Search results for: multi metal remediation

Authors: Andreas Hammer

Abstract:

Six peculiar architecture designs from the Frankfurt University will be discussed within this paper and their future potential of the adaptable and solar thin-film sheets implemented facades will be shown acting and reacting on climate/solar changes of their specific sites. The different aspects, as well as limitations with regard to technical and functional restrictions, will be named.  The design process for a “multi-purpose building”, a “high-rise building refurbishment” and a “biker’s lodge” on the river Rheine valley, has been critically outlined and developed step by step from an international studentship towards an overall energy strategy, that firstly had to push the design to a plus-energy building and secondly had to incorporate bionic aspects into the building skins design. Both main parameters needed to be reviewed and refined during the whole design process. Various basic bionic approaches have been given [e.g. solar ivy ^TM, flectofin ^TM or hygroskin ^TM, which were to experiment with, regarding the use of bendable photovoltaic thin film elements being parts of a hybrid, kinetic façade system.

Keywords: Energy-strategy, photovoltaic in building skins, bionic and bioclimatic design, plus-energy-buildings, solar gain, the harvesting façade, sustainable building concept, high-efficiency building skin, climate adaptive Building Shells (CABS).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2784

Authors: Farhad Kolahan, A. Hamid Khajavi

Abstract:

Abrasive waterjet is a novel machining process capable of processing wide range of hard-to-machine materials. This research addresses modeling and optimization of the process parameters for this machining technique. To model the process a set of experimental data has been used to evaluate the effects of various parameter settings in cutting 6063-T6 aluminum alloy. The process variables considered here include nozzle diameter, jet traverse rate, jet pressure and abrasive flow rate. Depth of cut, as one of the most important output characteristics, has been evaluated based on different parameter settings. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. The pairwise effects of process parameters settings on process response outputs are also shown graphically. The proposed model is then embedded into a Simulated Annealing algorithm to optimize the process parameters. The optimization is carried out for any desired values of depth of cut. The objective is to determine proper levels of process parameters in order to obtain a certain level of depth of cut. Computational results demonstrate that the proposed solution procedure is quite effective in solving such multi-variable problems.

Keywords: AWJ cutting, Mathematical modeling, Simulated Annealing, Optimization

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2154

Authors: Nataliya Hitsevich

Abstract:

Article 5(3) of the Brussels I Regulation provides that a person domiciled in a Member State may be sued in another Member State in matters relating to tort, delict or quasi-delict, in the courts for the place where the harmful events occurred or may occur. For a number of years Article 5 (3) of the Brussels I Regulation has been at the centre of the debate regarding the intellectual property rights infringement over the Internet. Nothing has been done to adapt the provisions relating to non-internet cases of infringement of intellectual property rights to the context of the Internet. The author’s findings indicate that in the case of intellectual property rights infringement on the Internet, the plaintiff has the option to sue either: the court of the Member State of the event giving rise to the damage: where the publisher of the newspaper is established; the court of the Member State where the damage occurred: where defamatory article is distributed. However, it must be admitted that whilst infringement over the Internet has some similarity to multi-State defamation by means of newspapers, the position is not entirely analogous due to the cross-border nature of the Internet. A simple example which may appropriately illustrate its contentious nature is a defamatory statement published on a website accessible in different Member States, and available in different languages. Therefore, we need to answer the question: how these traditional jurisdictional rules apply in the case of intellectual property rights infringement over the Internet? Should these traditional jurisdictional rules be modified?

Keywords: Intellectual property rights, infringement, Internet, jurisdiction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4533

Authors: Nkechi Neboh, Josiah Adeyemo, Abimbola Enitan, Oludayo Olugbara

Abstract:

Evolutionary Algorithms (EAs) have been used widely through evolution theory to discover acceptable solutions that corresponds to challenges such as natural resources management. EAs are also used to solve varied problems in the real world. EAs have been rapidly identified for its ease in handling multiple objective problems. Reservoir operations is a vital and researchable area which has been studied in the last few decades due to the limited nature of water resources that is found mostly in the semi-arid regions of the world. The state of some developing economy that depends on electricity for overall development through hydropower production, a renewable form of energy, is appalling due to water scarcity. This paper presents a review of the applications of evolutionary algorithms to reservoir operation for hydropower production. This review includes the discussion on areas such as genetic algorithm, differential evolution, and reservoir operation. It also identified the research gaps discovered in these areas. The results of this study will be an eye opener for researchers and decision makers to think deeply of the adverse effect of water scarcity and drought towards economic development of a nation. Hence, it becomes imperative to identify evolutionary algorithms that can address this issue which can hamper effective hydropower generation.

