, process and manufacturing facilities, flood control and water or waste water treatment plant. With a large capacity of few hundred to 50,000 m3/hr, cares must be taken to ensure the uniform flow to the pump to limit vibration, flow induced cavitation and performance problems due to formation of air entrained vortex and swirl flow. Successful prediction of these phenomena requires numerical method and turbulence model to characterize the dynamics of these flows. In the past years, single phase shear stress transport (SST) Reynolds averaged Navier Stokes Models (like k-ε, k-ω and RSM) were used to predict the behavior of flow. Literature study showed that two phase model will be more accurate over single phase model. In this paper, a 3D geometries simulated using detached eddy simulation (LES) is used to predict the behavior of the fluid and the results are compared with experimental results. Effect of different grid structure and boundary condition is also studied. It is observed that two phase flow model can more accurately predict the mean flow and turbulence statistics compared to the steady SST model. These validate model will be used for further analysis of vortex structure in lab scale model to generate their frequency-plot and intensity at different location in the set-up. This study will help in minimizing the ill effect of vortex on pump performance.

Keywords: grid structure, pump intake, simulation, vibration, vortex

Procedia PDF Downloads 175

Authors: Kanzumba Kusakana

Abstract:

The Democratic Republic of Congo (DRC) is currently experiencing a general energy crisis due to lack of proper investment and management in the energy sector. 93, 6% of the country is highly dependent on wood fuels as main source of energy having severe impacts such as deforestation and general degradation of the environment. On the other hand, the major share of the electricity produced mainly from ill-conditioned hydro and thermal power stations is principally used to supply the industrial sector as well as very few urban areas. Nevertheless, DRC possesses huge potential in renewable resources such as hydropower, biomass, methane gas, solar geothermal and moderate wind potential that can be used for energy generation. Recently the country has initiated projects to build decentralized micro hydropower station to supply remotes and isolated areas; to rehabilitate its existent main hydropower plants and transmission lines as well as to extend its current generation capacity by building new hydropower stations able to respond to a major part of the African continent energy needs. This paper presents a comprehensive review of current energy resources as well as of the electricity situation in DRC. Recent energy projects, the energy policy as well as the energy challenges in the DRC are also presented.

Keywords: energy, biomass, hydro power, renewable energy, energy policy, Democratic Republic of Congo

Procedia PDF Downloads 337

Authors: Xiaoxue Jin, Qiong Zhang

Abstract:

The rapid influx and ongoing flow of young migrants in large cities, alongside the emergence and evolution of new social media, have led to increased interpersonal alienation and weakened place attachment. In the interplay between individuals and space, urban public spaces play a pivotal role in meeting the multifaceted needs of individuals and fostering a sense of attachment. This article aims to investigate the relationship between the place characteristics of public spaces and individuals' needs and perceptions, with an aim to identify the factors influencing place attachment among the youth. This study is conducted in the Shekou community of Shenzhen, focusing on the youth residents to evaluate their place attachment levels and to analyze their perceptions of the place characteristics of selected public spaces. The influencing factors of public spaces on place attachment were sorted out through detailed data analysis. Research has found that rapid urbanization has led to spatial homogenization and spatial segregation caused by uneven resource distribution, which in turn diminishes the utilization of public spaces. The social characteristics of public spaces, such as the quality of social activities and spatial openness, are critical in forming place attachment. In this research, place characteristics impacting place attachment are categorized, aiming to reconstruct the characteristics of public space places and use them as a medium to explore the place attachment of young people, promote their independent creation and participation in public life, and enhance the dynamism between individuals and spaces.

Keywords: place attachment, place characteristics, public spaces, spatial perception

Procedia PDF Downloads 48

Authors: Alexandra Papagianni, George Filis, Panagiotis Papadopoulos

Abstract:

The liberalization of the energy market and the increasing penetration of fluctuating renewables (e.g., wind and solar power) have heightened the importance of the spot market for ensuring efficient electricity supply. This is further emphasized by the EU’s goal of achieving net-zero emissions by 2050. The day-ahead market (DAM) plays a key role in European energy trading, accounting for 80-90% of spot transactions and providing critical insights for next-day pricing. Therefore, short-term electricity price forecasting (EPF) within the DAM is crucial for market participants to make informed decisions and improve their market positioning. Existing literature highlights out-of-sample performance as a key factor in assessing EPF accuracy, with influencing factors such as predictors, forecast horizon, model selection, and strategy. Several studies indicate that electricity demand is a primary price determinant, while renewable energy sources (RES) like wind and solar significantly impact price dynamics, often lowering prices. Additionally, incorporating data from neighboring countries, due to market coupling, further improves forecast accuracy. Most studies predict up to 24 steps ahead using hourly data, while some extend forecasts using higher-frequency data (e.g., half-hourly or quarter-hourly). Short-term EPF methods fall into two main categories: statistical and computational intelligence (CI) methods, with hybrid models combining both. While many studies use advanced statistical methods, particularly through different versions of traditional AR-type models, others apply computational techniques such as artificial neural networks (ANNs) and support vector machines (SVMs). Recent research combines multiple methods to enhance forecasting performance. Despite extensive research on EPF accuracy, a gap remains in understanding how forecasting strategy affects prediction outcomes. While iterated strategies are commonly used, they are often chosen without justification. This paper contributes by examining whether the choice of forecasting strategy impacts the quality of day-ahead price predictions, especially for multi-step forecasts. We evaluate both iterated and direct methods, exploring alternative ways of conducting iterated forecasts on benchmark and state-of-the-art forecasting frameworks. The goal is to assess whether these factors should be considered by end-users to improve forecast quality. We focus on the Greek DAM using data from July 1, 2021, to March 31, 2022. This period is chosen due to significant price volatility in Greece, driven by its dependence on natural gas and limited interconnection capacity with larger European grids. The analysis covers two phases: pre-conflict (January 1, 2022, to February 23, 2022) and post-conflict (February 24, 2022, to March 31, 2022), following the Russian-Ukraine conflict that initiated an energy crisis. We use the mean absolute percentage error (MAPE) and symmetric mean absolute percentage error (sMAPE) for evaluation, as well as the Direction of Change (DoC) measure to assess the accuracy of price movement predictions. Our findings suggest that forecasters need to apply all strategies across different horizons and models. Different strategies may be required for different horizons to optimize both accuracy and directional predictions, ensuring more reliable forecasts.

