Search results for: solar–climatic data

Authors: Fereshteh Pashaei Kamali, Elham Kazemi, Shokooh Neshani Fam

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The subject of sustainable development is a reformist revision of modernism and tradition, proposing reconciliatory strategies between these two. Sustainability in architecture cannot only be interpreted as the construction’s physical stability, but also as stability, the preserving of the continuous totality of earth and its energy resources as well, whose available resources and materials should be employed more efficiently. In other words, by referring to the building ecology, emphasizing the combinatory capacity of the building with the environmental factors (existence context), the aim of sustainability is to achieve spatial quality and comfort, as well as proper design in the architectural composition. To achieve these traditional Iranian architecture objectives, it is essential to plan on protecting the environment, maintaining aesthetic measures and responding to the needs of each climatic region. This study was conducted based on the descriptive-analytical method, and aimed to express the design patterns compatible with the climate of the Tabriz residential fabric. The present article attempts to express the techniques and patterns used in traditional Iranian architecture, especially the Tabriz Sharbatoglu houses and Ghadaki houses, which are supposed to be in accordance with modern concepts of sustainable architecture.

Keywords: sustainable architecture, climate, Tabriz, Sharbatoglu house, Ghadaki house

Procedia PDF Downloads 375

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 73

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 160

Authors: R. Rajeswari

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An investigation was carried out to know the SOC stock and its change over time in benchmark soils of different agroclimatic zones of Tamil Nadu. Roth.C model was used to assess SOC stock under existing and alternate cropping pattern. Soil map prepared on 1:50,000 scale from Natural Resources Information System (NRIS) employed under satellite data (IRS-1C/1D-PAN sharpened LISS-III image) was used to estimate SOC stock in different agroclimatic zones of Tamil Nadu. Fifteen benchmark soils were selected in different agroclimatic zones of Tamil Nadu based on their land use and the areal extent to assess SOC level and its change overtime. This revealed that, between eleven years of period (1997 - 2007). SOC buildup was higher in soils under horticulture system, followed by soils under rice cultivation. Among different agroclimatic zones of Tamil Nadu hilly zone have the highest SOC stock, followed by north eastern, southern, western, cauvery delta, north western, and high rainfall zone. Although organic carbon content in the soils of North eastern, southern, western, North western, Cauvery delta were less than high rainfall zone, the SOC stock was high. SOC density was higher in high rainfall and hilly zone than other agroclimatic zones of Tamil Nadu. Among low rainfall regions of Tamil Nadu cauvery delta zone recorded higher SOC density. Roth.C model was used to assess SOC stock under existing and alternate cropping pattern in viz., Periyanaickenpalayam series (western zone), Peelamedu series (southern zone), Vallam series (north eastern zone), Vannappatti series (north western zone) and Padugai series (cauvery delta zone). Padugai series recorded higher TOC, BIO, and HUM, followed by Periyanaickenpalayam series, Peelamedu series, Vallam series, and Vannappatti series. Vannappatti and Padugai series develop high TOC, BIO, and HUM under existing cropping pattern. Periyanaickenpalayam, Peelamedu, and Vallam series develop high TOC, BIO, and HUM under alternate cropping pattern. Among five selected soil series, Periyanaickenpalayam, Peelamedu, and Padugai series recorded 0.75 per cent TOC during 2025 and 2018, 2100 and 2035, 2013 and 2014 under existing and alternate cropping pattern, respectively.

Keywords: agro climatic zones, benchmark soil, land use, soil organic carbon

Procedia PDF Downloads 95

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 108

Authors: Somia Lakehal Ayat, Ibtissem Samai, Srara Lakehal Ayat, Chaima Dahmani

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The aim of this work relates to the physicochemical diversity and the characterization of the different types of soils of the edough massif (North East of Algeria) and to the evaluation and characterization of the existing organic matter as well as to the evolution. and the dynamics of the latter, also on its influence on changes in the physical properties of soils. In order to know the soil properties of seraidi forest, we established a stratified sampling plan. The results obtained show that we are in the presence of a great diversity of soils, such as neutral to alkaline, whose adsorbent complex is sufficiently saturated. Also, the presence of limestone offers the soil a fairly significant buffering capacity. In our study region, the texture of the soils is varied between clayey and silty, where it offers medium porosity, there is a strong accumulation of organic matter, therefore soils rich in organic matter.The fractionation of the organic matter of the soils allowed to obtain a very high rate of humification. The soil characteristics of the edough massif (North East of Algeria) are controlled by the contribution of organic matter, which presents a dynamic and an important evolution and which varies with the climatic conditions and the nature and the type of plant formation, and these the latter have a capital and important role in the rate of mineralization of organic matter.

