Search results for: distribution network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9248

Search results for: distribution network

7598 Computer-Aided Diagnosis of Polycystic Kidney Disease Using ANN

Authors: G. Anjan Babu, G. Sumana, M. Rajasekhar

Abstract:

Many inherited diseases and non-hereditary disorders are common in the development of renal cystic diseases. Polycystic kidney disease (PKD) is a disorder developed within the kidneys in which grouping of cysts filled with water like fluid. PKD is responsible for 5-10% of end-stage renal failure treated by dialysis or transplantation. New experimental models, application of molecular biology techniques have provided new insights into the pathogenesis of PKD. Researchers are showing keen interest for developing an automated system by applying computer aided techniques for the diagnosis of diseases. In this paper a multi-layered feed forward neural network with one hidden layer is constructed, trained and tested by applying back propagation learning rule for the diagnosis of PKD based on physical symptoms and test results of urinanalysis collected from the individual patients. The data collected from 50 patients are used to train and test the network. Among these samples, 75% of the data used for training and remaining 25% of the data are used for testing purpose. Furthermore, this trained network is used to implement for new samples. The output results in normality and abnormality of the patient.

Keywords: dialysis, hereditary, transplantation, polycystic, pathogenesis

Procedia PDF Downloads 374
7597 Comparison between Hardy-Cross Method and Water Software to Solve a Pipe Networking Design Problem for a Small Town

Authors: Ahmed Emad Ahmed, Zeyad Ahmed Hussein, Mohamed Salama Afifi, Ahmed Mohammed Eid

Abstract:

Water has a great importance in life. In order to deliver water from resources to the users, many procedures should be taken by the water engineers. One of the main procedures to deliver water to the community is by designing pressurizer pipe networks for water. The main aim of this work is to calculate the water demand of a small town and then design a simple water network to distribute water resources among the town with the smallest losses. Literature has been mentioned to cover the main point related to water distribution. Moreover, the methodology has introduced two approaches to solve the research problem, one by the iterative method of Hardy-cross and the other by water software Pipe Flow. The results have introduced two main designs to satisfy the same research requirements. Finally, the researchers have concluded that the use of water software provides more abilities and options for water engineers.

Keywords: looping pipe networks, hardy cross networks accuracy, relative error of hardy cross method

Procedia PDF Downloads 159
7596 A Study on Method for Identifying Capacity Factor Declination of Wind Turbines

Authors: Dongheon Shin, Kyungnam Ko, Jongchul Huh

Abstract:

The investigation on wind turbine degradation was carried out using the nacelle wind data. The three Vestas V80-2MW wind turbines of Sungsan wind farm in Jeju Island, South Korea were selected for this work. The SCADA data of the wind farm for five years were analyzed to draw power curve of the turbines. It is assumed that the wind distribution is the Rayleigh distribution to calculate the normalized capacity factor based on the drawn power curve of the three wind turbines for each year. The result showed that the reduction of power output from the three wind turbines occurred every year and the normalized capacity factor decreased to 0.12%/year on average.

Keywords: wind energy, power curve, capacity factor, annual energy production

Procedia PDF Downloads 430
7595 Numerical Simulation of Different Configurations for a Combined Gasification/Carbonization Reactors

Authors: Mahmoud Amer, Ibrahim El-Sharkawy, Shinichi Ookawara, Ahmed Elwardany

Abstract:

Gasification and carbonization are two of the most common ways for biomass utilization. Both processes are using part of the waste to be accomplished, either by incomplete combustion or for heating for both gasification and carbonization, respectively. The focus of this paper is to minimize the part of the waste that is used for heating biomass for gasification and carbonization. This will occur by combining both gasifiers and carbonization reactors in a single unit to utilize the heat in the product biogas to heating up the wastes in the carbonization reactors. Three different designs are proposed for the combined gasification/carbonization (CGC) reactor. These include a parallel combination of two gasifiers and carbonized syngas, carbonizer and combustion chamber, and one gasifier, carbonizer, and combustion chamber. They are tested numerically using ANSYS Fluent Computational Fluid Dynamics to ensure homogeneity of temperature distribution inside the carbonization part of the CGC reactor. 2D simulations are performed for the three cases after performing both mesh-size and time-step independent solutions. The carbonization part is common among the three different cases, and the difference among them is how this carbonization reactor is heated. The simulation results showed that the first design could provide only partial homogeneous temperature distribution, not across the whole reactor. This means that the produced carbonized biomass will be reduced as it will only fill a specified height of the reactor. To keep the carbonized product production high, a series combination is proposed. This series configuration resulted in a uniform temperature distribution across the whole reactor as it has only one source for heat with no temperature distribution on any surface of the carbonization section. The simulations provided a satisfactory result that either the first parallel combination of gasifier and carbonization reactor could be used with a reduced carbonized amount or a series configuration to keep the production rate high.