Keywords: Evolutionary algorithms, genetic algorithm, hydropower, multi-objective, reservoir operations.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2794

Authors: B. O. Olawale, C. R. Chatwin, R. C. D. Young, P. M. Birch, F. O. Faithpraise, A. O. Olukiran

Abstract:

In this paper, we present a four-step ortho-rectification procedure for real-time geo-referencing of video data from a low-cost UAV equipped with a multi-sensor system. The basic procedures for the real-time ortho-rectification are: (1) decompilation of the video stream into individual frames; (2) establishing the interior camera orientation parameters; (3) determining the relative orientation parameters for each video frame with respect to each other; (4) finding the absolute orientation parameters, using a self-calibration bundle and adjustment with the aid of a mathematical model. Each ortho-rectified video frame is then mosaicked together to produce a mosaic image of the test area, which is then merged with a well referenced existing digital map for the purpose of geo-referencing and aerial surveillance. A test field located in Abuja, Nigeria was used to evaluate our method. Video and telemetry data were collected for about fifteen minutes, and they were processed using the four-step ortho-rectification procedure. The results demonstrated that the geometric measurement of the control field from ortho-images is more accurate when compared with those from original perspective images when used to pin point the exact location of targets on the video imagery acquired by the UAV. The 2-D planimetric accuracy when compared with the 6 control points measured by a GPS receiver is between 3 to 5 metres.

Keywords: Geo-referencing, ortho-rectification, video frame, self-calibration, UAV, target tracking.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1614

Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

Abstract:

With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: Activities of daily living, classification, internet of things, machine learning, smart home.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1770

Authors: Sanae Attioui, Said Najah

Abstract:

The Earth's surface is constantly changing through forces of nature and human activities. Reliable, accurate, and timely change detection is critical to environmental monitoring, resource management, and planning activities. Recently, interest in deep learning algorithms, especially convolutional neural networks, has increased in the field of image change detection due to their powerful ability to extract multi-level image features automatically. However, these networks are prone to drawbacks that limit their applications, which reside in their inability to capture spatial relationships between image instances, as this necessitates a large amount of training data. As an alternative, Capsule Network has been proposed to overcome these shortcomings. Although its effectiveness in remote sensing image analysis has been experimentally verified, its application in change detection tasks remains very sparse. Motivated by its greater robustness towards improved hierarchical object representation, this study aims to apply a capsule network for PolSAR image Change Detection. The experimental results demonstrate that the proposed change detection method can yield a significantly higher detection rate compared to methods based on convolutional neural networks.

Keywords: Change detection, capsule network, deep network, Convolutional Neural Networks, polarimetric synthetic aperture radar images, PolSAR images.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 498

Authors: Bello Ali

Abstract:

The use of Information and Communication Technology (ICT) in tertiary institutions by lecturers and students has become a necessity for the enhancement of quality teaching and learning. This study examined availability, accessibility and utilization of ICT in Teaching-Learning Islamic Studies in Colleges of Education, North-East, Nigeria. The study adopted multi-stage sampling technique, in which, five out of the eleven Colleges of Education (both Federal and State owned) were purposively selected for the study. Primary data was drawn from the respondents by the use of questionnaire, interviews and observations. The results of the study, generally, indicate that the availability and accessibility to ICT facilities in Colleges of Education in North-East, Nigeria, especially in teaching/learning delivery of Islamic studies were relatively inadequate and rare to lecturers and students. The study further reveals that the respondents’ level of utilization of ICT is low and only few computer packages and internet services were involved in the ICT utilization, which is yet to reach the real expected situation of the globalization and advancement in the application of ICT if compared to other parts of the world, as far as the teaching and learning of Islamic studies is concerned. Observations and conclusion were drawn from the findings and finally, recommendations on how to improve on ICT availability, accessibility and utilization in teaching/ learning were suggested.