Keywords: organic matter, soil, foresty, diversity, mineralization

Procedia PDF Downloads 89

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 422

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 63

Authors: José Neves, M. Rosário Martins, Fátima Candeias, Diana Ferreira, Sílvia Arantes, Júlio Cruz-Morais, Guida Gomes, Joaquim Macedo, António Abelha, Henrique Vicente

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Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

Keywords: artificial neuronal networks, essential oils, knowledge representation and reasoning, logic programming, Schinus molle L., Schinus terebinthifolius Raddi

Procedia PDF Downloads 544

Authors: Meryem Imane Babaghayou, Asma Abdelhafidi, Salem Fouad Chabira, Mohammed Sebaa

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A challenge of plastics industries is the realization of materials that resist the degradation in its application environment, and that to guarantee a longer life time therefore an optimal time of use. Blown extruded films of low-density polyethylene (LDPE) supplied by SABIC SAUDI ARABIA blown and extruded in SOFIPLAST company in Setif ALGERIA , have been subjected to climatic ageing in a sub-Saharan facility at Laghouat (Algeria) with direct exposure to sun. Samples were characterized by X-ray diffraction (XRD) and differential scanning calorimetry (DSC) techniques after prescribed amounts of time up to 8 months. It has been shown via these two techniques the impact of UV irradiation on the morphological development of a plastic material, especially the crystallinity degree which increases with exposure time. The reason of these morphological changes is related to photooxidative reactions leading to cross linking in the beginning and to chain scissions for an advanced stage of ageing this last ones are the first responsible. The crystallinity degree change is essentially controlled by the secondary crystallization of the amorphous chains whose mobility is enhanced by the chain scission processes. The diffusion of these short segments integrates the surface of the lamellae increasing in this way their thicknesses. The results presented highlight the complexity of the involved phenomena.

Keywords: Low Density poly (Ethylene), crystallinity, ageing, XRD, DSC

Procedia PDF Downloads 408

Authors: Gilbert O. Osayemwenre, Meyer L. Edson

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Ethylene vinyl acetate (EVA) encapsulation degradation affects the performance of photovoltaic (PV) module. Hotspot formation causes the EVA encapsulation to undergo photothermal deterioration and molecular breakdown by UV radiation. This leads to diffusion of chemical particles into other layers. During outdoor deployment, the EVA encapsulation in the affect region loses its adhesive strength, when this happen the affected region layer undergoes rapid delamination. The presence of photo-thermal degradation is detrimental to PV modules as it causes both optical and thermal degradation. Also, it enables the encapsulant to be more susceptible to chemicals substance and moisture. Our findings show a high concentration of Sodium, Phosphorus and Aluminium which originate from the glass substrate, cell emitter and back contact respectively.

Keywords: ethylene vinyl acetate (EVA), encapsulation, photo-thermal degradation, thermogravimetric analysis (TGA), scanning probe microscope (SPM)

Procedia PDF Downloads 306

Authors: Elissavet Feloni, Ioannis Kourtis, Konstantinos Kotsifakis, Evangelos Baltas

