Search results for: intelligent computational techniques

Authors: Li Zhang, Yuehong Su

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Lightpipe as a mature solar light tube technique has been employed worldwide. Accurately assessing the performance of lightpipe and evaluate daylighting available has been a challenging topic. Previous research had used regression model and computational simulation methods to estimate the performance of lightpipe. However, due to the nonlinear nature of solar light transferring in lightpipe, the methods mentioned above express inaccurate and time-costing issues. In the present study, a neural network model as an alternative method is investigated to predict the transmittance of lightpipe. Four types of commercial lightpipe with bended angle 0°, 30°, 45° and 60° are discussed under clear, intermediate and overcast sky conditions respectively. The neural network is generated in MATLAB by using the outcomes of an optical software Photopia simulations as targets for networks training and testing. The coefficient of determination (R²) for each model is higher than 0.98, and the mean square error (MSE) is less than 0.0019, which indicate the neural network strong predictive ability and the use of the neural network method could be an efficient technique for determining the performance of lightpipe.

Keywords: neural network, bended lightpipe, transmittance, Photopia

Procedia PDF Downloads 143

Authors: Mohammad Ali Badri, Pouya Molana, Amin Rezvanpour

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In this paper, planning catamaran and mono-hull vessels resistance and trim in calm waters were considered. Hydrodynamic analysis of fast mono-hull planning vessel was also investigated. In order to hull form geometry optimization, numerical methods of different parameters were used for this type of vessels. Hull material was selected in carbon fiber composite. Exact architectural aspects were specified and stability calculations were performed as well. Hydrodynamic calculations to extract the resistance force using semi-analytical methods and numerical modeling were carried out. Free surface numerical analysis of vessel in designed draft using finite volume method and double phase were evaluated and verified by experimental tests.

Keywords: fast vessel, hydrostatic and hydrodynamic optimization, free surface flow, computational fluid dynamics

Procedia PDF Downloads 508

Authors: Harris Niavis, Dimitra Politaki

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The manufacturing industry was collecting vast amounts of data for monitoring product quality thanks to the advances in the ICT sector and dedicated IoT infrastructure is deployed to track and trace the production line. However, industries have not yet managed to unleash the full potential of these data due to defective data collection methods and untrusted data storage and sharing. Blockchain is gaining increasing ground as a key technology enabler for Industry 4.0 and the smart manufacturing domain, as it enables the secure storage and exchange of data between stakeholders. On the other hand, AI techniques are more and more used to detect anomalies in batch and time-series data that enable the identification of unusual behaviors. The proposed scheme is based on smart contracts to enable automation and transparency in the data exchange, coupled with anomaly detection algorithms to enable reliable data ingestion in the system. Before sensor measurements are fed to the blockchain component and the smart contracts, the anomaly detection mechanism uniquely combines artificial intelligence models to effectively detect unusual values such as outliers and extreme deviations in data coming from them. Specifically, Autoregressive integrated moving average, Long short-term memory (LSTM) and Dense-based autoencoders, as well as Generative adversarial networks (GAN) models, are used to detect both point and collective anomalies. Towards the goal of preserving the privacy of industries' information, the smart contracts employ techniques to ensure that only anonymized pointers to the actual data are stored on the ledger while sensitive information remains off-chain. In the same spirit, blockchain technology guarantees the security of the data storage through strong cryptography as well as the integrity of the data through the decentralization of the network and the execution of the smart contracts by the majority of the blockchain network actors. The blockchain component of the Data Traceability Software is based on the Hyperledger Fabric framework, which lays the ground for the deployment of smart contracts and APIs to expose the functionality to the end-users. The results of this work demonstrate that such a system can increase the quality of the end-products and the trustworthiness of the monitoring process in the smart manufacturing domain. The proposed AI-enabled data traceability software can be employed by industries to accurately trace and verify records about quality through the entire production chain and take advantage of the multitude of monitoring records in their databases.

Keywords: blockchain, data quality, industry4.0, product quality

Procedia PDF Downloads 172

Authors: Uzu-Kuei Hsu, Keh-Chin Chang, Joo-Guan Hang, Chang-Hsien Tai

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Carbon Deposits are often occurred inside the industrial coke oven during the coking process. Accumulation of carbon deposits may cause a big issue, which seriously influences the coking operation. The carbon is burning off by injecting fresh air through pipes into coke oven which is an efficient way practically operated in industries. The burning off carbon deposition in coke oven performed by Computational Fluid Dynamics (CFD) method has provided an evaluation of the feasibility study. A three-dimensional, transient, turbulent reacting flow simulation has performed with three different injecting air flow rate and another kind of injecting configuration. The result shows that injection higher air flow rate would effectively reduce the carbon deposits. In the meantime, the opened charging holes would suck extra oxygen from the atmosphere to participate in reactions. In term of coke oven operating limits, the wall temperatures are monitored to prevent over-heating of the adiabatic walls during the burn-off process.