Keywords: short-term electricity price forecast, forecast strategies, forecast horizons, recursive strategy, direct strategy

Procedia PDF Downloads 8

Authors: Marielcio Lacerda, Angelo Paulino, Elcio Shiguemori, Alvaro Damiao, Lamartine Guimaraes, Camila Anjos

Abstract:

Accurate information about the terrain is extremely important in disaster management activities or conflict. This paper proposes the use of the Unmanned Aircraft Systems (UAS) at the identification of Airdrop Zones (AZs) and Helicopter Landing Zones (HLZs). In this paper we consider the AZs the zones where troops or supplies are dropped by parachute, and HLZs areas where victims can be rescued. The use of digital image processing enables the automatic generation of an orthorectified mosaic and an actual Digital Surface Model (DSM). This methodology allows obtaining this fundamental information to the terrain’s comprehension post-disaster in a short amount of time and with good accuracy. In order to get the identification and classification of AZs and HLZs images from DJI drone, model Phantom 4 have been used. The images were obtained with the knowledge and authorization of the responsible sectors and were duly registered in the control agencies. The flight was performed on May 24, 2017, and approximately 1,300 images were obtained during approximately 1 hour of flight. Afterward, new attributes were generated by Feature Extraction (FE) from the original images. The use of multispectral images and complementary attributes generated independently from them increases the accuracy of classification. The attributes of this work include the Declivity Map and Principal Component Analysis (PCA). For the classification four distinct classes were considered: HLZ 1 – small size (18m x 18m); HLZ 2 – medium size (23m x 23m); HLZ 3 – large size (28m x 28m); AZ (100m x 100m). The Decision Tree method Random Forest (RF) was used in this work. RF is a classification method that uses a large collection of de-correlated decision trees. Different random sets of samples are used as sampled objects. The results of classification from each tree and for each object is called a class vote. The resulting classification is decided by a majority of class votes. In this case, we used 200 trees for the execution of RF in the software WEKA 3.8. The classification result was visualized on QGIS Desktop 2.12.3. Through the methodology used, it was possible to classify in the study area: 6 areas as HLZ 1, 6 areas as HLZ 2, 4 areas as HLZ 3; and 2 areas as AZ. It should be noted that an area classified as AZ covers the classifications of the other classes, and may be used as AZ, HLZ of large size (HLZ3), medium size (HLZ2) and small size helicopters (HLZ1). Likewise, an area classified as HLZ for large rotary wing aircraft (HLZ3) covers the smaller area classifications, and so on. It was concluded that images obtained through small UAV are of great use in calamity situations since they can provide data with high accuracy, with low cost, low risk and ease and agility in obtaining aerial photographs. This allows the generation, in a short time, of information about the features of the terrain in order to serve as an important decision support tool.

Keywords: disaster management, unmanned aircraft systems, helicopter landing zones, airdrop zones, random forest

Procedia PDF Downloads 177

Authors: Lin Dong-Yih, Yang S. M., Huang B. W., Lian J. A.

Abstract:

Super duplex stainless steel has excellent mechanical properties and corrosion resistance. It becomes important structural material as its application has been extended to the fields such as renewable energy and the chemical industry because of its excellent properties. As examples are offshore wind power, solar cell machinery, and pipes in the chemical industry. The mechanical properties and corrosion resistance of super duplex stainless steel can be eliminated by welding due to the precipitation of the hard and brittle σ phase, which is rich of chromium, and molybdenum elements. This paper studies the influence of carbon element on the phase transformation of -ferrite and σ phase in 2507 super duplex stainless steel. The 2507 will be under argon gas protection welded with 316 and 316L extra low carbon stainless steel separately. The microstructural phases of stainless steels before and after welding, in fusion, heat affected zones, and base material will be studied via X-ray, OM, SEM, EPMA i.e. their quantity, size, distribution, and morphology. The influences of diffusion by carbon element will be compared according to the microstructures, hardness, and corrosion tests.

Keywords: complex stainless steel, welding, phase formation, carbon element, sigma phase, delta ferrite

Procedia PDF Downloads 99

Authors: Sujata Upgupta, Prasoon Kumar Singh

Abstract:

The expansion of large scale coal mining into forest areas is a potential hazard for the local biodiversity and wildlife. The objective of this study is to provide a picture of the threat that coal mining poses to the forests of the East Bokaro landscape. The vulnerable forest areas at risk have been assessed and the priority areas for conservation have been presented. The forested areas at risk in the current scenario have been assessed and compared with the past conditions using classification and buffer based overlay approach. Forest vulnerability has been assessed using an analytical framework based on systematic indicators and composite vulnerability index values. The results indicate that more than 4 km² of forests have been lost from 1973 to 2016. Large patches of forests have been diverted for coal mining projects. Forests in the northern part of the coal field within 1-3 km radius around the coal mines are at immediate risk. The original contiguous forests have been converted into fragmented and degraded forest patches. Most of the collieries are located within or very close to the forests thus threatening the biodiversity and hydrology of the surrounding regions. Based on the vulnerability values estimated, it was concluded that more than 90% of the forested grids in East Bokaro are highly vulnerable to mining. The forests in the sub-districts of Bermo and Chandrapura have been identified as the most vulnerable to coal mining activities. This case study would add to the capacity of the forest managers and mine managers to address the risk and vulnerability of forests at a small landscape level in order to achieve sustainable development.

