Search results for: hydraulic data

Authors: Eng. M. Ahmed, A. Ibrahim, M. Ashour

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One of the major concerns facing dam is the repair of their structures to prevent the seepage under them. In previous years, many existing dams have been treated by grouting, but with varying degrees of success. One of the major reasons for this erratic performance is the unsuitable selection of the grouting materials to reduce the seepage. Grouting is an effective way to improve the engineering properties of the soil and strengthen of the permeability of the soil to reduce the seepage. The purpose of this paper is to focus on the efficiency of current available grouting materials and techniques from construction, environmental and economical point of view. The seepage reduction usually accomplished by either chemical grouting or cementious grouting using ultrafine cement. In addition, the study shows a comparison between grouting materials according to their degree of permeability reduction and cost. The application of seepage reduction is based on the permeation grouting using grout curtain installation. The computer program (SEEP/W) is employed to model a dam rested on sandy soil, using grout curtain to reduce seepage quantity and hydraulic gradient by different grouting materials. This study presents a relationship that takes into account the permeability of the soil, grout curtain spacing and a new performance parameter that can be used to predict the best selection of grouting materials for seepage reduction.

Keywords: seepage, sandy soil, grouting, permeability

Procedia PDF Downloads 351

Authors: Celal Dudak, Aslı Utku, Burak Yağlioğlu

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Uninterrupted and continuous satellite communication through the whole orbit time is becoming more indispensable every day. Data relay systems are developed and built for various high/low data rate information exchanges like TDRSS of USA and EDRSS of Europe. In these missions, a couple of task-dedicated communication satellites exist. In this regard, for Turkey a data relay system is attempted to be defined exchanging low data rate information (i.e. TTC) for Earth-observing LEO satellites appointing commercial GEO communication satellites all over the world. First, justification of this attempt is given, demonstrating duration enhancements in the link. Discussion of preference of RF communication is, also, given instead of laser communication. Then, preferred communication GEOs – including TURKSAT4A already belonging to Turkey- are given, together with the coverage enhancements through STK simulations and the corresponding link budget. Also, a block diagram of the communication system is given on the LEO satellite.

Keywords: communication, GEO satellite, data relay system, coverage

Procedia PDF Downloads 426

Authors: Jayesh Mahitkar, V. K. Singh, Surendra Singh Kachhwaha

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Wire Mesh Heat Pipe (WMHP) as an effective component of thermal control system in the payload of spacecraft, utilizing ammonia to transfer efficient amount of heat. One dimensional generic and robust mathematical model with partial-analytical hydraulic approach (PAHA) is developed to study inside behaviour of WMHP. In this model, inside performance during operation is investigated like mass flow rate, and velocity along the wire mesh as well as vapour core is modeled respectively. This numerical model investigate heat flow along length, pressure drop along wire mesh as well as vapour line in axial direction. Furthermore, WMHP is modeled into equivalent resistance network such that total thermal resistance of heat pipe, temperature drop across evaporator end and condenser end is evaluated. This numerical investigation should be carried out for single layer and double layer wire mesh each with heat input at evaporator section is 10W, 20 W and 30 W at condenser temperature maintained at 20˚C.

Keywords: ammonia, heat transfer, modeling, wire mesh

Procedia PDF Downloads 268

Authors: Tanawat Hongthai, Dusit Thanapatay

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This paper presents the development of encrypted near field communication (NFC) data exchange format transmission in an NFC passive tag for the feasibility of implementing a genuine product authentication. We propose a research encryption and checking the genuine product into four major categories; concept, infrastructure, development and applications. This result shows the passive NFC-forum Type 2 tag can be configured to be compatible with the NFC data exchange format (NDEF), which can be automatically partially data updated when there is NFC field.