Keywords: coke oven, burning off, carbon deposits, carbon combustion, CFD

Procedia PDF Downloads 681

Authors: Pablo Chico De Guzman, Cesar Sanchez

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Microservices are a software development methodology in which applications are built by composing a set of independently deploy-able, small, modular services. Each service runs a unique process and it gets instantiated and deployed in one or more machines (we assume that different microservices are deployed into different machines). Microservices are becoming the de facto standard for developing distributed cloud applications due to their reduced release cycles. In principle, the responsibility of a microservice can be as simple as implementing a single function, which can lead to the following issues: - Resource fragmentation due to the virtual machine boundary. - Poor communication performance between microservices. Two composition techniques can be used to optimize resource fragmentation and communication performance: aggregation and embedding of microservices. Aggregation allows the deployment of a set of microservices on the same machine using a proxy server. Aggregation helps to reduce resource fragmentation, and is particularly useful when the aggregated services have a similar scalability behavior. Embedding deals with communication performance by deploying on the same virtual machine those microservices that require a communication channel (localhost bandwidth is reported to be about 40 times faster than cloud vendor local networks and it offers better reliability). Embedding can also reduce dependencies on load balancer services since the communication takes place on a single virtual machine. For example, assume that microservice A has two instances, a1 and a2, and it communicates with microservice B, which also has two instances, b1 and b2. One embedding can deploy a1 and b1 on machine m1, and a2 and b2 are deployed on a different machine m2. This deployment configuration allows each pair (a1-b1), (a2-b2) to communicate using the localhost interface without the need of a load balancer between microservices A and B. Aggregation and embedding techniques are complex since different microservices might have incompatible runtime dependencies which forbid them from being installed on the same machine. There is also a security concern since the attack surface between microservices can be larger. Luckily, container technology allows to run several processes on the same machine in an isolated manner, solving the incompatibility of running dependencies and the previous security concern, thus greatly simplifying aggregation/embedding implementations by just deploying a microservice container on the same machine as the aggregated/embedded microservice container. Therefore, a wide variety of deployment configurations can be described by combining aggregation and embedding to create an efficient and robust microservice architecture. This paper presents a formal method that receives a declarative definition of a microservice architecture and proposes different optimized deployment configurations by aggregating/embedding microservices. The first prototype is based on i2kit, a deployment tool also submitted to ICWS 2018. The proposed prototype optimizes the following parameters: network/system performance, resource usage, resource costs and failure tolerance.

Keywords: aggregation, deployment, embedding, resource allocation

Procedia PDF Downloads 194

Authors: Fatma Khaled, Khaoula Hidouri, Bechir Chaouachi

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Desalination using solar energy coupled with membrane techniques such as vacuum membrane distillation (VMD) is considered as an interesting alternative for the production of pure water. During this work, a developed model of a polytetrafluoroethylene (PTFE) hollow fiber membrane module of a VMD unit of seawater was carried out. This simulation leads to establishing a comparison between the effects of two different equations of the vaporization latent heat on the membrane surface temperature and on the unit productivity. Besides, in order to study the effect of putting membrane modules in series on the outlet fluid temperature and on the productivity of the process, a simulation was executed.

Keywords: vacuum membrane distillation, membrane module, membrane temperature, productivity

Procedia PDF Downloads 177

Authors: Abdul Wahed Al Zumor

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Saudi EFL Students majoring in English face difficulties in academic lectures listening comprehension in content courses like linguistics, applied linguistics or literature theories. To validate this assumption, a questionnaire assessing students' lecture comprehension experience was administered. The findings have shown that Saudi EFL learners face a great challenge in lecture comprehension at advanced levels. Literature has suggested a myriad of techniques which can enhance academic lecture comprehension. This study has used "reciprocal peer-questioning and responding technique" as an integral part of the academic lecture occupying the last ten minutes. Improvement in experimental students' scores in these courses has been noticed.