Keywords: forest, coal mining, indicators, vulnerability

Procedia PDF Downloads 390

Authors: E. Al-Essa, R. Bello-Mendoza, D. G. Wareham

Abstract:

Anaerobic batch experiments were conducted to investigate the effect of magnetite-supplementation (7 mM) on methane production from digested sludge undergoing two different microbial growth phases, namely fresh sludge (exponential growth phase) and degassed sludge (endogenous decay phase). Three different particle sizes were assessed: small (50 - 150 nm), medium (168 – 490 nm) and large (800 nm - 4.5 µm) particles. Results show that, in the case of the fresh sludge, magnetite significantly enhanced the methane production rate (up to 32%) and reduced the lag phase (by 15% - 41%) as compared to the control, regardless of the particle size used. However, the cumulative methane produced at the end of the incubation was comparable in all treatment and control bottles. In the case of the degassed sludge, only the medium-sized magnetite particles increased significantly the methane production rate (12% higher) as compared to the control. Small and large particles had little effect on the methane production rate but did result in an extended lag phase which led to significantly lower cumulative methane production at the end of the incubation period. These results suggest that magnetite produces a clear and positive effect on methane production only when an active and balanced microbial community is present in the anaerobic digester. It is concluded that, (i) the effect of magnetite particle size on increasing the methane production rate and reducing lag phase duration is strongly influenced by the initial metabolic state of the microbial consortium, and (ii) the particle size would positively affect the methane production if it is provided within the nanometer size range.

Keywords: anaerobic digestion, iron oxide, methanogenesis, nanoparticle

Procedia PDF Downloads 140

Authors: Nosheen Fatima Warraich

Abstract:

One of the most often used models in information system (IS) research is the technology acceptance model (TAM). This meta-analysis aims to measure the relationship between TAM variables, Perceived Ease of Use (PEOU), and Perceived Usefulness (PU) with users’ attitudes and behavioral intention (BI) in mobile and digital libraries context. It also examines the relationship of external variables (information quality and system quality) with TAM variables (PEOU and PU) in digital libraries settings. This meta-analysis was performed through PRISMA-P guidelines. Four databases (Google Scholar, Web of Science, Scopus, and LISTA) were utilized for searching, and the search was conducted according to defined criteria. The findings of this study revealed a large effect size of PU and PEOU with BI. There was also a large effect size of PU and PEOU with attitude. A medium effect size was found between SysQ -> PU, InfoQ-> PU, and SysQ -> PEOU. However, there was a small effect size between InfoQ and PEOU. It fills the literature gap and also confirms that TAM is a valid model for the acceptance and use of technology in mobile and digital libraries context. Thus, its findings would be helpful for developers and designers in designing and developing mobile library apps. It will also be beneficial for library authorities and system librarians in designing and developing digital libraries in academic settings.

Keywords: technology acceptance model (tam), perceived ease of use, perceived usefulness, information quality, system quality, meta-analysis, systematic review, digital libraries, and mobile library apps.

Procedia PDF Downloads 74

Authors: Chung-Yuan Huang, Yu-Hsiang Fu, Chuen-Tsai Sun

Abstract:

Community detection represents an important data-mining tool for analyzing and understanding real-world complex network structures and functions. We believe that at least four criteria determine the appropriateness of a community detection algorithm: (a) it produces useable normalized mutual information (NMI) and modularity results for social networks, (b) it overcomes resolution limitation problems associated with synthetic networks, (c) it produces good NMI results and performance efficiency for Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks, and (d) it produces good modularity and performance efficiency for large-scale real-world complex networks. To our knowledge, no existing community detection algorithm meets all four criteria. In this paper, we describe a simple hierarchical arc-merging (HAM) algorithm that uses network topologies and rule-based arc-merging strategies to identify community structures that satisfy the criteria. We used five well-studied social network datasets and eight sets of LFR benchmark networks to validate the ground-truth community correctness of HAM, eight large-scale real-world complex networks to measure its performance efficiency, and two synthetic networks to determine its susceptibility to resolution limitation problems. Our results indicate that the proposed HAM algorithm is capable of providing satisfactory performance efficiency and that HAM-identified communities were close to ground-truth communities in social and LFR benchmark networks while overcoming resolution limitation problems.

Keywords: complex network, social network, community detection, network hierarchy

Procedia PDF Downloads 227

Authors: Oibar Martinez, Clara Oliver

Abstract:

The Cherenkov Telescope Array Project (CTA) aims to build two different observatories of Cherenkov Telescopes, located in Cerro del Paranal, Chile, and La Palma, Spain. These facilities are used in this paper as a case study to investigate how to apply standard Directives on Electromagnetic Compatibility to astronomical observatories. Cherenkov Telescopes are able to provide valuable information from both Galactic and Extragalactic sources by measuring Cherenkov radiation, which is produced by particles which travel faster than light in the atmosphere. The construction requirements demand compliance with the European Electromagnetic Compatibility Directive. The largest telescopes of these observatories, called Large Scale Telescopes (LSTs), are high precision instruments with advanced photomultipliers able to detect the faint sub-nanosecond blue light pulses produced by Cherenkov Radiation. They have a 23-meter parabolic reflective surface. This surface focuses the radiation on a camera composed of an array of high-speed photosensors which are highly sensitive to the radio spectrum pollution. The camera has a field of view of about 4.5 degrees and has been designed for maximum compactness and lowest weight, cost and power consumption. Each pixel incorporates a photo-sensor able to discriminate single photons and the corresponding readout electronics. The first LST is already commissioned and intends to be operated as a service to Scientific Community. Because of this, it must comply with a series of reliability and functional requirements and must have a Conformité Européen (CE) marking. This demands compliance with Directive 2014/30/EU on electromagnetic compatibility. The main difficulty of accomplishing this goal resides on the fact that Conformité Européen marking setups and procedures were implemented for industrial products, whereas no clear protocols have been defined for scientific installations. In this paper, we aim to give an answer to the question on how the directive should be applied to our installation to guarantee the fulfillment of all the requirements and the proper functioning of the telescope itself. Experts in Optics and Electromagnetism were both needed to make these kinds of decisions and match tests which were designed to be made over the equipment of limited dimensions on large scientific plants. An analysis of the elements and configurations most likely to be affected by external interferences and those that are most likely to cause the maximum disturbances was also performed. Obtaining the Conformité Européen mark requires knowing what the harmonized standards are and how the elaboration of the specific requirement is defined. For this type of large installations, one needs to adapt and develop the tests to be carried out. In addition, throughout this process, certification entities and notified bodies play a key role in preparing and agreeing the required technical documentation. We have focused our attention mostly on the technical aspects of each point. We believe that this contribution will be of interest for other scientists involved in applying industrial quality assurance standards to large scientific plant.

Keywords: CE marking, electromagnetic compatibility, european directive, scientific installations

Procedia PDF Downloads 110

Authors: Dhruvit S. Berawala, Jann R. Ursin, Obrad Slijepcevic

Abstract:

Shale gas is one of the most rapidly growing forms of natural gas. Unconventional natural gas deposits are difficult to characterize overall, but in general are often lower in resource concentration and dispersed over large areas. Moreover, gas is densely packed into the matrix through adsorption which accounts for large volume of gas reserves. Gas production from tight shale deposits are made possible by extensive and deep well fracturing which contacts large fractions of the formation. The conventional reservoir modelling and production forecasting methods, which rely on fluid-flow processes dominated by viscous forces, have proved to be very pessimistic and inaccurate. This paper presents a new approach to forecast shale gas production by detailed modeling of gas desorption, diffusion and non-linear flow mechanisms in combination with statistical representation of these processes. The representation of the model involves a cube as a porous media where free gas is present and a sphere (SiC: Sphere in Cube model) inside it where gas is adsorbed on to the kerogen or organic matter. Further, the sphere is considered consisting of many layers of adsorbed gas in an onion-like structure. With pressure decline, the gas desorbs first from the outer most layer of sphere causing decrease in its molecular concentration. The new available surface area and change in concentration triggers the diffusion of gas from kerogen. The process continues until all the gas present internally diffuses out of the kerogen, gets adsorbs onto available surface area and then desorbs into the nanopores and micro-fractures in the cube. Each SiC idealizes a gas pathway and is characterized by sphere diameter and length of the cube. The diameter allows to model gas storage, diffusion and desorption; the cube length takes into account the pathway for flow in nanopores and micro-fractures. Many of these representative but general cells of the reservoir are put together and linked to a well or hydraulic fracture. The paper quantitatively describes these processes as well as clarifies the geological conditions under which a successful shale gas production could be expected. A numerical model has been derived which is then compiled on FORTRAN to develop a simulator for the production of shale gas by considering the spheres as a source term in each of the grid blocks. By applying SiC to field data, we demonstrate that the model provides an effective way to quickly access gas production rates from shale formations. We also examine the effect of model input properties on gas production.

Keywords: adsorption, diffusion, non-linear flow, shale gas production

Procedia PDF Downloads 165

Authors: H. Abbasi, K. Sennah

Abstract:

A Structural Insulated Panel (SIP) is a structural element contains of foam insulation core sandwiched between two oriented-strand boards (OSB), plywood boards, steel sheets or fibre cement boards. Superior insulation, exceptional strength and fast insulation are the specifications of a SIP-based structure. There are also many other benefits such as less total construction costs, speed of construction, less expensive HVAC equipment required, favourable energy-efficient mortgages comparing to wood-framed houses. This paper presents the experimental analysis on selected foam-timber SIPs to study their structural behaviour when used as walls in residential construction under lateral loading. The experimental program has also taken several stud panels in order to compare the performance of SIP with conventional wood-frame system. The results of lateral tests performed in this study established a database that can be used further to develop design tables of SIP wall subjected to lateral loading caused by wind or earthquake. A design table for walls subjected to lateral loading was developed. Experimental results proved that the tested SIPs are ‘as good as’ the conventional wood-frame system.

Keywords: structural insulated panel, experimental study, lateral load, design tables

Procedia PDF Downloads 316

Authors: Kerryn Krige, Kerrin Myers

Abstract:

Social entrepreneurship offers the opportunity to simultaneously address both social and economic inequality in South Africa. Its appeal across racial groups, its attractiveness to young people, its applicability in rural and peri-urban markets, and its acceleration in middle income, large-business economies suits the South African context. However, the potential to deliver much-needed developmental benefits has not been realised because the social entrepreneurship debate lacks evidence as to who social entrepreneurs are, their goals and operations and the socio-economic results they achieve. As a result, policy development has been stunted, and legislative barriers and red tape remain. Social entrepreneurs are isolated from the mainstream economy, and struggle to access funding because of limitations in legislative and organisational structures. The objective of the study is to strengthen the ecosystem for social entrepreneurship in South Africa by producing robust, policy-rich information from and about social enterprises currently in operation across the country. The study employs a quantitative survey methodology, using online and telephonic data collection methods. A purposive sample of 1000 social enterprises was included in the first large-scale study of social entrepreneurship in South Africa. The results offer deep insight into the characteristics of social enterprises; the activities they undertake and the markets they serve; their modes of operation and funding sources as well as key challenges and support systems. The results contribute towards developing a model of social enterprise in the African context.