Keywords: Accessibility, availability, college of education, ICT, Islamic Studies, learning, North-Eastern, teaching, utilization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1132

Authors: Osama M. Darwesh, Sahar H. Hassan, Abd El-Raheem R. El-Shanshoury, Shawky Z. Sabae

Abstract:

Nanotechnology as multidisciplinary technology is growing rapidly with important applications in several sectors. Also, nanobiotechnology is known for the use of microorganisms for the synthesis of targeted nanoparticles. The present study deals with the green synthesis of silver nanoparticles using aquatic bacteria and the development of a biogenic nanocomposite for environmental applications. 20 morphologically different colonies were isolated from the collected water samples from eight different locations at the Rosetta branch of the Nile Delta, Egypt. The obtained results illustrated that the most effective bacterial isolate (produced the higher amount of AgNPs after 24 h of incubation time) is isolate R3. Bacillus tequilensis was the strongest extracellular bio-manufactory of AgNPs. Biosynthesized nanoparticles had a spherical shape with a mean diameter of 2.74 to 28.4 nm. The antimicrobial activity of silver nanoparticles against many pathogenic microbes indicated that the produced AgNPs had high activity against all tested multi-antibiotic resistant pathogens. Also, the stabilized prepared AgNPs-SA nanocomposite has greater catalytic activity for the decolourization of some dyes like Methylene blue (MB) and Crystal violet. Such results represent a promising stage for producing eco-friendly, cost-effective, and easy-to-handle devices for the bioremediation of contaminated industrial wastewater.

Keywords: Bioremediation, AgNPs, AgNPs-SA nanocomposite, Bacillus tequilensis, nanobiotechnology.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 363

Authors: Handan Ertaş

Abstract:

The aim of the study is to determine the relationship between organizational trust level and organizational justice of Municipality officials. Correlational method has been used via descriptive survey model and Organizational Justice Perception Scale, Organizational Trust Inventory and Interpersonal Trust Scale have been applied to 353 participants who work in Konya Metropolitan Municipality and central district municipalities in the study. Frequency as statistical method, Independent Samples t test for binary groups, One Way-ANOVA analyses for multi-groups and Pearson Correlation analysis have been used to determine the relation in the data analysis process.It has been determined in the outcomes of the study that participants have high level of organizational trust, “Interpersonal Trust” is in the first place and there is a significant difference in the favor of male officials in terms of Trust on the Organization Itself and Interpersonal Trust. It has also been understood that officials in district municipalities have higher perception level in all dimensions, there is a significant difference in Trust on the Organization sub-dimension and work status is an important factor on organizational trust perception. Moreover, the study has shown that organizational justice implementations are important in raising trust of official on the organization, administrator and colleagues, and there is a parallel relation between Organizational Trust components and Organizational Trust dimensions.

Keywords: Konya, Organizational Justice, Organizational.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1870

Authors: Petr Cernohorsky, Jan Voracek

Abstract:

Well-developed strategic marketing planning is the essential prerequisite for establishment of the right and unique competitive advantage. Typical market, however, is a heterogeneous and decentralized structure with natural involvement of individual or group subjectivity and irrationality. These features cannot be fully expressed with one-shot rigorous formal models based on, e.g. mathematics, statistics or empirical formulas. We present an innovative solution, extending the domain of agent based computational economics towards the concept of hybrid modeling in service provider and consumer market such as telecommunications. The behavior of the market is described by two classes of agents - consumer and service provider agents - whose internal dynamics are fundamentally different. Customers are rather free multi-state structures, adjusting behavior and preferences quickly in accordance with time and changing environment. Producers, on the contrary, are traditionally structured companies with comparable internal processes and specific managerial policies. Their business momentum is higher and immediate reaction possibilities limited. This limitation underlines importance of proper strategic planning as the main process advising managers in time whether to continue with more or less the same business or whether to consider the need for future structural changes that would ensure retention of existing customers or acquisition of new ones.