Keywords: EFL learners, lecture comprehension, content courses, peer questioning

Procedia PDF Downloads 589

Authors: Souhila Bendenia, Chahrazed Bendenia, Hanaa Merad-Dib, Sarra Merabet, Samia Moulebhar, Sid Ahmed Khantar

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Today, environmental pollution is a major concernworldwide, threateninghumanhealth. Various techniques have been used, includingdegradation, filtration, advancedoxidationprocesses, ion exchange, membrane processes, and adsorption. The latter is one of the mostsuitablemethods, usinghighly efficient materials. In this study, NaX zeolite was modified with Cu or Ni at various rates. Following ion exchange, the samples were characterized by XRD, BET and SEM/EDX. After characterization, the exchanged zeolites were used for adsorption of various pollutants as CO2. Different thermodynamic parameters were studied such as Qst. XRD results show that the most intense peaks characteristic of 13X persist after the exchange reaction for all samples. The SEM images of our samples have uniform and regular crystal shapes. The results show that ion exhange with Cu or Ni affect the textural properties of X zeolites and prove that the exchange zeolites can be used as an adsorbent for depollution.

Keywords: X zeolites (NaX), ion exchange, characterization, adsorption

Procedia PDF Downloads 66

Authors: R. Mohan, V. Jadhav, A. Ahmed, J. Rivas, A. Kelkar

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Cementitious materials are an excellent example of a composite material with complex hierarchical features and random features that range from nanometer (nm) to millimeter (mm) scale. Multi-scale modeling of complex material systems requires starting from fundamental building blocks to capture the scale relevant features through associated computational models. In this paper, molecular dynamics (MD) modeling is employed to predict the effect of plasticizer additive on the mechanical properties of key hydrated cement constituent calcium-silicate-hydrate (CSH) at the molecular, nanometer scale level. Due to complexity, still unknown molecular configuration of CSH, a representative configuration widely accepted in the field of mineral Jennite is employed. The effectiveness of the Molecular Dynamics modeling to understand the predictive influence of material chemistry changes based on molecular/nanoscale models is demonstrated.

Keywords: cement composite, mechanical properties, molecular dynamics, plasticizer additives

Procedia PDF Downloads 443

Authors: Seung-Jun Yu, Yeong-Seop Ahn, Young-Min Ko, Hyoung-Kyu Song

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In order to achieve high data rate and increase the spectral efficiency, multiple input multiple output (MIMO) system has been proposed. However, multiple antennas are limited by size and cost. Therefore, recently developed cooperative diversity scheme, which profits the transmit diversity only with the existing hardware by constituting a virtual antenna array, can be a solution. However, most of the introduced cooperative techniques have a common fault of decreased transmission rate because the destination should receive the decodable compositions of symbols from the source and the relay. In this paper, we propose a cooperative cyclic delay diversity (CDD) scheme that uses hierarchical modulation. This scheme is free from the rate loss and allows seamless cooperative communication.

Keywords: MIMO, cooperative communication, CDD, hierarchical modulation

Procedia PDF Downloads 541

Authors: Mohammad Shams Esfand Abadi, Mehrdad Zalaghi, Reza ebrahimpour

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In this paper, we propose a sign adaptive filter algorithm with the ability of dynamic selection of subband filters which leads to low computational complexity compared with conventional sign subband adaptive filter (SSAF) algorithm. Dynamic selection criterion is based on largest reduction of the mean square deviation at each adaption. We demonstrate that this simple proposed algorithm has the same performance of the conventional SSAF and somewhat faster than it. In the presence of impulsive interferences robustness of the simple proposed algorithm as well as the conventional SSAF and outperform the conventional normalized subband adaptive filter (NSAF) algorithm. Therefore, it is preferred for environments under impulsive interferences. Simulation results are presented to verify these above considerations very well have been achieved.

Keywords: acoustic echo cancellation (AEC), normalized subband adaptive filter (NSAF), dynamic selection subband adaptive filter (DS-NSAF), sign subband adaptive filter (SSAF), impulsive noise, robust filtering

Procedia PDF Downloads 585

Authors: Klathea Sevilla, Marjorie Remolador, Bryan Baltazar, Imee Saladaga, Loureal Camille Inocencio, Ma. Rosario Concepcion Ang

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The underutilization of biomass resources in the Philippines, combined with its growing population and the rise in fossil fuel prices confirms demand for alternative energy sources. The goal of this paper is to provide a comparison of MODIS-based and Landsat-based agricultural land cover maps when used in the estimation of rice hull’s available energy potential. Biomass resource assessment was done using mathematical models and remote sensing techniques employed in a GIS platform.