Keywords: social enterprise, key characteristics, challenges and enablers, towards an African model

Procedia PDF Downloads 307

Authors: Shalini Singh, Sanjay K. Srivastava, Govind, Mukhtar. A. Khan, P. K. Singh

Abstract:

Nanotechnology is revolutionizing the development of biosensors. Nanomaterials and nanofabrication technologies are increasingly being used to design novel biosensors. Sensitivity and other attributes of biosensors can be improved by using nanomaterials with unique chemical, physical, and mechanical properties in their construction. Silicon is a promising biomaterial that is non-toxic and biodegradable and can be exploited in chemical and biological sensing. Present study demonstrated the streptavidin–biotin interaction on silicon surfaces with different topographies such as flat and nanostructured silicon (nanowires) surfaces. Silicon nanowires with wide range of surface to volume ratio were prepared by electrochemical etching of silicon wafer. The large specific surface of silicon nanowires can be chemically modified to link different molecular probes (DNA strands, enzymes, proteins and so on), which recognize the target analytes, in order to enhance the selectivity and specificity of the sensor device. The interaction of streptavidin with biotin was carried out on 3-aminopropyltriethoxysilane (APTS) functionalized silicon surfaces. Fourier Transform Infrared Spectroscopy (FTIR) and X-ray Photoelectron Spectroscopy (XPS) studies have been performed to characterize the surface characteristics to ensure the protein attachment. Silicon nanowires showed the enhance protein attachment, as compared to flat silicon surface due to its large surface area and good molecular penetration to its surface. The methodology developed herein could be generalized to a wide range of protein-ligand interactions, since it is relatively easy to conjugate biotin with diverse biomolecules such as antibodies, enzymes, peptides, and nucleotides.

Keywords: FTIR, silicon nanowires, streptavidin-biotin, XPS

Procedia PDF Downloads 417

Authors: Reza Karimpour

Abstract:

Ports play a decisive role in the EU's external and internal trade, as about 74% of imports and exports and 37% of exchanges go through ports. Although ports, especially Deep Sea Shipping (DSS) ports, are integral nodes within multimodal logistic flows, Short Sea Shipping (SSS) and inland waterways are not so well integrated. The automated vessels and supply chain optimisations for sustainable shortsea shipping (MOSES) project aims to enhance the short sea shipping component of the European supply chain by addressing the vulnerabilities and strains related to the operation of large containerships. The MOSES concept can be shortly described as a large containership (mother-vessel) approaching a DSS port (or a large container terminal). Upon her arrival, a combined intelligent mega-system consisting of the MOSES Autonomous tugboat swarm for manoeuvring and the MOSES adapted AutoMoor system. Then, container handling processes are ready to start moving containers to their destination via hinterland connections (trucks and/or rail) or to be shipped to destinations near small ports (on the mainland or island). For the first case, containers are stored in a dedicated port area (Storage area), waiting to be moved via trucks and/or rail. For the second case, containers are stacked by existing port equipment near-dedicated berths of the DSS port. They then are loaded on the MOSES Innovative Feeder Vessel, equipped with the MOSES Robotic Container-Handling System that provides (semi-) autonomous (un) feeding of the feeder. The Robotic Container-Handling System is remotely monitored through a Shore Control Centre. When the MOSES innovative Feeder vessel approaches the small port, where her docking is achieved without tugboats, she automatically unloads the containers using the Robotic Container-Handling System on the quay or directly on trucks. As a result, ports with minimal or no available infrastructure may be effectively integrated with the container supply chain. Then, the MOSES innovative feeder vessel continues her voyage to the next small port, or she returns to the DSS port. MOSES exploitation activity mainly aims to exploit research outcomes beyond the project, facilitate utilisation of the pilot results by others, and continue the pilot service after the project ends. By the mid-lifetime of the project, the exploitation plan introduces the reader to the MOSES project and its key exploitable results. It provides a plan for delivering the MOSES innovations to the market as part of the overall exploitation plan.

Keywords: automated vessels, exploitation, shortsea shipping, supply chain

Procedia PDF Downloads 110

Authors: U. Datta

Abstract:

The main objective of this study is to find a suitable approach to monitor the land infrastructure growth over a period of time using multispectral satellite images. Bi-temporal change detection method is unable to indicate the continuous change occurring over a long period of time. To achieve this objective, the approach used here estimates a statistical model from series of multispectral image data over a long period of time, assuming there is no considerable change during that time period and then compare it with the multispectral image data obtained at a later time. The change is estimated pixel-wise. Statistical composite hypothesis technique is used for estimating pixel based change detection in a defined region. The generalized likelihood ratio test (GLRT) is used to detect the changed pixel from probabilistic estimated model of the corresponding pixel. The changed pixel is detected assuming that the images have been co-registered prior to estimation. To minimize error due to co-registration, 8-neighborhood pixels around the pixel under test are also considered. The multispectral images from Sentinel-2 and Landsat-8 from 2015 to 2018 are used for this purpose. There are different challenges in this method. First and foremost challenge is to get quite a large number of datasets for multivariate distribution modelling. A large number of images are always discarded due to cloud coverage. Due to imperfect modelling there will be high probability of false alarm. Overall conclusion that can be drawn from this work is that the probabilistic method described in this paper has given some promising results, which need to be pursued further.