Keywords: Agent-based computational economics, hybrid modeling, strategic marketing, system dynamics.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1641

Authors: Rajendraprasad Narne, P. C. Panda

Abstract:

In this article, coordinated tuning of power system stabilizer (PSS) with static var compensator (SVC) and thyristor controlled series capacitor (TCSC) in multi-machine power system is proposed. The design of proposed coordinated damping controller is formulated as an optimization problem and the controller gains are optimized instantaneously using advanced adaptive particle swarm optimization (AAPSO). The objective function is framed with the inter-area speed deviations of the generators and it is minimized using AAPSO to improve the dynamic stability of power system under severe disturbance. The proposed coordinated controller performance is evaluated under a wide range of system operating conditions with three-phase fault disturbance. Using time domain simulations the damping characteristics of proposed controller is compared with individually tuned PSS, SVC and TCSC controllers. Finally, the real-time simulations are carried out in Opal-RT hardware simulator to synchronize the proposed controller performance in the real world.

Keywords: Advanced adaptive particle swarm optimization, Coordinated design, Power system stabilizer, Real-time implementation, static var compensator, Thyristor controlled series capacitor.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2591

Authors: Rong-Terng Juang

Abstract:

Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: Autonomous vehicle, data recording, remote monitoring, controller area network.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1351

Authors: Fiona Curran-Cournane

Abstract:

Soil quality monitoring is a science-based soil management tool that assesses soil ecosystem health. A soil monitoring program in Auckland, New Zealand’s largest city extends from 1995 to the present. The objective of this study was to firstly determine changes in soil parameters (basic soil properties and heavy metals) that were assessed from rural land in 1995-2000 and repeated in 2008-2012. The second objective was to determine differences in soil parameters across various land uses including native bush, rural (horticulture, pasture and plantation forestry) and urban land uses using soil data collected in more recent years (2009- 2013). Across rural land, mean concentrations of Olsen P had significantly increased in the second sampling period and was identified as the indicator of most concern, followed by soil macroporosity, particularly for horticultural and pastoral land. Mean concentrations of Cd were also greatest for pastoral and horticultural land and a positive correlation existed between these two parameters, which highlights the importance of analysing basic soil parameters in conjunction with heavy metals. In contrast, mean concentrations of As, Cr, Pb, Ni and Zn were greatest for urban sites. Native bush sites had the lowest concentrations of heavy metals and were used to calculate a ‘pollution index’ (PI). The mean PI was classified as high (PI > 3) for Cd and Ni and moderate for Pb, Zn, Cr, Cu, As and Hg, indicating high levels of heavy metal pollution across both rural and urban soils. From a land use perspective, the mean ‘integrated pollution index’ was highest for urban sites at 2.9 followed by pasture, horticulture and plantation forests at 2.7, 2.6 and 0.9, respectively. It is recommended that soil sampling continues over time because a longer spanning record will allow further identification of where soil problems exist and where resources need to be targeted in the future. Findings from this study will also inform policy and science direction in regional councils.

Keywords: Heavy metals, Pollution Index, Rural and Urban land use.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2211

Authors: A. D. Parekh, P. R. Tailor

Abstract:

Capacity and efficiency of any refrigerating system diminish rapidly as the difference between the evaporating and condensing temperature is increased by reduction in the evaporator temperature. The single stage vapour compression refrigeration system is limited to an evaporator temperature of -40 0C. Below temperature of -40 0C the either cascade refrigeration system or multi stage vapour compression system is employed. Present work describes thermal design of main three heat exchangers namely condenser (HTS), cascade condenser and evaporator (LTS) of R404A-R508B and R410A-R23 cascade refrigeration system. Heat transfer area of condenser (HTS), cascade condenser and evaporator (LTS) for both systems have been compared and the effect of condensing and evaporating temperature on heat-transfer area for both systems have been studied under same operating condition. The results shows that the required heat-transfer area of condenser and cascade condenser for R410A-R23 cascade system is lower than the R404A-R508B cascade system but heat transfer area of evaporator is similar for both the system. The heat transfer area of condenser and cascade condenser decreases with increase in condensing temperature (Tc), whereas the heat transfer area of cascade condenser and evaporator increases with increase in evaporating temperature (Te).