Keywords: biomass, geographic information system (GIS), remote sensing, renewable energy

Procedia PDF Downloads 475

Authors: Maedeh Shojaeizadeh, Amirreza Yeganegi

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Nowadays many people lose their lives due to cardiovascular diseases. Inappropriate food habits and lack of exercise expedite deposit process of fatty substances on inner surface of blood arteries. This abnormal lump disturbs uniform blood flow and reduces oxygen delivery to active organs. This work presents a numerical simulation of Non-Newtonian blood flow in a stenosis vessel. The vessel is considered as two dimensional channel and plaque area is modelled as a homogenous porous medium. To simulate blood flow reaction around stenosis region, we use C++ code and solve coupled Cauchy, Darcy, governing continuity and energy equations. The analyses results show that viscosity power (n) plays an important role in flow separation and the size of the eddy at the downstream edge of the plaque. It is also observed that with increasing (n) value, temperature discontinuity and likelihood of vessel rupture declined.

Keywords: blood flow, computational fluid dynamic, porosity, power law fluid

Procedia PDF Downloads 449

Authors: Mohamed Alimoussa, Alice Porebski, Nicolas Vandenbroucke, Rachid Oulad Haj Thami, Sana El Fkihi

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Color and texture are highly discriminant visual cues that provide an essential information in many types of images. Color texture representation and classification is therefore one of the most challenging problems in computer vision and image processing applications. Color textures can be represented in different color spaces by using multiple image descriptors which generate a high dimensional set of texture features. In order to reduce the dimensionality of the feature set, feature selection techniques can be used. The goal of feature selection is to find a relevant subset from an original feature space that can improve the accuracy and efficiency of a classification algorithm. Traditionally, feature selection is focused on removing irrelevant features, neglecting the possible redundancy between relevant ones. This is why some feature selection approaches prefer to use feature clustering analysis to aid and guide the search. These techniques can be divided into two categories. i) Feature clustering-based ranking algorithm uses feature clustering as an analysis that comes before feature ranking. Indeed, after dividing the feature set into groups, these approaches perform a feature ranking in order to select the most discriminant feature of each group. ii) Feature clustering-based subset search algorithms can use feature clustering following one of three strategies; as an initial step that comes before the search, binded and combined with the search or as the search alternative and replacement. In this paper, we propose a new feature clustering-based sequential selection approach for the purpose of color texture representation and classification. Our approach is a three step algorithm. First, irrelevant features are removed from the feature set thanks to a class-correlation measure. Then, introducing a new automatic feature clustering algorithm, the feature set is divided into several feature clusters. Finally, a sequential search algorithm, based on a filter model and a separability measure, builds a relevant and non redundant feature subset: at each step, a feature is selected and features of the same cluster are removed and thus not considered thereafter. This allows to significantly speed up the selection process since large number of redundant features are eliminated at each step. The proposed algorithm uses the clustering algorithm binded and combined with the search. Experiments using a combination of two well known texture descriptors, namely Haralick features extracted from Reduced Size Chromatic Co-occurence Matrices (RSCCMs) and features extracted from Local Binary patterns (LBP) image histograms, on five color texture data sets, Outex, NewBarktex, Parquet, Stex and USPtex demonstrate the efficiency of our method compared to seven of the state of the art methods in terms of accuracy and computation time.

Keywords: feature selection, color texture classification, feature clustering, color LBP, chromatic cooccurrence matrix

Procedia PDF Downloads 123

Authors: Hira Jabbar, Tanzeel-Ur Rehman

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Urban parks and open spaces play a significant role in improving physical and mental health of the citizens, strengthen the societies and make the cities more attractive places to live and work. As the world’s cities continue to grow, continuing to value green space in cities is vital but is also a challenge, particularly in developing countries where there is pressure for space, resources, and development. Offering equal opportunity of accessibility to parks is one of the important issues of park distribution. The distribution of parks should allow all inhabitants to have close proximity to their residence. Remote sensing and Geographic information systems (GIS) can provide decision makers with enormous opportunities to improve the planning and management of Park facilities. This study exhibits the capability of GIS and RS techniques to provide baseline knowledge about the distribution of parks, level of accessibility and to help in identification of potential areas for such facilities. For this purpose Landsat OLI imagery for year 2016 was acquired from USGS Earth Explorer. Preprocessing models were applied using Erdas Imagine 2014v for the atmospheric correction and NDVI model was developed and applied to quantify the land use/land cover classes including built up, barren land, water, and vegetation. The parks amongst total public green spaces were selected based on their signature in remote sensing image and distribution. Percentages of total green and parks green were calculated for each town of Lahore City and results were then synchronized with the recommended standards. ANGSt model was applied to calculate the accessibility from parks. Service area analysis was performed using Network Analyst tool. Serviceability of these parks has been evaluated by employing statistical indices like service area, service population and park area per capita. Findings of the study may contribute in helping the town planners for understanding the distribution of parks, demands for new parks and potential areas which are deprived of parks. The purpose of present study is to provide necessary information to planners, policy makers and scientific researchers in the process of decision making for the management and improvement of urban parks.