Keywords: near field communication, NFC data exchange format, checking the genuine product, encrypted NFC

Procedia PDF Downloads 265

Authors: Yung Gi Wu

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With the growing of computer and network, digital data can be spread to anywhere in the world quickly. In addition, digital data can also be copied or tampered easily so that the security issue becomes an important topic in the protection of digital data. Digital watermark is a method to protect the ownership of digital data. Embedding the watermark will influence the quality certainly. In this paper, Vector Quantization (VQ) is used to embed the watermark into the image to fulfill the goal of data hiding. This kind of watermarking is invisible which means that the users will not conscious the existing of embedded watermark even though the embedded image has tiny difference compared to the original image. Meanwhile, VQ needs a lot of computation burden so that we adopt a fast VQ encoding scheme by partial distortion searching (PDS) and mean approximation scheme to speed up the data hiding process. The watermarks we hide to the image could be gray, bi-level and color images. Texts are also can be regarded as watermark to embed. In order to test the robustness of the system, we adopt Photoshop to fulfill sharpen, cropping and altering to check if the extracted watermark is still recognizable. Experimental results demonstrate that the proposed system can resist the above three kinds of tampering in general cases.

Keywords: data hiding, vector quantization, watermark, color image

Procedia PDF Downloads 350

Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: anomaly detection, autoencoder, data centers, deep learning

Procedia PDF Downloads 181

Authors: Hossein Agheshlui, Stephan Matthai

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In fractured rock masses open fractures tend to act as the main pathways of fluid flow. The permeability of a rock fracture depends on its aperture. The change of aperture with stress can cause a many-orders-of-magnitude change in the hydraulic conductivity at moderate compressive stress levels. In this study, the change of aperture in fragmented rocks is investigated using finite element analysis. A full 3D mechanical model of a simplified version of an outcrop analog is created and studied. A constant initial aperture value is applied to all fractures. Different far field stresses are applied and the change of aperture is monitored considering the block to block interaction. The fragmented rock layer is assumed to be sandwiched between softer layers. Frictional contact forces are defined at the layer boundaries as well as among contacting rock blocks. For a given in situ stress, the blocks slide and contact each other, resulting in new aperture distributions. A map of changed aperture is produced after applying the in situ stress and compared to the initial apertures. Subsequently, the permeability of the system before and after the stress application is compared.

Keywords: fractured rocks, mechanical model, aperture change due to stress, frictional interface

Procedia PDF Downloads 406

Authors: A. Ghadbane, M. N. Bouaziz, S. Hanini, B. Baggoura, M. Abbaci

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The spacer grids are used to fix the rods bundle in a nuclear reactor core also act as turbulence-enhancing devices to improve the heat transfer from the hot surfaces of the rods to the surrounding coolant stream. Therefore, the investigation of thermal-hydraulic characteristics inside the rod bundles is important for optima design and safety operation of a nuclear reactor power plant. This contribution presents a feasibility study to use the ribbed spacer grids as mixing devices. The present study evaluates the effects of different ribbed spacer grids configurations on flow pattern and heat transfer in the downstream of the mixing devices in a 2 x 2 rod bundle array. This is done by obtaining velocity and pressure fields, turbulent intensity and the heat transfer coefficient using a three-dimensional CFD analysis. Numerical calculations are performed by employing K-ε turbulent model. The computational results obtained are promising and the comparison with standard spacer grids shows a clear difference which required the experimental approach to validate.

Keywords: PWR fuel assembly, spacer grid, mixing vane, swirl flow, turbulent heat transfer, CFD