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Water inadequacy in small dry islands scattered in the Aegean Sea (Greece) is a major problem regarding Water Resources Management (WRM), especially during the summer period due to tourism. In the present work, various WRM schemes are designed and presented. The WRM schemes take into account current infrastructure and include Rainwater Harvesting tanks and Reverse Osmosis Desalination Units. The energy requirements are covered mainly by wind turbines and/or a seawater pumped storage system. Sizing is based on the available data for population and tourism per island, after taking into account a slight increase in the population (up to 1.5% per year), and it guarantees at least 80% reliability for the energy supply and 99.9% for potable water. Evaluation of scenarios is carried out from a financial perspective, after calculating the Life Cycle Cost (LCC) of each investment for a lifespan of 30 years. The wind-powered desalination plant was found to be the most cost-effective practice, from an economic point of view. Finally, in order to estimate the Climate Change (CC) impact, six different CC scenarios were investigated. The corresponding rate of on-grid versus off-grid energy required for ensuring the targeted reliability for the zero and each climatic scenario was investigated per island. The results revealed that under CC the grid-on energy required would increase and as a result, the reduction in wind turbines and seawater pumped storage systems’ reliability will be in the range of 4 to 44%. However, the range of this percentage change does not exceed 22% per island for all examined CC scenarios. Overall, CC is proposed to be incorporated into the design process for WRM-related projects. Acknowledgements: This research is co-financed by Greece and the European Union (European Social Fund - ESF) through the Operational Program «Human Resources Development, Education and Lifelong Learning 2014-2020» in the context of the project “Development of a combined rain harvesting and renewable energy-based system for covering domestic and agricultural water requirements in small dry Greek Islands” (MIS 5004775).

Keywords: small dry islands, water resources management, climate change, desalination, RES, seawater pumped storage system, rainwater harvesting

Procedia PDF Downloads 116

Authors: Valeria Piccioni, Matthias Leschok, Ina Cheibas, Illias Hischier, Benjamin Dillenburger, Arno Schlueter, Matthias Kohler, Fabio Gramazio

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The decarbonisation of the building sector requires the development of building components that provide energy efficiency while producing minimal environmental impact. Recent advancements in large-scale 3D printing have shown that it is possible to fabricate components with embedded performances that can be tuned for their specific application. We investigate the potential of polymer 3D printing for the fabrication of translucent facade components. In this study, we explore the effect of geometry on thermal insulation of printed cavity structures following a Hot Box test method. The experimental results are used to calibrate a finite-element simulation model which can support the informed design of 3D printed insulation structures. We show that it is possible to fabricate components providing thermal insulation ranging from 1.7 to 0.95 W/m2K only by changing the internal cavity distribution and size. Moreover, we identify design guidelines that can be used to fabricate components for different climatic conditions and thermal insulation requirements. The research conducted provides the first insights into the thermal behaviour of polymer 3DP facades on a large scale. These can be used as design guidelines for further research toward performant and low-embodied energy 3D printed facade components.

Keywords: 3D printing, thermal performance, polymers, facade components, hot-box method

Procedia PDF Downloads 181

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 370

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 432

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 254

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 274

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 261

Authors: N. Soli, B. Chaouachi, M. Bourouis

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We propose in this work the thermodynamic feasibility study of the operation of a refrigerating machine with absorption-diffusion with mixtures of hydrocarbons. It is for a refrigerating machine of low power (300 W) functioning on a level of temperature of the generator lower than 150 °C (fossil energy or solar energy) and operative with non-harmful fluids for the environment. According to this study, we determined to start from the digraphs of Oldham of the different binary of hydrocarbons, the minimal and maximum temperature of operation of the generator, as well as possible enrichment. The cooling medium in the condenser and absorber is done by the ambient air with a temperature at 35 °C. Helium is used as inert gas. The total pressure in the cycle is about 17.5 bars. We used suitable software to modulate for the two binary following the system propylene /butane and propylene/pentane. Our model is validated by comparison with the literature’s resultants.

Keywords: absorption, DAR cycle, diffusion, propyléne

Procedia PDF Downloads 274

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 489

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

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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 558

Authors: Xiaoyan Dai, Hsieh Yisan

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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 168