Keywords: accessible natural green space standards (ANGSt), geographic information systems (GIS), remote sensing (RS), United States geological survey (USGS)

Procedia PDF Downloads 322

Authors: Benn Van Den Ende

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Over the last three decades, there has been an exponential increase in developments in implantable technologies such as the cardiac pacemaker, bionic prosthesis, and implantable chips. The effect of these technologies has been well researched in many areas. However, there is a lack of critical research in security studies. This paper will provide preliminary findings to an ongoing research project which aims to examine how implantable technologies effect the practices of governmentality in the context of security. It will do this by looking at the practices and techniques of governmentality along with different implantable technologies which increase, change or otherwise affect governmental practices. The preliminary research demonstrates that implantable technologies have a profound effect on the practices of governmentality, while also paving the way for further research into a potential ‘new’ form of governmentality in relation to these implantable technologies.

Keywords: critical security studies, governmentality, security theory, political theory, Foucault

Procedia PDF Downloads 175

Authors: Werner Grommes

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The institute of occupational safety and health works in a working group for building a normative standard for illuminated warning vests and did a lot of experiments and measurements as basic work (cooperation). Intelligent car headlamps are able to suppress conventional warning vests with retro-reflective stripes as a disturbing light. Illuminated warning vests are therefore required for occupational safety. However, they must not pose any danger to the wearer or other persons. Here, the risks of the batteries (lithium types), the maximum brightness (glare) and possible interference radiation from the electronics on the implant carrier must be taken into account. The all-around visibility, as well as the required range, play an important role here. For the study, many luminance measurements of already commercially available LEDs and electroluminescent warning vests, as well as their electromagnetic interference fields and aspects of electrical safety, were measured. The results of this study showed that LED lighting is all far too bright and causes strong glare. The integrated controls with pulse modulation and switching regulators cause electromagnetic interference fields. Rechargeable lithium batteries can explode depending on the temperature range. Electroluminescence brings even more hazards. A test method was developed for the evaluation of visibility at distances of 50, 100, and 150 m, including the interview of test persons. A measuring method was developed for the detection of glare effects at close range with the assignment of the maximum permissible luminance. The electromagnetic interference fields were tested in the time and frequency ranges. A risk and hazard analysis were prepared for the use of lithium batteries. The range of values for luminance and risk analysis for lithium batteries were discussed in the standards working group. These will be integrated into the standard. This paper gives a brief overview of the topics of illuminated warning vests, which takes into account the risks and hazards for the vest wearer or others

Keywords: illuminated warning vest, optical tests and measurements, risks, hazards, optical glare effects, LED, E-light, electric luminescent

Procedia PDF Downloads 104

Authors: C. Slim

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Traditional techniques for analyzing time series are based on the notion of stationarity of phenomena under study, but in reality most economic and financial series do not verify this hypothesis, which implies the implementation of specific tools for the detection of such behavior. In this paper, we study nonstationary non-seasonal time series tests in a non-exhaustive manner. We formalize the problem of nonstationary processes with numerical simulations and take stock of their statistical characteristics. The theoretical aspects of some of the most common unit root tests will be discussed. We detail the specification of the tests, showing the advantages and disadvantages of each. The empirical study focuses on the application of these tests to the exchange rate (USD/TND) and the Consumer Price Index (CPI) in Tunisia, in order to compare the Power of these tests with the characteristics of the series.