Keywords: Heat-transfer area, R410A, R404A, R508B, R23, Refrigeration system, Thermal design

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2439

Authors: M. Ishak, K. Yamasaki, K. Maekawa

Abstract:

Magnesium alloys have gained increased attention in recent years in automotive, electronics, and medical industry. This because of magnesium alloys have better properties than aluminum alloys and steels in respects of their low density and high strength to weight ratio. However, the main problems of magnesium alloy welding are the crack formation and the appearance of porosity during the solidification. This paper proposes a unique technique to weld two thin sheets of AZ31B magnesium alloy using a paste containing Ag nanoparticles. The paste containing Ag nanoparticles of 5 nm in average diameter and an organic solvent was used to coat the surface of AZ31B thin sheet. The coated sheet was heated at 100 °C for 60 s to evaporate the solvent. The dried sheet was set as a lower AZ31B sheet on the jig, and then lap fillet welding was carried out by using a pulsed Nd:YAG laser in a closed box filled with argon gas. The characteristics of the microstructure and the corrosion behavior of the joints were analyzed by opticalmicroscopy (OM), energy dispersive spectrometry (EDS), electron probe micro-analyzer (EPMA), scanning electron microscopy (SEM), and immersion corrosion test. The experimental results show that the wrought AZ31B magnesium alloy can be joined successfully using Ag nanoparticles. Ag nanoparticles insert promote grain refinement, narrower the HAZ width and wider bond width compared to weld without and insert. Corrosion rate of welded AZ31B with Ag nanoparticles reduced up to 44 % compared to base metal. The improvement of corrosion resistance of welded AZ31B with Ag nanoparticles due to finer grains and large grain boundaries area which consist of high Al content. β-phase Mg17Al12 could serve as effective barrier and suppressed further propagation of corrosion. Furthermore, Ag distribution in fusion zone provide much more finer grains and may stabilize the magnesium solid solution making it less soluble or less anodic in aqueous

Keywords: Laser welding, magnesium alloys, nanoparticles, mechanical property

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2073

Authors: Fatma El-zahraa El-taher, Ayman Taha, Jane Courtney, Susan Mckeever

Abstract:

Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions is critical to decisions such as crossing roads or selecting safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition  problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset are examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of detection of intersections in satellite images is evaluated.

Keywords: Satellite images, remote sensing images, data acquisition, autonomous vehicles, robot navigation, route planning, road intersections.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 757

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

Abstract:

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

Keywords: Anomaly detection, autoencoder, data centers, deep learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 742

Authors: J. P. Dubois, H. M. Chiu

Abstract:

In this paper, we study statistical multiplexing of VBR video in ATM networks. ATM promises to provide high speed realtime multi-point to central video transmission for telemedicine applications in rural hospitals and in emergency medical services. Video coders are known to produce variable bit rate (VBR) signals and the effects of aggregating these VBR signals need to be determined in order to design a telemedicine network infrastructure capable of carrying these signals. We first model the VBR video signal and simulate it using a generic continuous-data autoregressive (AR) scheme. We carry out the queueing analysis by the Fluid Approximation Model (FAM) and the Markov Modulated Poisson Process (MMPP). The study has shown a trade off: multiplexing VBR signals reduces burstiness and improves resource utilization, however, the buffer size needs to be increased with an associated economic cost. We also show that the MMPP model and the Fluid Approximation model fit best, respectively, the cell region and the burst region. Therefore, a hybrid MMPP and FAM completely characterizes the overall performance of the ATM statistical multiplexer. The ramifications of this technology are clear: speed, reliability (lower loss rate and jitter), and increased capacity in video transmission for telemedicine. With migration to full IP-based networks still a long way to achieving both high speed and high quality of service, the proposed ATM architecture will remain of significant use for telemedicine.