Procedia PDF Downloads 480

Authors: Pavel H. Llamocca, Victoria Lopez

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The main objective of our work is the comparative analysis of environmental data from Open Data bases, belonging to different governments. This means that you have to integrate data from various different sources. Nowadays, many governments have the intention of publishing thousands of data sets for people and organizations to use them. In this way, the quantity of applications based on Open Data is increasing. However each government has its own procedures to publish its data, and it causes a variety of formats of data sets because there are no international standards to specify the formats of the data sets from Open Data bases. Due to this variety of formats, we must build a data integration process that is able to put together all kind of formats. There are some software tools developed in order to give support to the integration process, e.g. Data Tamer, Data Wrangler. The problem with these tools is that they need data scientist interaction to take part in the integration process as a final step. In our case we don’t want to depend on a data scientist, because environmental data are usually similar and these processes can be automated by programming. The main idea of our tool is to build Hadoop procedures adapted to data sources per each government in order to achieve an automated integration. Our work focus in environment data like temperature, energy consumption, air quality, solar radiation, speeds of wind, etc. Since 2 years, the government of Madrid is publishing its Open Data bases relative to environment indicators in real time. In the same way, other governments have published Open Data sets relative to the environment (like Andalucia or Bilbao). But all of those data sets have different formats and our solution is able to integrate all of them, furthermore it allows the user to make and visualize some analysis over the real-time data. Once the integration task is done, all the data from any government has the same format and the analysis process can be initiated in a computational better way. So the tool presented in this work has two goals: 1. Integration process; and 2. Graphic and analytic interface. As a first approach, the integration process was developed using Java and Oracle and the graphic and analytic interface with Java (jsp). However, in order to open our software tool, as second approach, we also developed an implementation with R language as mature open source technology. R is a really powerful open source programming language that allows us to process and analyze a huge amount of data with high performance. There are also some R libraries for the building of a graphic interface like shiny. A performance comparison between both implementations was made and no significant differences were found. In addition, our work provides with an Official Real-Time Integrated Data Set about Environment Data in Spain to any developer in order that they can build their own applications.

Keywords: open data, R language, data integration, environmental data

Procedia PDF Downloads 301

Authors: Sepideh Beiramipour, Hadi Haghjouei, Kourosh Qaderi, Majid Rahimpour, Mohammad M. Ahmadi, Sameh A. Kantoush

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Reservoir sedimentation is one of the main challenges by which the reservoir behind the dam is filled with sediments transferred through the river flow. Pressure flushing method is an effective way to drain the deposited sediments of the reservoirs through the bottom outlet. So far, several structural methods have been proposed to increase the efficiency of pressure flushing. The aim of this study is to increase the performance of Dendritic Bottomless Extended (DBE) structure on the efficiency of pressurized sediment flushing using submerged vanes. For this purpose, the physical model of the dam reservoir with dimensions of 7.5 m in length, 3.5 m in width, and 1.8 m in height in the hydraulic and water structures research laboratory of Shahid Bahonar University of Kerman was used. In order to investigate the influence of submerged vanes on the performance of DBE structure in pressure flushing, the best arrangement and geometric parameters of the vanes were selected and combined with the DBE structure. The results showed that the submerged vanes significantly increased the performance of the DBE structure so that the volume of the sediment flushing cone with the combination of two structures increased by 3.7 times compared to the DBE structure test.

Keywords: dendritic bottomless extended structure, flushing efficiency, sedimentation, sediment flushing

Procedia PDF Downloads 206

Authors: Zahid Ullah, Atlas Khan

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The rapid growth of data in various domains has created a pressing need for effective methods to transform this data into meaningful knowledge. In this era of big data, mathematical and statistical innovations play a crucial role in unlocking insights and facilitating informed decision-making in data analytics. This abstract aims to explore the transformative potential of these innovations and their impact on converting raw data into actionable knowledge. Drawing upon a comprehensive review of existing literature, this research investigates the cutting-edge mathematical and statistical techniques that enable the conversion of data into knowledge. By evaluating their underlying principles, strengths, and limitations, we aim to identify the most promising innovations in data analytics. To demonstrate the practical applications of these innovations, real-world datasets will be utilized through case studies or simulations. This empirical approach will showcase how mathematical and statistical innovations can extract patterns, trends, and insights from complex data, enabling evidence-based decision-making across diverse domains. Furthermore, a comparative analysis will be conducted to assess the performance, scalability, interpretability, and adaptability of different innovations. By benchmarking against established techniques, we aim to validate the effectiveness and superiority of the proposed mathematical and statistical innovations in data analytics. Ethical considerations surrounding data analytics, such as privacy, security, bias, and fairness, will be addressed throughout the research. Guidelines and best practices will be developed to ensure the responsible and ethical use of mathematical and statistical innovations in data analytics. The expected contributions of this research include advancements in mathematical and statistical sciences, improved data analysis techniques, enhanced decision-making processes, and practical implications for industries and policymakers. The outcomes will guide the adoption and implementation of mathematical and statistical innovations, empowering stakeholders to transform data into actionable knowledge and drive meaningful outcomes.