Keywords: stationarity, unit root tests, economic time series, ADF tests

Procedia PDF Downloads 413

Authors: L. Diogo, A. Legrand, J. Nguyen-Cao, J. Rogeau, S. Bornhofen

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Lenia is a system of cellular automata with continuous states, space and time, which surprises not only with the emergence of interesting life-like structures but also with its beauty. This paper reports ongoing research on a GPU implementation of Lenia using CUDA C++ and OpenGL Interoperability. We demonstrate how CUDA as a low-level GPU programming paradigm allows optimizing performance and memory usage of the Lenia algorithm. A comparative analysis through experimental runs with existing implementations shows that the CUDA implementation outperforms the others by one order of magnitude or more. Cellular automata hold significant interest due to their ability to model complex phenomena in systems with simple rules and structures. They allow exploring emergent behavior such as self-organization and adaptation, and find applications in various fields, including computer science, physics, biology, and sociology. Unlike classic cellular automata which rely on discrete cells and values, Lenia generalizes the concept of cellular automata to continuous space, time and states, thus providing additional fluidity and richness in emerging phenomena. In the current literature, there are many implementations of Lenia utilizing various programming languages and visualization libraries. However, each implementation also presents certain drawbacks, which serve as motivation for further research and development. In particular, speed is a critical factor when studying Lenia, for several reasons. Rapid simulation allows researchers to observe the emergence of patterns and behaviors in more configurations, on bigger grids and over longer periods without annoying waiting times. Thereby, they enable the exploration and discovery of new species within the Lenia ecosystem more efficiently. Moreover, faster simulations are beneficial when we include additional time-consuming algorithms such as computer vision or machine learning to evolve and optimize specific Lenia configurations. We developed a Lenia implementation for GPU using the C++ and CUDA programming languages, and CUDA/OpenGL Interoperability for immediate rendering. The goal of our experiment is to benchmark this implementation compared to the existing ones in terms of speed, memory usage, configurability and scalability. In our comparison we focus on the most important Lenia implementations, selected for their prominence, accessibility and widespread use in the scientific community. The implementations include MATLAB, JavaScript, ShaderToy GLSL, Jupyter, Rust and R. The list is not exhaustive but provides a broad view of the principal current approaches and their respective strengths and weaknesses. Our comparison primarily considers computational performance and memory efficiency, as these factors are critical for large-scale simulations, but we also investigate the ease of use and configurability. The experimental runs conducted so far demonstrate that the CUDA C++ implementation outperforms the other implementations by one order of magnitude or more. The benefits of using the GPU become apparent especially with larger grids and convolution kernels. However, our research is still ongoing. We are currently exploring the impact of several software design choices and optimization techniques, such as convolution with Fast Fourier Transforms (FFT), various GPU memory management scenarios, and the trade-off between speed and accuracy using single versus double precision floating point arithmetic. The results will give valuable insights into the practice of parallel programming of the Lenia algorithm, and all conclusions will be thoroughly presented in the conference paper. The final version of our CUDA C++ implementation will be published on github and made freely accessible to the Alife community for further development.

Keywords: artificial life, cellular automaton, GPU optimization, Lenia, comparative analysis.

Procedia PDF Downloads 20

Authors: Juyon Lee, Myoungjin Park, Jonghoon Kim, Jaekook Ha, Chanhee Lee

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We demonstrated a new positive aging methods of QLEDs devices that can apply in large size inkjet printing display. Conventional positive aging method using photo-curable resin remains unclear mechanism of the phenomenon and also there are many limitations to apply large size panels in commercial process. Through the photo acid generator (PAG) in ETL Ink, we achieved 90% of the efficiency of the conventional method and up to 1000h life time stability (T80). This techniques could be applied to next generation of QLEDs panels and also can prove the working mechanism of positive aging in QLED related to modification of ZnMgO NPs.

Keywords: quantum dots, QLED, printing, positive aging, ZnMgO NPs

Procedia PDF Downloads 135

Authors: Rob van den Dam

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Today’s Internet of Things (IoT) comprises more than a billion intelligent devices, connected via wired/wireless communications. The expected proliferation of hundreds of billions more places us at the threshold of a transformation sweeping across the communications industry. Yet, we found that the IoT architecture and solutions that currently work for billions of devices won’t necessarily scale to tomorrow’s hundreds of billions of devices because of high cost, lack of privacy, not future-proof, lack of functional value and broken business models. As the IoT scales exponentially, decentralized networks have the potential to reduce infrastructure and maintenance costs to manufacturers. Decentralization also promises increased robustness by removing single points of failure that could exist in traditional centralized networks. By shifting the power in the network from the center to the edges, devices gain greater autonomy and can become points of transactions and economic value creation for owners and users. To validate the underlying technology vision, IBM jointly developed with Samsung Electronics the autonomous decentralized peer-to- peer proof-of-concept (PoC). The primary objective of this PoC was to establish a foundation on which to demonstrate several capabilities that are fundamental to building a decentralized IoT. Though many commercial systems in the future will exist as hybrid centralized-decentralized models, the PoC demonstrated a fully distributed proof. The PoC (a) validated the future vision for decentralized systems to extensively augment today’s centralized solutions, (b) demonstrated foundational IoT tasks without the use of centralized control, (c) proved that empowered devices can engage autonomously in marketplace transactions. The PoC opens the door for the communications and electronics industry to further explore the challenges and opportunities of potential hybrid models that can address the complexity and variety of requirements posed by the internet that continues to scale. Contents: (a) The new approach for an IoT that will be secure and scalable, (b) The three foundational technologies that are key for the future IoT, (c) The related business models and user experiences, (d) How such an IoT will create an 'Economy of Things', (e) The role of users, devices, and industries in the IoT future, (f) The winners in the IoT economy.