Keywords: co-registration, GLRT, infrastructure growth, multispectral, multitemporal, pixel-based change detection

Procedia PDF Downloads 135

Authors: Hamidreza Ghazvinian, Khosro Ghazvinian, Touba Khodaiean

Abstract:

The importance of evaporation estimation in water resources and agricultural studies is undeniable. Pan evaporation are used as an indicator to determine the evaporation of lakes and reservoirs around the world due to the ease of interpreting its data. In this research, intelligent models were investigated in estimating pan evaporation on a daily basis. Shahroud and Mayamey were considered as the studied cities. These two cities are located in Semnan province in Iran. The mentioned cities have dry weather conditions that are susceptible to high evaporation potential. Meteorological data of 11 years of synoptic stations of Shahrood and Mayamey cities were used. The intelligent models used in this study are Artificial Neural Network (ANN), Least Squares Support Vector Machine (LSSVM), and M5 tree models. Meteorological parameters of minimum and maximum air temperature (Tmax, Tmin), wind speed (WS), sunshine hours (SH), air pressure (PA), relative humidity (RH) as selected input data and evaporation data from pan (EP) to The output data was considered. 70% of data is used at the education level, and 30 % of the data is used at the test level. Models used with explanation coefficient evaluation (R2) Root of Mean Squares Error (RMSE) and Mean Absolute Error (MAE). The results for the two Shahroud and Mayamey stations showed that the above three models' operations are rather appropriate.

Keywords: pan evaporation, intelligent methods, shahroud, mayamey

Procedia PDF Downloads 74

Authors: Julia Cristina Bonaldo, Christophe L. Martin, Severine Romero Baivier, Stephane Mazerat

Abstract:

Alumina refractories are commonly used in steel and foundry industries. These refractories are prepared through a powder metallurgy route. They are a mixture of hard alumina particles and graphite platelets embedded into a soft carbonic matrix (binder). The powder can be cold pressed isostatically or uniaxially, depending on the application. The compact is then fired to obtain the final product. The quality of the product is governed by the microstructure of the composite and by the process parameters. The compaction behavior and the mechanical properties of the fired product depend greatly on the amount of each phase, on their morphology and on the initial microstructure. In order to better understand the link between these parameters and the macroscopic behavior, we use the Discrete Element Method (DEM) to simulate the compaction process and the fracture behavior of the fired composite. These simulations are coupled with well-designed experiments. Four mixes with various amounts of Al₂O₃ and binder were tested both experimentally and numerically. In DEM, each particle is modelled and the interactions between particles are taken into account through appropriate contact or bonding laws. Here, we model a bimodal mixture of large Al₂O₃ and small Al₂O₃ covered with a soft binder. This composite is itself mixed with graphite platelets. X-ray tomography images are used to analyze the morphologies of the different components. Large Al₂O₃ particles and graphite platelets are modelled in DEM as sets of particles bonded together. The binder is modelled as a soft shell that covers both large and small Al₂O₃ particles. When two particles with binder indent each other, they first interact through this soft shell. Once a critical indentation is reached (towards the end of compaction), hard Al₂O₃ - Al₂O₃ contacts appear. In accordance with experimental data, DEM simulations show that the amount of Al₂O₃ and the amount of binder play a major role for the compaction behavior. The graphite platelets bend and break during the compaction, also contributing to the macroscopic stress. Firing step is modeled in DEM by ascribing bonds to particles which contact each other after compaction. The fracture behavior of the compacted mixture is also simulated and compared with experimental data. Both diametrical tests (Brazilian tests) and triaxial tests are carried out. Again, the link between the amount of Al₂O₃ particles and the fracture behavior is investigated. The methodology described here can be generalized to other particulate materials that are used in the ceramic industry.

Keywords: cold compaction, composites, discrete element method, refractory materials, x-ray tomography

Procedia PDF Downloads 138

Authors: Finn Lannon, Jenny Roth, Roland Deutsch, Eric Igou

Abstract:

The world continues to be rife with economic inequality, which has an impact on how people think and behaves in response to large and often growing gaps in wealth. Large gaps in earnings between groups within a particular organization, area or society can create tension between groups. Collective action tendencies (to protest, sign a petition, vote on behalf of an ingroup etc.) are also a growing phenomenon globally. Research shows that economic inequality promotes social processes such as appraisals of illegitimacy, which are recognized antecedents of collective action. This paper examines different types of collective action intentions among middle-status group members in response to economic inequality in two studies. Study 1 (N = 72) demonstrates a causal link between high economic inequality and collective action intentions of middle-status group members both to reduce inequality and to improve group status. A second pre-registered study (N = 432) examines key drivers of these relationships, including illegitimacy appraisals and direction of intergroup comparison. Adding to the current understanding of the topic, distinctions between the illegitimacy of one’s group status and the illegitimacy of societal inequality are found to mediate key relationships between economic inequality and relevant collective action types. The direction of intergroup comparison (upwards vs. downwards) is also shown to have a significant impact on collective action intentions to improve group status. Findings add to the understanding of the consequences of economic inequality and drivers of collective action intentions.

Keywords: economic inequality, collective action, legitimacy, social psychology

Procedia PDF Downloads 90

Authors: Maher Aburrous, Adel Khelifi, Manar Abu Talib

Abstract:

Transactions performed by financial institutions on daily basis require XML encryption on large scale. Encrypting large volume of message fully will result both performance and resource issues. In this paper a novel approach is presented for securing financial XML transactions using classification data mining (DM) algorithms. Our strategy defines the complete process of classifying XML transactions by using set of classification algorithms, classified XML documents processed at later stage using element-wise encryption. Classification algorithms were used to identify the XML transaction rules and factors in order to classify the message content fetching important elements within. We have implemented four classification algorithms to fetch the importance level value within each XML document. Classified content is processed using element-wise encryption for selected parts with "High", "Medium" or “Low” importance level values. Element-wise encryption is performed using AES symmetric encryption algorithm and proposed modified algorithm for AES to overcome the problem of computational overhead, in which substitute byte, shift row will remain as in the original AES while mix column operation is replaced by 128 permutation operation followed by add round key operation. An implementation has been conducted using data set fetched from e-banking service to present system functionality and efficiency. Results from our implementation showed a clear improvement in processing time encrypting XML documents.