Keywords: data analytics, mathematical innovations, knowledge extraction, decision-making

Procedia PDF Downloads 62

Authors: Lu Si, Jie Yu, Shasha Li, Jun Ma, Lei Luo, Qingbo Wu, Yongqi Ma, Zhengji Liu

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Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rule, we propose a large data sets instance selection method with MapReduce framework. Besides ensuring the prediction accuracy and reduction rate, it has two desirable properties: First, it reduces the work load in the aggregation node; Second and most important, it produces the same result with the sequential version, which other parallel methods cannot achieve. We evaluate the performance of FCNN-MR on one small data set and two large data sets. The experimental results show that it is effective and practical.

Keywords: instance selection, data reduction, MapReduce, kNN

Procedia PDF Downloads 243

Authors: Trevor Toy, Josef Langerman

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Around a quarter of the world’s data is generated by financial with an estimated 708.5 billion global non-cash transactions reached between 2018 and. And with Open Banking still a rapidly developing concept within the financial industry, there is an opportunity to create a secure mechanism for connecting its stakeholders to openly, legitimately and consensually share the data required to enable it. Integration and data sharing of anonymised transactional data are still operated in silos and centralised between the large corporate entities in the ecosystem that have the resources to do so. Smaller fintechs generating data and businesses looking to consume data are largely excluded from the process. Therefore there is a growing demand for accessible transactional data for analytical purposes and also to support the rapid global adoption of Open Banking. The following research has provided a solution framework that aims to provide a secure decentralised marketplace for 1.) data providers to list their transactional data, 2.) data consumers to find and access that data, and 3.) data subjects (the individuals making the transactions that generate the data) to manage and sell the data that relates to themselves. The platform also provides an integrated system for downstream transactional-related data from merchants, enriching the data product available to build a comprehensive view of a data subject’s spending habits. A robust and sustainable data market can be developed by providing a more accessible mechanism for data producers to monetise their data investments and encouraging data subjects to share their data through the same financial incentives. At the centre of the platform is the market mechanism that connects the data providers and their data subjects to the data consumers. This core component of the platform is developed on a decentralised blockchain contract with a market layer that manages transaction, user, pricing, payment, tagging, contract, control, and lineage features that pertain to the user interactions on the platform. One of the platform’s key features is enabling the participation and management of personal data by the individuals from whom the data is being generated. This framework developed a proof-of-concept on the Etheruem blockchain base where an individual can securely manage access to their own personal data and that individual’s identifiable relationship to the card-based transaction data provided by financial institutions. This gives data consumers access to a complete view of transactional spending behaviour in correlation to key demographic information. This platform solution can ultimately support the growth, prosperity, and development of economies, businesses, communities, and individuals by providing accessible and relevant transactional data for big data analytics and open banking.

Keywords: big data markets, open banking, blockchain, personal data management

Procedia PDF Downloads 63

Authors: Rahman Davtalab

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Florida is one of the most vulnerable states to natural disasters among the 50 states of the USA. The state exposed by tropical storms, hurricanes, storm surge, landslide, etc. Besides, the mentioned natural phenomena, global warming, sea-level rise, and other anthropogenic environmental changes make a very complicated and unpredictable system for decision-makers. In this study, we tried to highlight the effects of climate change and sea-level rise on surface water and groundwater systems for three different geographical locations in Florida; Main Canal of Jacksonville Beach (in the northeast of Florida adjacent to the Atlantic Ocean), Grace Lake in central Florida, far away from surrounded coastal line, and Mc Dill in Florida and adjacent to Tampa Bay and Mexican Gulf. An integrated hydrologic and hydraulic model was developed and simulated for all three cases, including surface water, groundwater, or a combination of both. For the case study of Main Canal-Jacksonville Beach, the investigation showed that a 76 cm sea-level rise in time horizon 2060 could increase the flow velocity of the tide cycle for the main canal's outlet and headwater. This case also revealed how the sea level rise could change the tide duration, potentially affecting the coastal ecosystem. As expected, sea-level rise can raise the groundwater level. Therefore, for the Mc Dill case, the effect of groundwater rise on soil storage and the performance of stormwater retention ponds is investigated. The study showed that sea-level rise increased the pond’s seasonal high water up to 40 cm by time horizon 2060. The reliability of the retention pond is dropped from 99% for the current condition to 54% for the future. The results also proved that the retention pond could not retain and infiltrate the designed treatment volume within 72 hours, which is a significant indication of increasing pollutants in the future. Grace Lake case study investigates the effects of climate change on groundwater recharge. This study showed that using the dynamically downscaled data of the groundwater recharge can decline up to 24% by the mid-21st century.