Keywords: IoT, internet, wired, wireless

Procedia PDF Downloads 328

Authors: S. Mehrab Amiri, Nasser Talebbeydokhti

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Modeling sediment transport processes by means of numerical approach often poses severe challenges. In this way, a number of techniques have been suggested to solve flow and sediment equations in decoupled, semi-coupled or fully coupled forms. Furthermore, in order to capture flow discontinuities, a number of techniques, like artificial viscosity and shock fitting, have been proposed for solving these equations which are mostly required careful calibration processes. In this research, a numerical scheme for solving shallow water and Exner equations in fully coupled form is presented. First-Order Centered scheme is applied for producing required numerical fluxes and the reconstruction process is carried out toward using Monotonic Upstream Scheme for Conservation Laws to achieve a high order scheme.  In order to satisfy C-property of the scheme in presence of bed topography, Surface Gradient Method is proposed. Combining the presented scheme with fourth order Runge-Kutta algorithm for time integration yields a competent numerical scheme. In addition, to handle non-prismatic channels problems, Cartesian Cut Cell Method is employed. A trained Multi-Layer Perceptron Artificial Neural Network which is of Feed Forward Back Propagation (FFBP) type estimates sediment flow discharge in the model rather than usual empirical formulas. Hydrodynamic part of the model is tested for showing its capability in simulation of flow discontinuities, transcritical flows, wetting/drying conditions and non-prismatic channel flows. In this end, dam-break flow onto a locally non-prismatic converging-diverging channel with initially dry bed conditions is modeled. The morphodynamic part of the model is verified simulating dam break on a dry movable bed and bed level variations in an alluvial junction. The results show that the model is capable in capturing the flow discontinuities, solving wetting/drying problems even in non-prismatic channels and presenting proper results for movable bed situations. It can also be deducted that applying Artificial Neural Network, instead of common empirical formulas for estimating sediment flow discharge, leads to more accurate results.

Keywords: artificial neural network, morphodynamic model, sediment continuity equation, shallow water equations

Procedia PDF Downloads 182

Authors: Vinai K. Singh

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In Neural Network-based Learning techniques, there are several models of Convolutional Networks. Whenever the methods are deployed with large datasets, only then can their applicability and appropriateness be determined. Clinical and pathological pictures of lobular carcinoma are thought to exhibit a large number of random formations and textures. Working with such pictures is a difficult problem in machine learning. Focusing on wet laboratories and following the outcomes, numerous studies have been published with fresh commentaries in the investigation. In this research, we provide a framework that can operate effectively on raw photos of various resolutions while easing the issues caused by the existence of patterns and texturing. The suggested approach produces very good findings that may be used to make decisions in the diagnosis of cancer.

Keywords: lobular carcinoma, convolutional neural networks (CNN), deep learning, histopathological imagery scans

Procedia PDF Downloads 127

Authors: S. Ghasemi, K. Khorasani

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In this paper, the problem of fault detection and isolation in the attitude control subsystem of spacecraft formation flying is considered. In order to design the fault detection method, an extended Kalman filter is utilized which is a nonlinear stochastic state estimation method. Three fault detection architectures, namely, centralized, decentralized, and semi-decentralized are designed based on the extended Kalman filters. Moreover, the residual generation and threshold selection techniques are proposed for these architectures.

Keywords: component, formation flight of satellites, extended Kalman filter, fault detection and isolation, actuator fault

Procedia PDF Downloads 423

Authors: Nneka Osuchukwu, Leonid Shpanin

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The concept of converting the kinetic energy of quadcopter propellers into electrical energy is considered in this contribution following the feasibility study of the propeller vibrations, theoretical energy conversion, and simulation techniques. Analysis of the propeller vibration performance is presented via graphical representation of calculated and simulated parameters, in order to demonstrate the possibility of recovering the harvested energy from the propeller vibrations of the quadcopter while the quadcopter is in operation. Consideration of using piezoelectric materials in such concept, converting the mechanical energy of the propeller into the electrical energy, is given. Photographic evidence of the propeller in operation is presented and discussed together with experimental results to validate the theoretical concept.