Keywords: XML transaction, encryption, Advanced Encryption Standard (AES), XML classification, e-banking security, fuzzy classification, cryptography, intelligent encryption

Procedia PDF Downloads 411

Authors: Ja-Keoung Koo, Kensuke Nakamura, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Byung-Woo Hong

Abstract:

The machine learning techniques based on a convolutional neural network (CNN) have been actively developed and successfully applied to a variety of image analysis tasks including reconstruction, noise reduction, resolution enhancement, segmentation, motion estimation, object recognition. The classical visual information processing that ranges from low level tasks to high level ones has been widely developed in the deep learning framework. It is generally considered as a challenging problem to derive visual interpretation from high dimensional imagery data. A CNN is a class of feed-forward artificial neural network that usually consists of deep layers the connections of which are established by a series of non-linear operations. The CNN architecture is known to be shift invariant due to its shared weights and translation invariance characteristics. However, it is often computationally intractable to optimize the network in particular with a large number of convolution layers due to a large number of unknowns to be optimized with respect to the training set that is generally required to be large enough to effectively generalize the model under consideration. It is also necessary to limit the size of convolution kernels due to the computational expense despite of the recent development of effective parallel processing machinery, which leads to the use of the constantly small size of the convolution kernels throughout the deep CNN architecture. However, it is often desired to consider different scales in the analysis of visual features at different layers in the network. Thus, we propose a CNN model where different sizes of the convolution kernels are applied at each layer based on the random projection. We apply random filters with varying sizes and associate the filter responses with scalar weights that correspond to the standard deviation of the random filters. We are allowed to use large number of random filters with the cost of one scalar unknown for each filter. The computational cost in the back-propagation procedure does not increase with the larger size of the filters even though the additional computational cost is required in the computation of convolution in the feed-forward procedure. The use of random kernels with varying sizes allows to effectively analyze image features at multiple scales leading to a better generalization. The robustness and effectiveness of the proposed CNN based on random kernels are demonstrated by numerical experiments where the quantitative comparison of the well-known CNN architectures and our models that simply replace the convolution kernels with the random filters is performed. The experimental results indicate that our model achieves better performance with less number of unknown weights. The proposed algorithm has a high potential in the application of a variety of visual tasks based on the CNN framework. Acknowledgement—This work was supported by the MISP (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by IITP, and NRF-2014R1A2A1A11051941, NRF2017R1A2B4006023.

Keywords: deep learning, convolutional neural network, random kernel, random projection, dimensionality reduction, object recognition

Procedia PDF Downloads 290

Authors: Rouaz Idriss, Bourahla Nour-Eddine, Kahlouche Farah, Rafa Sid Ali

Abstract:

The stability of structures made of light-gauge steel depends highly on the contribution of Shear Wall Panel (SWP) systems under horizontal forces due to wind or earthquake loads. Steel plate sheathing is often used with these panels made of cold formed steel (CFS) to improve its shear strength. In order to predict the shear strength resistance, two methods are presented in this paper. In the first method, the steel plate sheathing is modeled with plats strip taking into account only the tension and compression force due to the horizontal load, where both track and stud are modeled according to the geometrical and mechanical characteristics of the specimen used in the experiments. The theoretical background and empirical formulations of this method are presented in this paper. However, the second method is based on a micro modeling of the cold formed steel Shear Wall Panel “CFS-SWP” using Abaqus software. A nonlinear analysis was carried out with an in-plan monotonic load. Finally, the comparison between these two methods shows that the micro modeling with Abaqus gives better prediction of shear resistance of SWP than strips method. However, the latter is easier and less time consuming than the micro modeling method.

Keywords: cold formed steel 'CFS', shear wall panel, strip method, finite elements

Procedia PDF Downloads 309

Authors: Almaz Negash, Dessie Tibebe, Marye Mulugeta, Yezbie Kassa

Abstract:

Large-scale textile industries use large amounts of toxic chemicals, which are very hazardous to human health and environmental sustainability. In this study, the removal of various dyes from effluents of textile industries using the electrocoagulation process was investigated. The studied dyes were Reactive Red 120 (RR-120), Basic Blue 3 (BB-3), and Basic Red 46 (BR-46), which were found in samples collected from effluents of three major textile factories in the Amhara region, Ethiopia. For maximum removal, the dye BB-3 required an acidic pH 3, RR120 basic pH 11, while BR-46 neutral pH 7 conditions. BB-3 required a longer treatment time of 80 min than BR46 and RR-120, which required 30 and 40 min, respectively. The best removal efficiency of 99.5%, 93.5%, and 96.3% was achieved for BR-46, BB-3, and RR-120, respectively, from synthetic wastewater containing 10 mg L1of each dye at an applied potential of 10 V. The method was applied to real textile wastewaters and 73.0 to 99.5% removal of the dyes was achieved, Indicating Electrocoagulation can be used as a simple, and reliable method for the treatment of real wastewater from textile industries. It is used as a potentially viable and inexpensive tool for the treatment of textile dyes. Analysis of the electrochemically generated sludge by X-ray Diffraction, Scanning Electron Microscope, and Fourier Transform Infrared Spectroscopy revealed the expected crystalline aluminum oxides (bayerite (Al(OH)3 diaspore (AlO(OH)) found in the sludge. The amorphous phase was also found in the floc. Textile industry owners should be aware of the impact of the discharge of effluents on the Ecosystem and should use the investigated electrocoagulation method for effluent treatment before discharging into the environment.