Authors: Naci Büyükkaracığan, Hasan Uzun

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Flood is the event which damage to the surrounding lands, residential places, infrastructure and vibrant, because of the streams overflow events from its bed for several reasons. Flood is a natural formation which develops due to its region's climatic conditions, technical and topographical characteristics. However, factors causing floods with global warming caused by human activity are events such as uncontrolled urbanization. Floods in Turkey are natural disasters which cause huge economic losses after the earthquake. At the same time, the flood disaster is one of the most observed hydrometeorological disasters, compared to 30%, in Turkey. Every year, there are around 200 flood-flood disasters and the disaster as a result of financial losses of $ 100 million per year are reported to occur in public institutions. The amount allocated for carrying out investment-project activities for reducing and controlling of flood damage control are around US $ 30 million per year. The existence of a linear increase in the number of flood disasters is noteworthy due to various reasons in the last 50 years of observation. In this study, first of all, big events of the flood in Turkey and their reasons were examined. And then, the information about the work to be done in order to prevent flooding by government was given with examples. Meteorological early warning systems, flood risk maps and regulation of urban development studies are described for this purpose. As a result, recommendations regarding in the event of the occurrence of floods disaster management were issues raised.

Keywords: flood, disaster, disaster management, Türkiye

Procedia PDF Downloads 329

Authors: Gyu-Dong Kim, Wuk-Jae Yoo, Sang-Youl Lee

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Composite structures offer numerous advantages over conventional structural systems in the form of higher specific stiffness and strength, lower life-cycle costs, and benefits such as easy installation and improved safety. Recently, there has been a considerable increase in the use of composites in engineering applications and as wraps for seismic upgrading and repairs. However, these composites deteriorate with time because of outdated materials, excessive use, repetitive loading, climatic conditions, manufacturing errors, and deficiencies in inspection methods. In particular, damaged fibers in a composite result in significant degradation of structural performance. In order to reduce the failure probability of composites in service, techniques to assess the condition of the composites to prevent continual growth of fiber damage are required. Condition assessment technology and nondestructive evaluation (NDE) techniques have provided various solutions for the safety of structures by means of detecting damage or defects from static or dynamic responses induced by external loading. A variety of techniques based on detecting the changes in static or dynamic behavior of isotropic structures has been developed in the last two decades. These methods, based on analytical approaches, are limited in their capabilities in dealing with complex systems, primarily because of their limitations in handling different loading and boundary conditions. Recently, investigators have introduced direct search methods based on metaheuristics techniques and artificial intelligence, such as genetic algorithms (GA), simulated annealing (SA) methods, and neural networks (NN), and have promisingly applied these methods to the field of structural identification. Among them, GAs attract our attention because they do not require a considerable amount of data in advance in dealing with complex problems and can make a global solution search possible as opposed to classical gradient-based optimization techniques. In this study, we propose an alternative damage-detection technique that can determine the degraded stiffness distribution of vibrating laminated composites made of Glass Fiber-reinforced Polymer (GFRP). The proposed method uses a modified form of the bivariate Gaussian distribution function to detect degraded stiffness characteristics. In addition, this study presents a method to detect the fiber property variation of laminated composite plates from the micromechanical point of view. The finite element model is used to study free vibrations of laminated composite plates for fiber stiffness degradation. In order to solve the inverse problem using the combined method, this study uses only first mode shapes in a structure for the measured frequency data. In particular, this study focuses on the effect of the interaction among various parameters, such as fiber angles, layup sequences, and damage distributions, on fiber-stiffness damage detection.