Keywords: groundwater, surface water, Florida, retention pond, tide, sea level rise

Procedia PDF Downloads 173

Authors: Dmitriy Kuptsov

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Tree data structures, such as binary or in general k-ary trees, are essential in computer science. The applications of these data structures can range from data search and retrieval to sorting and ranking algorithms. Naive implementations of these data structures can consume prohibitively large volumes of random access memory limiting their applicability in certain solutions. Thus, in these cases, more advanced representation of these data structures is essential. In this paper we present the design of the compact version of ternary tree data structure and demonstrate the results for the experimental evaluation using static dictionary problem. We compare these results with the results for binary and regular ternary trees. The conducted evaluation study shows that our design, in the best case, consumes up to 12 times less memory (for the dictionary used in our experimental evaluation) than a regular ternary tree and in certain configuration shows performance comparable to regular ternary trees. We have evaluated the performance of the algorithms using both 32 and 64 bit operating systems.

Keywords: algorithms, data structures, succinct ternary tree, per- formance evaluation

Procedia PDF Downloads 152

Authors: Samia Rabet, Rachida Chemini, Gerhard Schäfer, Farid Aiouache

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The textile industry generates large quantities of wastewater, which poses significant environmental problems due to its complex composition and high levels of pollutants loaded principally with heavy metals, large amounts of COD, and dye. Separation treatment methods are often known for their effectiveness in removing contaminants whereas membrane separation techniques are a promising process for the treatment of textile effluent due to their versatility, efficiency, and low energy requirements. This study focuses on the modeling and simulation of membrane separation technologies with a cross-flow filtration process for textile effluent treatment. It aims to explore the application of mathematical models and computational simulations using ASPEN Plus Software in the prediction of a complex and real effluent separation. The results demonstrate the effectiveness of modeling and simulation techniques in predicting pollutant removal efficiencies with a global deviation percentage of 1.83% between experimental and simulated results; membrane fouling behavior, and overall process performance (hydraulic resistance, membrane porosity) were also estimated and indicating that the membrane losses 10% of its efficiency after 40 min of working.

Keywords: membrane separation, ultrafiltration, textile effluent, modeling, simulation

Procedia PDF Downloads 44

Authors: Ahmed I. Alutabi, Naghmeh Dezhabad, Sudhakar Ganti

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Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%.

Keywords: machine learning, artificial intelligence, prediction, data center, resource allocation, green computing

Procedia PDF Downloads 99

Authors: Prabhakar C. Dhavale, Meenakshi M. Pawar

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In this paper, everyday tons of data is embedded on digital media or distributed over the internet. The data is so distributed that it can easily be replicated without error, putting the rights of their owners at risk. Even when encrypted for distribution, data can easily be decrypted and copied. One way to discourage illegal duplication is to insert information known as watermark, into potentially valuable data in such a way that it is impossible to separate the watermark from the data. These challenges motivated researchers to carry out intense research in the field of watermarking. A watermark is a form, image or text that is impressed onto paper, which provides evidence of its authenticity. Digital watermarking is an extension of the same concept. There are two types of watermarks visible watermark and invisible watermark. In this project, we have concentrated on implementing watermark in image. The main consideration for any watermarking scheme is its robustness to various attacks