Keywords: electrocoagulation, aluminum electrodes, Basic Blue 3, Basic Red 46, Reactive Red 120, textile industry, wastewater

Procedia PDF Downloads 53

Authors: Hassan Parandvar, Mehrdad Farid

Abstract:

In this paper, a finite element modeling is presented for large amplitude vibration of functionally graded material (FGM) plates subjected to combined random pressure and thermal load. The material properties of the plates are assumed to vary continuously in the thickness direction by a simple power law distribution in terms of the volume fractions of the constituents. The material properties depend on the temperature whose distribution along the thickness can be expressed explicitly. The von Karman large deflection strain displacement and extended Hamilton's principle are used to obtain the governing system of equations of motion in structural node degrees of freedom (DOF) using finite element method. Three-node triangular Mindlin plate element with shear correction factor is used. The nonlinear equations of motion in structural degrees of freedom are reduced by using modal reduction method. The reduced equations of motion are solved numerically by 4th order Runge-Kutta scheme. In this study, the random pressure is generated using Monte Carlo method. The modeling is verified and the nonlinear dynamic response of FGM plates is studied for various values of volume fraction and sound pressure level under different thermal loads. Snap-through type behavior of FGM plates is studied too.

Keywords: nonlinear vibration, finite element method, functionally graded material (FGM) plates, snap-through, random vibration, thermal effect

Procedia PDF Downloads 262

Authors: O. E. Ogunjinmi, N. O. Olawore, L. A. Usman, S. O. Ogunjinmi

Abstract:

An essential oil is any concentrated, hydrophobic liquid containing volatile aroma compounds produced by plants. It has been established that several factors affect the component of the plants such as the texture of the soil, relative humidity, wind, and collection time. This study is aimed at investigating the effect of collection time on the chemical composition of this essential oil. Pulverized leaves (500 g) of Hoslundia opposite harvested in the morning (7 am) and afternoon (2 pm) of the same day were separately hydrodistilled using Clevenger apparatus to obtain the essential oils from the leaves. The leaf oils collected in the morning (7 am) and afternoon (2 pm) harvests yielded 0.54 and 0.65 %w/w respectively. Analysis of the leaf oil obtained in the morning, using gas chromatography (GC) and gas chromatography combined mass spectrometry (GC-MS) revealed the presence of twenty-three (23) compounds which made up 81.8% of the total oil while nineteen (19) compounds (93.2%) were identified in the afternoon leaf essential oil. The most abundant components of the leaf oil collected in the morning (7 am) harvest were p-cymene (28.7%), sabinene (7.1%) and 1,8-cineole (6.6%) Meanwhile the major components of leaf oil in the afternoon (2 pm) harvest were p-cymene (26.4%), thymol (15.3%), 1,8-cineole (15.0%) and g-terpinene (10.4%). The composition pattern of leaf oil obtained in the morning and afternoon harvests of Hoslundia opposite revealed significant differences in qualitative and quantitative.

Keywords: essential oil, Hoslundia opposita, para cymene, 1, 8-cineole

Procedia PDF Downloads 391

Authors: Mayuva Youngsabanant, Chanikarn Srinark, Supanyika Sengsai, Soratorn Kerdkriangkrai, Nongnuch Gumlungpat, Mayuree Pumipaiboon

Abstract:

The follicular fluid proteins of healthy medium size follicles (4-6 mm in diameters) and large size follicles (7-8 mm in diameter) of large white pig ovaries were collected by using sterile technique. They were used for testing the effect on primary in vitro cell culture growth of porcine oviductal epithelial cells (pOEC). Porcine oviductal epithelial cells of luteal phase was culture in M199 and added with 10% fetal calf serum 2.2 mg/mL, NaHCO₃, 0.25 mM pyruvate, 15 µg/mL and 50 µg/mL, gentamycin sulfate at high humidified atmosphere with 5% CO₂ in 95% air atmosphere at 37°C for 96 h before testing. The optimized concentration of pFF of two follicle sizes (at concentration of 2, 4, 20, 40, 200, 400, 500, and 600 µg proteins) in culture medium was observed for 24 h using MTT assay. Results were analyzed with a one-way ANOVA in SPSS statistic. Moreover, pOEC was also studied in morphological characteristic on long-term culture. The results of long-term study revealed that pOEC showed 70-80 percentage of healthy morphology on epithelial-like character and contained 30 percentage of an elongated shape (fibroblast-like morphology) at 4 weeks of culture time. MTT assay reviewed an increase in the percentage of viability of pOEC in 2 treated of follicular fluid groups. Two treatment concentration groups were higher than control group (p < 0.05) but not in positive control group. Interestingly, at 200 µg protein of 2 treated follicular fluid groups were reached the highest cell viability which is higher than a positive control and it is significantly different form control group (P < 0.05). These cells are developed and had fibroblast elongate shape which is longer than the cells in control group and positive control group. This report implies that pFF of medium follicle size at 200 µg proteins and large follicle size at 200 and 500 µg proteins could be optimized concentration for using as a supplement in culture medium to promote cell growth and development instead of growth hormone from fetal calf serum. It could be applied in cell biotechnology researches. Acknowledgements: The project was funded by a grant from Silpakorn University Research and Development Institute (SURDI) and Faculty of Science, Silpakorn University, Thailand.

Keywords: in vitro, porcine follicular fluid protein (pFF), porcine oviductal epithelial cells (pOEC), MTT

Procedia PDF Downloads 145