Keywords: stiffness detection, fiber damage, genetic algorithm, layup sequences

Procedia PDF Downloads 272

Authors: Abdullah Al Mamoon, Niels E. Joergensen, Ataur Rahman, Hassan Qasem

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Intergovernmental Panel for Climate Change (IPCC) in its fourth Assessment Report AR4 predicts a more extreme climate towards the end of the century, which is likely to impact the design of engineering infrastructure projects with a long design life. A recent study in 2013 developed new design rainfall for Qatar, which provides an improved design basis of drainage infrastructure for the State of Qatar under the current climate. The current design standards in Qatar do not consider increased rainfall intensity caused by climate change. The focus of this paper is to update recently developed design rainfalls in Qatar under the changing climatic conditions based on IPCC's AR4 allowing a later revision to the proposed design standards, relevant for projects with a longer design life. The future climate has been investigated based on the climate models released by IPCC’s AR4 and A2 story line of emission scenarios (SRES) using a stationary approach. Annual maximum series (AMS) of predicted 24 hours rainfall data for both wet (NCAR-CCSM) scenario and dry (CSIRO-MK3.5) scenario for the Qatari grid points in the climate models have been extracted for three periods, current climate 2010-2039, medium term climate (2040-2069) and end of century climate (2070-2099). A homogeneous region of the Qatari grid points has been formed and L-Moments based regional frequency approach is adopted to derive design rainfalls. The results indicate no significant changes in the design rainfall on the short term 2040-2069, but significant changes are expected towards the end of the century (2070-2099). New design rainfalls have been developed taking into account climate change for 2070-2099 scenario and by averaging results from the two scenarios. IPCC’s AR4 predicts that the rainfall intensity for a 5-year return period rain with duration of 1 to 2 hours will increase by 11% in 2070-2099 compared to current climate. Similarly, the rainfall intensity for more extreme rainfall, with a return period of 100 years and duration of 1 to 2 hours will increase by 71% in 2070-2099 compared to current climate. Infrastructure with a design life exceeding 60 years should add safety factors taking the predicted effects from climate change into due consideration.

Keywords: climate change, design rainfalls, IDF, Qatar

Procedia PDF Downloads 393

Authors: Jessica Vasil'chuk, Elena Ivanova, Pavel Krechetov, Vladimir Litvinsky, Nadine Budantseva, Julia Chizhova, Yurij Vasil'chuk

Abstract:

Carbonate minerals’ isotopic composition is widely used as a proxy for environmental parameters of the past. Pedogenic carbonate coatings on lower surfaces of coarse rock fragments are studied in order to indicate the climatic conditions and predominant vegetation under which they were formed. The purpose of the research is to characterize the isotopic composition of carbonate pedofeatures in soils of Minusink Hollow and estimate its correlation with isotopic composition of soil pore water, precipitation, vegetation and parent material. The samples of pedogenic carbonates, vegetation, carbonate parent material, soil water and precipitation water were analyzed using the Delta-V mass spectrometer with options of a gas bench and element analyser. The soils we studied are mainly Kastanozems that are poorly moisturized, therefore soil pore water was extracted by ethanol. Oxygen and carbon isotopic composition of pedogenic carbonates was analyzed in 3 key sites. Kazanovka Khakass state national reserve, Hankul salt lake, region of Sayanogorsk aluminum smelter. Vegetation photosynthetic pathway in the region is mainly C3. δ18O values of carbonate coatings in soils of Kazanovka vary in a range from −7.49 to −10.5‰ (vs V-PDB), and the smallest value −13.9‰ corresponds the coatings found between two buried soil horizons which 14C dates are 4.6 and 5.2 kyr BP. That may indicate cooler conditions of late Holocene than nowadays. In Sayanogorsk carbonates’ δ18O range is from −8.3 to −11.1‰ and near the Hankul Lake is from −9.0 to −10.2‰ all ranges are quite similar and may indicate coatings’ uniform formation conditions. δ13C values of carbonate coatings in Kazanovka vary from −2.5 to −6.7‰, the highest values correspond to the soils of Askiz and Syglygkug rivers former floodplains. For Sayanogorsk the range is from −4.9 to −6.8‰ and for Hankul from −2.3 to −5.7‰, where the highest value is for the modern salt crust. δ13C values of coatings strongly decrease from inner (older) to outer (younger) layers of coatings, that can indicate differences connected with the diffusion of organic material. Carbonate parent material δ18O value in the region vary from −11.1 to −12.0‰ and δ13C values vary from −4.9 to −5.7‰. Soil pore water δ18O values that determine the oxygen isotope composition of carbonates vary due to the processes of transpiration and mixing in the studied sites in a wide range of −2.0 to −13.5‰ (vs V-SMOW). Precipitation waters show δ18O values from -6.6‰ in May and -19.0‰ in January (snow) due to the temperature difference. The main conclusions are as follows: pedogenic carbonates δ13C values (−7…−2,5‰) show no correlation with modern C3 vegetation δ13C values (−30…−26‰), expected values under such vegetation are (−19…−15‰) but are closer to C4 vegetation. Late Holocene climate for the Minusinsk Hollow according to obtained data on isotope composition of carbonates and soil pore water chemical composition was dryer and cooler than present, that does not contradict with paleocarpology data obtained for the region. The research was supported by Russian Science Foundation (grant №14-27-00083).