Keywords: ATM, multiplexing, queueing, telemedicine, VBR.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1744

Authors: Atena Sajedin, Shokoufeh Zakernejad, Soheil Faridi, Mehrdad Javadi, Reza Ebrahimpour

Abstract:

This paper illustrates the use of a combined neural network model for classification of electrocardiogram (ECG) beats. We present a trainable neural network ensemble approach to develop customized electrocardiogram beat classifier in an effort to further improve the performance of ECG processing and to offer individualized health care. We process a three stage technique for detection of premature ventricular contraction (PVC) from normal beats and other heart diseases. This method includes a denoising, a feature extraction and a classification. At first we investigate the application of stationary wavelet transform (SWT) for noise reduction of the electrocardiogram (ECG) signals. Then feature extraction module extracts 10 ECG morphological features and one timing interval feature. Then a number of multilayer perceptrons (MLPs) neural networks with different topologies are designed. The performance of the different combination methods as well as the efficiency of the whole system is presented. Among them, Stacked Generalization as a proposed trainable combined neural network model possesses the highest recognition rate of around 95%. Therefore, this network proves to be a suitable candidate in ECG signal diagnosis systems. ECG samples attributing to the different ECG beat types were extracted from the MIT-BIH arrhythmia database for the study.

Keywords: ECG beat Classification; Combining Classifiers;Premature Ventricular Contraction (PVC); Multi Layer Perceptrons;Wavelet Transform

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2216

Authors: A. Chaouachi, R. M. Kamel, K. Nagasaka

Abstract:

This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW Photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three Radial Basis Function Neural Networks (RBFNN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated RBFNN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and non-linear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network.

Keywords: MPPT, neuro-fuzzy, RBFN, grid-connected, photovoltaic.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3182

Authors: Ekesa B. Nakhauka, De Lange M., Macharia I., Garming H., Ouma E., Birachi E., Van Asten P., Van-Lauwe B., Blomme G.

Abstract:

Impact of adopting products promoted by the Consortium for Improving Agriculture-based livelihoods in Central Africa (CIALCA) on food and nutrition security was tested. Multi-stage sampling was used to select 7 project mandate areas, 5 villages/mandate area (stratified into action, satellite and control sites) and 913 households. Structured questionnaires were administered; analysis of impact based on comparison between stratums, differences in means tested by ANOVA and significance of difference obtained by Tukey's HSD multiple rank tests. Perception of adequate food sufficiency received a higher rating in action and satellite sites compared to control sites reason being improved agricultural technologies. For >60% of households, worsened food security was due to climatic conditions. Although a higher proportion of households in action and satellite was meeting calorie RDIs in DRC and Burundi the difference was insignificant from control sites. 53% of respondents in control sites indicated a decrease in intake of protein rich foods, this was significantly higher than the proportion in the action (46%) and satellite (41%) sites.

Keywords: Food security, Farmer-households, Nutrition security

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2018

Authors: Pradyumna Kumar Sahoo, Prasanta Kumar Satpathy

Abstract:

This paper aims at finding a suitable neural network for monitoring congestion level in electrical power systems. In this paper, the input data has been framed properly to meet the target objective through supervised learning mechanism by defining normal and abnormal operating conditions for the system under study. The congestion level, expressed as line congestion index (LCI), is evaluated for each operating condition and is presented to the NN along with the bus voltages to represent the input and target data. Once, the training goes successful, the NN learns how to deal with a set of newly presented data through validation and testing mechanism. The crux of the results presented in this paper rests on performance comparison of a multi-layered feed forward neural network with eleven types of back propagation techniques so as to evolve the best training criteria. The proposed methodology has been tested on the standard IEEE-14 bus test system with the support of MATLAB based NN toolbox. The results presented in this paper signify that the Levenberg-Marquardt backpropagation algorithm gives best training performance of all the eleven cases considered in this paper, thus validating the proposed methodology.

Keywords: Line congestion index, critical bus, contingency, neural network.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1787

Authors: Pavel Pořízka, David Prochazka, Karel Novotný, Ota Samek, ZdeněkPilát, Klára Procházková, and Jozef Kaiser

Abstract:

Themain goal of this article is to find efficient methods for elemental and molecular analysis of living microorganisms (algae) under defined environmental conditions and cultivation processes. The overall knowledge of chemical composition is obtained utilizing laser-based techniques, Laser- Induced Breakdown Spectroscopy (LIBS) for acquiring information about elemental composition and Raman Spectroscopy for gaining molecular information, respectively. Algal cells were suspended in liquid media and characterized using their spectra. Results obtained employing LIBS and Raman Spectroscopy techniques will help to elucidate algae biology (nutrition dynamics depending on cultivation conditions) and to identify algal strains, which have the potential for applications in metal-ion absorption (bioremediation) and biofuel industry. Moreover, bioremediation can be readily combined with production of 3rd generation biofuels. In order to use algae for efficient fuel production, the optimal cultivation parameters have to be determinedleading to high production of oil in selected cellswithout significant inhibition of the photosynthetic activity and the culture growth rate, e.g. it is necessary to distinguish conditions for algal strain containing high amount of higher unsaturated fatty acids. Measurements employing LIBS and Raman Spectroscopy were utilized in order to give information about alga Trachydiscusminutus with emphasis on the amount of the lipid content inside the algal cell and the ability of algae to withdraw nutrients from its environment and bioremediation (elemental composition), respectively. This article can serve as the reference for further efforts in describing complete chemical composition of algal samples employing laserablation techniques.

Keywords: Laser-Induced Breakdown Spectroscopy, Raman Spectroscopy, Algae, Algal strains, Bioremediation, Biofuels.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2250

Authors: Axay J Mehta, Hema A Mehta, T.C.Manjunath, C. Ardil

Abstract:

In this paper, the modelling and design of artificial neural network architecture for load forecasting purposes is investigated. The primary pre-requisite for power system planning is to arrive at realistic estimates of future demand of power, which is known as Load Forecasting. Short Term Load Forecasting (STLF) helps in determining the economic, reliable and secure operating strategies for power system. The dependence of load on several factors makes the load forecasting a very challenging job. An over estimation of the load may cause premature investment and unnecessary blocking of the capital where as under estimation of load may result in shortage of equipment and circuits. It is always better to plan the system for the load slightly higher than expected one so that no exigency may arise. In this paper, a load-forecasting model is proposed using a multilayer neural network with an appropriately modified back propagation learning algorithm. Once the neural network model is designed and trained, it can forecast the load of the power system 24 hours ahead on daily basis and can also forecast the cumulative load on daily basis. The real load data that is used for the Artificial Neural Network training was taken from LDC, Gujarat Electricity Board, Jambuva, Gujarat, India. The results show that the load forecasting of the ANN model follows the actual load pattern more accurately throughout the forecasted period.

Keywords: Power system, Load forecasting, Neural Network, Neuron, Stabilization, Network structure, Load.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3423

Authors: Z. El Felsoufi, L. Azrar

Abstract:

This paper studies a mathematical model based on the integral equations for dynamic analyzes numerical investigations of a non-uniform or multi-material composite beam. The beam is subjected to a sub-tangential follower force and elastic foundation. The boundary conditions are represented by generalized parameterized fixations by the linear and rotary springs. A mathematical formula based on Euler-Bernoulli beam theory is presented for beams with variable cross-sections. The non-uniform section introduces non-uniformity in the rigidity and inertia of beams and consequently, more complicated equilibrium who governs the equation. Using the boundary element method and radial basis functions, the equation of motion is reduced to an algebro-differential system related to internal and boundary unknowns. A generalized formula for the deflection, the slope, the moment and the shear force are presented. The free vibration of non-uniform loaded beams is formulated in a compact matrix form and all needed matrices are explicitly given. The dynamic stability analysis of slender beam is illustrated numerically based on the coalescence criterion. A realistic case related to an industrial chimney is investigated.

Keywords: Chimney, BEM and integral equation formulation, non uniform cross section, vibration and Flutter.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1620

Authors: Sohrab Khanmohammadi, Raana Soltani Zarrin

Abstract:

In this paper, a heuristic method for simultaneous rescue robot path-planning and mission scheduling is introduced based on project management techniques, multi criteria decision making and artificial potential fields path-planning. Groups of injured people are trapped in a disastrous situation. These people are categorized into several groups based on the severity of their situation. A rescue robot, whose ultimate objective is reaching injured groups and providing preliminary aid for them through a path with minimum risk, has to perform certain tasks on its way towards targets before the arrival of rescue team. A decision value is assigned to each target based on the whole degree of satisfaction of the criteria and duties of the robot toward the target and the importance of rescuing each target based on their category and the number of injured people. The resulted decision value defines the strength of the attractive potential field of each target. Dangerous environmental parameters are defined as obstacles whose risk determines the strength of the repulsive potential field of each obstacle. Moreover, negative and positive energies are assigned to the targets and obstacles, which are variable with respects to the factors involved. The simulation results show that the generated path for two cases studies with certain differences in environmental conditions and other risk factors differ considerably.