Keywords: watermarking, digital, DCT-DWT, security

Procedia PDF Downloads 412

Authors: Neerav Kumar, Naumaan Nayyar, Sharath Kashyap

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Most companies see an increase in the adoption of machine learning (ML) applications across internal and external-facing use cases. ML applications vend output either in batch or real-time patterns. A complete batch ML pipeline architecture comprises data sourcing, feature engineering, model training, model deployment, model output vending into a data store for downstream application. Due to unclear role expectations, we have observed that scientists specializing in building and optimizing models are investing significant efforts into building the other components of the architecture, which we do not believe is the best use of scientists’ bandwidth. We propose a system architecture created using AWS services that bring industry best practices to managing the workflow and simplifies the process of model deployment and end-to-end data integration for an ML application. This narrows down the scope of scientists’ work to model building and refinement while specialized data engineers take over the deployment, pipeline orchestration, data quality, data permission system, etc. The pipeline infrastructure is built and deployed as code (using terraform, cdk, cloudformation, etc.) which makes it easy to replicate and/or extend the architecture to other models that are used in an organization.

Keywords: data pipeline, machine learning, AWS, architecture, batch machine learning

Procedia PDF Downloads 51

Authors: Cui Fu, Yi-Zhou Zhuang, Sheng-Zhi Wang

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Full scale tests of six micropiles with different predrilled-hole parameters under low frequency cyclic lateral loading in-sand were carried out using the MTS hydraulic loading system to analyze the seismic performance of micropiles. Hysteresis curves, skeleton curves, energy dissipation capacity and ductility of micropiles were investigated. The experimental results show the hysteresis curves appear like plump bows in the elastic–plastic stage and failure stage which exhibit good hysteretic characteristics without pinching phenomena and good energy dissipating capacities. The ductility coefficient varies from 2.51 to 3.54 and the depth and loose backfill of oversized holes can improve ductility, but the diameter of predrilled-hole has a limited effect on enhancing its ductility. These findings and conclusions could make contribution to the practical application of the semi-integral abutment bridges and provide a reference for the predrilled oversized hole technology in integral abutment bridges.

Keywords: ductility, energy dissipation capacity, micropile with predrilled oversized hole, seismic performance, semi-integral abutment bridge

Procedia PDF Downloads 424

Authors: André Smith, Amr Abdel-Dayem

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The stereo matching problem, while having been present for several decades, continues to be an active area of research. The goal of this research is to find correspondences between elements found in a set of stereoscopic images. With these pairings, it is possible to infer the distance of objects within a scene, relative to the observer. Advancements in this field have led to experimentations with various techniques, from graph-cut energy minimization to artificial neural networks. At the basis of these techniques is a cost function, which is used to evaluate the likelihood of a particular match between points in each image. While at its core, the cost is based on comparing the image pixel data; there is a general lack of consistency as to what image data representation to use. This paper presents an experimental analysis to compare the effectiveness of more common image data representations. The goal is to determine the effectiveness of these data representations to reduce the cost for the correct correspondence relative to other possible matches.

Keywords: colour data, local stereo matching, stereo correspondence, disparity map

Procedia PDF Downloads 359

Authors: Mokhtar Nikgoo

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Definition of Concrete and Concreting: Concrete (in French: Béton) in a broad sense is any substance or combination that consists of a sticky substance with the property of cementation. In general, concrete refers to concrete made by Portland cement, which is produced by mixing fine and coarse aggregates, Portland cement and water. After enough time, this mixture turns into a stone-like substance. During the hardening or processing of the concrete, cement is chemically combined with water to form strong crystals that bind the aggregates together, a process called hydration. During this process, significant heat is released called hydration heat. Additionally, concrete shrinks slightly, especially as excess water evaporates, a phenomenon known as drying shrinkage. The process of hardening and the gradual increase in concrete strength that occurs with it does not end suddenly unless it is artificially interrupted. Instead, it decreases more over long periods of time, although, in practical applications, concrete is usually set after 28 days and is considered at full design strength. Concrete may be made from different types of cement as well as pozzolans, furnace slag, additives, additives, polymers, fibers, etc. It may also be used in the way it is made, heating, water vapor, autoclave, vacuum, hydraulic pressures and various condensers.