Keywords: carbon, oxygen, pedogenic carbonates, South Siberia, stable isotopes

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Authors: Rahul Malhotra, Anurag Sharma

Abstract:

Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice, and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: FTTH, quad play, play service, access networks, data rate

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Authors: Laura Piedra-Munoz, Angeles Godoy-Duran, Emilio Galdeano-Gomez, Juan C. Perez-Mesa

Abstract:

Spain is very sensitive to water management issues due to its climatic characteristics and the deficit of this resource in many areas of its territory. This study examines the characteristics of the family farms that are more efficient in the use of water, focusing on a semi-arid area located in Almeria, southeast of Spain. In the case of irrigated agriculture, water usage efficiency usually indicates water productivity in terms of yield (kg/m³), or in economic terms (euros/m³). These two water usage indicators were considered to analyse water usage efficiency according to other studies on water efficiency in the horticultural area under analysis. This work also takes into account other water usage characteristics such as water supplied, innovative irrigation practices, water-efficient technology, and water-saving practices. The results show that the most water efficient farms have technical advisors and use irrigation on demand, that measures the water needs of the crops and are considered the most technological irrigation system. These farms are more technological and less labor intensive. They are also aware of water scarcity and the need to conserve the environment. This approach allow managers to identify the principal factors and best practices related to water efficiency in order to promote and implement them in inefficient farms and promote sustainability.

Keywords: cluster analysis, family farms, Spain, sustainability, water-use efficiency

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Authors: Melissa Lubitz

Abstract:

Water scarcity is one of the crucial challenges of our time. There needs to be a focus on creating a society where people and nature flourish, regardless of climatic conditions. One of the solutions we can look to is decentralized greywater recycling. The vision is simple. Every building has its own water source being greywater from the bath, shower, sink and washing machine. By treating this in the home, you can save 25-45% of potable water use and wastewater production, a reduction in energy consumption and CO2 emissions. This reusable water is clean, and safe to be used for toilet flushing, washing machine, and outdoor irrigation. Companies like Hydraloop have been committed to the greywater recycle-ready building concept for years. This means that drinking water conservation and water reuse are included as standards in the design of all new buildings. Sustainability and renewal go hand in hand. This vision includes not only optimizing water savings and waste reduction but also forging strong partnerships that bring this ambition to life. Together with regulators, municipalities and builders, a sustainable and water-conscious future is pursued. This is an opportunity to be part of a movement that is making a difference. By pushing this initiative forward, we become part of a growing community that resists dehydration, believes in sustainability, and is committed to a living environment at the forefront of change: sustainable living, where saving water is the norm and where we shape the future together.

Keywords: greywater, wastewater treatment, water conservation, circular water society

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Authors: Onyedikachi Ulelu, Andrew P. Longstaff, Simon Fletcher, Simon Parkinson

Abstract:

The widespread interest in 'Industry 4.0' or 'digital manufacturing' has led to significant research requiring the acquisition of data from sensors, instruments, and machine signals. In-depth research then identifies methods of analysis of the massive amounts of data generated before and during manufacture to solve a particular problem. The ultimate goal is for industrial Internet of Things (IIoT) data to be processed automatically to assist with either visualisation or autonomous system decision-making. However, the collection and processing of data in an industrial environment come with a cost. Little research has been undertaken on how to specify optimally what data to capture, transmit, process, and store at various levels of an edge-cloud network. The first step in this specification is to categorise IIoT data for efficient and effective use. This paper proposes the required attributes and classification to take manufacturing digital data from various sources to determine the most suitable location for data processing on the edge-cloud network. The proposed classification framework will minimise overhead in terms of network bandwidth/cost and processing time of machine tool data via efficient decision making on which dataset should be processed at the ‘edge’ and what to send to a remote server (cloud). A fast-and-frugal heuristic method is implemented for this decision-making. The framework is tested using case studies from industrial machine tools for machine productivity and maintenance.

Keywords: data classification, decision making, edge computing, industrial IoT, industry 4.0

Procedia PDF Downloads 180