Keywords: Artificial potential field, GERT, path planning

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1844

Authors: Wenhao Wang, Xinzhi Xu, Limin Feng, Wei Cong

Abstract:

This paper comprehensively investigates current development status of global power grids and fossil energy pipelines (oil and natural gas), proposes a standard visual platform of global power and fossil energy based on Geographic Information System (GIS) technology. In this visual platform, a series of systematic visual models is proposed with global spatial data, systematic energy and power parameters. Under this visual platform, the current Global Power Grids Map and Global Fossil Energy Pipelines Map are plotted within more than 140 countries and regions across the world. Using the multi-scale fusion data processing and modeling methods, the world’s global fossil energy pipelines and power grids information system basic database is established, which provides important data supporting global fossil energy and electricity research. Finally, through the systematic and comparative study of global fossil energy pipelines and global power grids, the general status of global fossil energy and electricity development are reviewed, and energy transition in key areas are evaluated and analyzed. Through the comparison analysis of fossil energy and clean energy, the direction of relevant research is pointed out for clean development and energy transition.

Keywords: Energy Transition, geographic information system, fossil energy, power systems.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 966

Authors: R.Balamurugan, S.Subramanian

Abstract:

This paper presents the solution of power economic dispatch (PED) problem of generating units with valve point effects and multiple fuel options using Self-Adaptive Differential Evolution (SDE) algorithm. The global optimal solution by mathematical approaches becomes difficult for the realistic PED problem in power systems. The Differential Evolution (DE) algorithm is found to be a powerful evolutionary algorithm for global optimization in many real problems. In this paper the key parameters of control in DE algorithm such as the crossover constant CR and weight applied to random differential F are self-adapted. The PED problem formulation takes into consideration of nonsmooth fuel cost function due to valve point effects and multi fuel options of generator. The proposed approach has been examined and tested with the numerical results of PED problems with thirteen-generation units including valve-point effects, ten-generation units with multiple fuel options neglecting valve-point effects and ten-generation units including valve-point effects and multiple fuel options. The test results are promising and show the effectiveness of proposed approach for solving PED problems.

Keywords: Multiple fuels, power economic dispatch, selfadaptivedifferential evolution and valve-point effects.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1895

Authors: A. Abdulkadir, A. A. Okhimamhe, Y. M. Bello, H. Ibrahim, D. H. Makun, M. T. Usman

Abstract:

Household waste form a larger proportion of waste generated across the state, accumulation of organic waste is an apparent problem and the existing dump sites could be overstress. Niger state has abundant arable land and water resources thus should be one of the highest producers of agricultural crops in the country. However, the major challenge to agricultural sector today is loss of soil nutrient coupled with high cost of fertilizer. These have continued to increase the use of fertilizer and decomposed solid waste for enhance agricultural yield, which have varying effects on the soil as well a threat to human livelihood. Consequently, vegetable yield samples from poultry droppings, decomposed household waste manure, NPK treatments and control from each replication were subjected to proximate analysis to determine the nutritional and antinutritional component as well as heavy metal concentration. Data collected was analyzed using SPSS software and Randomized complete Block Design means were compared. The result shows that the treatments do not devoid the concentrations of any nutritional components while the anti-nutritional analysis proved that NPK had higher oxalate content than control and organic treats. The concentration of lead and cadmium are within safe permissible level while the mercury level exceeded the FAO/WHO maximum permissible limit for the entire treatments depicts the need for urgent intervention to minimize mercury levels in soil and manure in order to mitigate its toxic effect. Thus, eco-agriculture should be widely accepted and promoted by the stakeholders for soil amendment, higher yield, strategies for sustainable environmental protection, food security, poverty eradication, attainment of sustainable development and healthy livelihood.

Keywords: Anti-nutritional, healthy livelihood, nutritional waste, organic waste.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1629