Keywords: concrete, RCC, batching, cement, Pozzolan, mixing plan

Procedia PDF Downloads 83

Authors: Karima Qayumi, Alex Norta

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The rapid generation of high volume and a broad variety of data from the application of new technologies pose challenges for the generation of business-intelligence. Most organizations and business owners need to extract data from multiple sources and apply analytical methods for the purposes of developing their business. Therefore, the recently decentralized data management environment is relying on a distributed computing paradigm. While data are stored in highly distributed systems, the implementation of distributed data-mining techniques is a challenge. The aim of this technique is to gather knowledge from every domain and all the datasets stemming from distributed resources. As agent technologies offer significant contributions for managing the complexity of distributed systems, we consider this for next-generation data-mining processes. To demonstrate agent-based business intelligence operations, we use agent-oriented modeling techniques to develop a new artifact for mining massive datasets.

Keywords: agent-oriented modeling (AOM), business intelligence model (BIM), distributed data mining (DDM), multi-agent system (MAS)

Procedia PDF Downloads 419

Authors: Qing K. Zhu

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Very Large Scale Integration (VLSI) design becomes very complex due to the continuous integration of millions of gates in one chip based on Moore’s law. Designers have encountered numerous report files during design iterations using timing and noise analysis tools. This paper presented our work using data mining techniques combined with HTML tables to extract and represent critical timing/noise data. When we apply this data-mining tool in real applications, the running speed is important. The software employs table look-up techniques in the programming for the reasonable running speed based on performance testing results. We added several advanced features for the application in one industry chip design.

Keywords: VLSI design, data mining, big data, HTML forms, web, VLSI, EDA, timing, noise

Procedia PDF Downloads 240

Authors: Anuruddha Jagoda, Samiddhi Samarakoon, Anil Jasinghe

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In its simplest form, data quality can be defined as 'fitness for use' and it is a concept with multi-dimensions. Emergency Departments(ED) require information to treat patients and on the other hand it is the primary source of information regarding accidents, injuries, emergencies etc. Also, it is the starting point of various patient registries, databases and surveillance systems. This interventional study was carried out to improve data quality at the ED of the National Hospital of Sri Lanka (NHSL) by introducing an e health solution to improve data quality. The NHSL is the premier trauma care centre in Sri Lanka. The study consisted of three components. A research study was conducted to assess the quality of data in relation to selected five dimensions of data quality namely accuracy, completeness, timeliness, legibility and reliability. The intervention was to develop and deploy an electronic emergency department information system (eEDIS). Post assessment of the intervention confirmed that all five dimensions of data quality had improved. The most significant improvements are noticed in accuracy and timeliness dimensions.

Keywords: electronic health records, electronic emergency department information system, emergency department, data quality

Procedia PDF Downloads 260

Authors: Basma Khelfa, Antoine Tordeux, Ibrahima Ba

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We present a descriptive analysis data of lane-changing events in multi-lane roads. The data are provided from The Highway Drone Dataset (HighD), which are microscopic trajectories in highway. This paper describes and analyses the role of the different parameters and their significance. Thanks to HighD data, we aim to find the most frequent reasons that motivate drivers to change lanes. We used the programming language R for the processing of these data. We analyze the involvement and relationship of different variables of each parameter of the ego vehicle and the four vehicles surrounding it, i.e., distance, speed difference, time gap, and acceleration. This was studied according to the class of the vehicle (car or truck), and according to the maneuver it undertook (overtaking or falling back).

Keywords: autonomous driving, physical traffic model, prediction model, statistical learning process