Keywords: energy harvesting, piezoelectric material, propeller vibration, unmanned aerial vehicle

Procedia PDF Downloads 465

Authors: Kritika Bansal, Akwinder Kaur, Shruti Gujral

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In this paper, the approach of denoising is solved by using a new hybrid technique which associates the different denoising methods. Wavelet thresholding and anisotropic diffusion filter are the two different filters in our hybrid techniques. The Wavelet thresholding removes the noise by removing the high frequency components with lesser edge preservation, whereas an anisotropic diffusion filters is based on partial differential equation, (PDE) to remove the speckle noise. This PDE approach is used to preserve the edges and provides better smoothing. So our new method proposes a combination of these two filtering methods which performs better results in terms of peak signal to noise ratio (PSNR), coefficient of correlation (COC) and equivalent no of looks (ENL).

Keywords: denoising, anisotropic diffusion filter, multiplicative noise, speckle, wavelets

Procedia PDF Downloads 504

Authors: Norm Josephy, Lucy Kimball, Victoria Steblovskaya

Abstract:

Hedging of a portfolio of European options under proportional transaction costs is considered. Our discrete time financial market model extends the binomial market model with transaction costs to the case where the underlying stock price ratios are distributed over a bounded interval rather than over a two-point set. An optimal hedging strategy is chosen from a set of admissible non-self-financing hedging strategies. Our approach to optimal hedging of a portfolio of options is based on theoretical foundation that includes determination of a no-arbitrage option price interval as well as on properties of the non-self-financing strategies and their residuals. A computational algorithm for optimizing an investor relevant criterion over the set of admissible non-self-financing hedging strategies is developed. Applicability of our approach is demonstrated using both simulated data and real market data.

Keywords: extended binomial model, non-self-financing hedging, optimization, proportional transaction costs

Procedia PDF Downloads 247

Authors: A. J. Regan, F. J. Lidgey, M. Betteridge, P. Georgiou, C. Toumazou, K. Hayatleh, J. R. Dibble

Abstract:

Our goal is development of an algorithm capable of predicting the directional trend of the Standard and Poor’s 500 index (S&P 500). Extensive research has been published attempting to predict different financial markets using historical data testing on an in-sample and trend basis, with many authors employing excessively complex mathematical techniques. In reviewing and evaluating these in-sample methodologies, it became evident that this approach was unable to achieve sufficiently reliable prediction performance for commercial exploitation. For these reasons, we moved to an out-of-sample strategy based on linear regression analysis of an extensive set of financial data correlated with historical closing prices of the S&P 500. We are pleased to report a directional trend accuracy of greater than 55% for tomorrow (t+1) in predicting the S&P 500.

Keywords: financial algorithm, GPU, S&P 500, stock market prediction

Procedia PDF Downloads 342

Authors: Jagdish Prasad Maurya, Sanjay Kumar Pandey

Abstract:

Inadequate understanding of the complex nature of flow features in tornado vortex is a major problem in modelling tornadoes. Tornadoes are violent atmospheric phenomenon that appear all over the world. Modelling tornadoes aim to reduce the loss of the human lives and material damage caused by the tornadoes. Dynamics of tornado is investigated by a numerical technique, the improved version of the projection method. In this paper, authors solve the problem for axisymmetric tornado vortex by the said method that uses a finite difference approach for getting an accurate and stable solution. The conclusions drawn are that large radial inflow velocity occurs near the ground that leads to increase the tangential velocity. The increased velocity phenomenon occurs close to the boundary and absolute maximum wind is obtained near the vortex core. The results validate previous numerical and theoretical models.

Keywords: computational fluid dynamics, mathematical model, Navier-Stokes equations, tornado

Procedia PDF Downloads 343

Authors: Kadi-Hanifi Halima, Amghar Fateh

Abstract:

Steppes of arid Mediterranean zones are deeply threatened by desertification. To stop or alleviate ecological and economic problems associated with this desertification, management actions have been implemented since the last three decades. The struggle against desertification has become a national priority in many countries. In Algeria, several management techniques have been used to cope with desertification. This study aims at investigating the effect of exclosure on floristic diversity and chemical soil properties after four years of implementation. 167 phyto-ecological samples have been studied, 122 inside the exclosure and 45 outside. Results showed that plant diversity, composition, vegetation cover, pastoral value and soil fertility were significantly higher in protected areas.

Keywords: desertification, arid, pastoral management, plant community soil fertility, gestation of environment, Algeria

Procedia PDF Downloads 321