Procedia PDF Downloads 246

Authors: Shoukat Ali, Abdul Qadir Jandga, Amjad Hussain

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Objective: The main purpose of this study is to compare the Percent Depth dose (PDD) and In-plane and cross-plane profiles of Varian Golden beam data to the measured data of 6 and 18 MV photons for the commissioning of Eclipse treatment planning system. Introduction: Commissioning of treatment planning system requires an extensive acquisition of beam data for the clinical use of linear accelerators. Accurate dose delivery require to enter the PDDs, Profiles and dose rate tables for open and wedges fields into treatment planning system, enabling to calculate the MUs and dose distribution. Varian offers a generic set of beam data as a reference data, however not recommend for clinical use. In this study, we compared the generic beam data with the measured beam data to evaluate the reliability of generic beam data to be used for the clinical purpose. Methods and Material: PDDs and Profiles of Open and Wedge fields for different field sizes and at different depths measured as per Varian’s algorithm commissioning guideline. The measurement performed with PTW 3D-scanning water phantom with semi-flex ion chamber and MEPHYSTO software. The online available Varian Golden Beam Data compared with the measured data to evaluate the accuracy of the golden beam data to be used for the commissioning of Eclipse treatment planning system. Results: The deviation between measured vs. golden beam data was in the range of 2% max. In PDDs, the deviation increases more in the deeper depths than the shallower depths. Similarly, profiles have the same trend of increasing deviation at large field sizes and increasing depths. Conclusion: Study shows that the percentage deviation between measured and golden beam data is within the acceptable tolerance and therefore can be used for the commissioning process; however, verification of small subset of acquired data with the golden beam data should be mandatory before clinical use.

Keywords: percent depth dose, flatness, symmetry, golden beam data

Procedia PDF Downloads 479

Authors: Selvakumar Ulaganathan, Ivo Couckuyt, Francesco Ferranti, Tom Dhaene, Eric Laermans

Abstract:

Variable-fidelity surrogate modelling offers an efficient way to approximate function data available in multiple degrees of accuracy each with varying computational cost. In this paper, a Kriging-based variable-fidelity surrogate modelling approach is introduced to approximate such deterministic data. Initially, individual Kriging surrogate models, which are enhanced with gradient data of different degrees of accuracy, are constructed. Then these Gradient enhanced Kriging surrogate models are strategically coupled using a recursive CoKriging formulation to provide an accurate surrogate model for the highest fidelity data. While, intuitively, gradient data is useful to enhance the accuracy of surrogate models, the primary motivation behind this work is to investigate if it is also worthwhile incorporating gradient data of varying degrees of accuracy.

Keywords: Kriging, CoKriging, Surrogate modelling, Variable- fidelity modelling, Gradients

Procedia PDF Downloads 541

Authors: Xiaoyan Dai, Hsieh Yisan

Abstract:

Barcode processing of captured images is a huge challenge, as different shooting conditions can result in different barcode appearances. This paper proposes a deep learning-based barcode detection using synthetic-to-real data augmentation. We first augment barcodes themselves; we then augment images containing the barcodes to generate a large variety of data that is close to the actual shooting environments. Comparisons with previous works and evaluations with our original data show that this approach achieves state-of-the-art performance in various real images. In addition, the system uses hybrid resolution for barcode “scan” and is applicable to real-time applications.

Keywords: barcode detection, data augmentation, deep learning, image-based processing

Procedia PDF Downloads 151

Authors: Haon-Yao Chen, Cheng-Fang Lin, Pui-Kwan Andy Hong, Ping-Yi Yang, Kok Kwang Ng, Sheng-Fu Yang

Abstract:

Simultaneous nitrification and denitrification (SND) are a natural phenomenon in the soil environment that can be applied in wastewater treatment. At a domestic wastewater treatment plant, we performed a pilot test of installing bioplates with entrapped biomass into a conventional aeration basin for SND, and investigated the effects of bioplate packing ratio, hydraulic retention time, dissolved oxygen level, on/off aeration mode, and supplemental carbon and alkalinity on nitrogen removal. With the pilot aeration basin of 1.3 m3 loaded with mixed liquor suspended solids of 1500-2500 mg/L and bioplates at PR of 3.2% (3.2% basin volume) operated at HRT of 6 h and DO of 4-6 mg/L without supplemental carbon or alkalinity, nitrogen in the wastewater was removed to an effluent total nitrogen (TN) of 7.3 mg/L from an influent TN of 28 mg/L. The bioplate robust cellulose triacetate structure carrying the biomass shows promise in retrofitting conventional aeration basins for enhanced nutrient removal.

Keywords: immobilization, nitrification/denitrification, nutrient removal, total nitrogen

Procedia PDF Downloads 638