Keywords: numerical simulation, carbonization, gasification, biomass, reactor

Procedia PDF Downloads 98
7594 Early Prediction of Disposable Addresses in Ethereum Blockchain

Authors: Ahmad Saleem

Abstract:

Ethereum is the second largest crypto currency in blockchain ecosystem. Along with standard transactions, it supports smart contracts and NFT’s. Current research trends are focused on analyzing the overall structure of the network its growth and behavior. Ethereum addresses are anonymous and can be created on fly. The nature of Ethereum network and addresses make it hard to predict their behavior. The activity period of an ethereum address is not much analyzed. Using machine learning we can make early prediction about the disposability of the address. In this paper we analyzed the lifetime of the addresses. We also identified and predicted the disposable addresses using machine learning models and compared the results.

Keywords: blockchain, Ethereum, cryptocurrency, prediction

Procedia PDF Downloads 94
7593 Performance Analysis of Scalable Secure Multicasting in Social Networking

Authors: R. Venkatesan, A. Sabari

Abstract:

Developments of social networking internet scenario are recommended for the requirements of scalable, authentic, secure group communication model like multicasting. Multicasting is an inter network service that offers efficient delivery of data from a source to multiple destinations. Even though multicast has been very successful at providing an efficient and best-effort data delivery service for huge groups, it verified complex process to expand other features to multicast in a scalable way. Separately, the requirement for secure electronic information had become gradually more apparent. Since multicast applications are deployed for mainstream purpose the need to secure multicast communications will become significant.

Keywords: multicasting, scalability, security, social network

Procedia PDF Downloads 289
7592 Stress Analysis of Laminated Cylinders Subject to the Thermomechanical Loads

Authors: Şafak Aksoy, Ali Kurşun, Erhan Çetin, Mustafa Reşit Haboğlu

Abstract:

In this study, thermo elastic stress analysis is performed on a cylinder made of laminated isotropic materials under thermomechanical loads. Laminated cylinders have many applications such as aerospace, automotive and nuclear plant in the industry. These cylinders generally performed under thermomechanical loads. Stress and displacement distribution of the laminated cylinders are determined using by analytical method both thermal and mechanical loads. Based on the results, materials combination plays an important role on the stresses distribution along the radius. Variation of the stresses and displacements along the radius are presented as graphs. Calculations program are prepared using MATLAB® by authors.

Keywords: isotropic materials, laminated cylinders, thermoelastic stress, thermomechanical load

Procedia PDF Downloads 408
7591 Solving the Wireless Mesh Network Design Problem Using Genetic Algorithm and Simulated Annealing Optimization Methods

Authors: Moheb R. Girgis, Tarek M. Mahmoud, Bahgat A. Abdullatif, Ahmed M. Rabie

Abstract:

Mesh clients, mesh routers and gateways are components of Wireless Mesh Network (WMN). In WMN, gateways connect to Internet using wireline links and supply Internet access services for users. We usually need multiple gateways, which takes time and costs a lot of money set up, due to the limited wireless channel bit rate. WMN is a highly developed technology that offers to end users a wireless broadband access. It offers a high degree of flexibility contrasted to conventional networks; however, this attribute comes at the expense of a more complex construction. Therefore, a challenge is the planning and optimization of WMNs. In this paper, we concentrate on this challenge using a genetic algorithm and simulated annealing. The genetic algorithm and simulated annealing enable searching for a low-cost WMN configuration with constraints and determine the number of used gateways. Experimental results proved that the performance of the genetic algorithm and simulated annealing in minimizing WMN network costs while satisfying quality of service. The proposed models are presented to significantly outperform the existing solutions.

Keywords: wireless mesh networks, genetic algorithms, simulated annealing, topology design

Procedia PDF Downloads 456
7590 Modelling a Hospital as a Queueing Network: Analysis for Improving Performance

Authors: Emad Alenany, M. Adel El-Baz

Abstract:

In this paper, the flow of different classes of patients into a hospital is modelled and analyzed by using the queueing network analyzer (QNA) algorithm and discrete event simulation. Input data for QNA are the rate and variability parameters of the arrival and service times in addition to the number of servers in each facility. Patient flows mostly match real flow for a hospital in Egypt. Based on the analysis of the waiting times, two approaches are suggested for improving performance: Separating patients into service groups, and adopting different service policies for sequencing patients through hospital units. The separation of a specific group of patients, with higher performance target, to be served separately from the rest of patients requiring lower performance target, requires the same capacity while improves performance for the selected group of patients with higher target. Besides, it is shown that adopting the shortest processing time and shortest remaining processing time service policies among other tested policies would results in, respectively, 11.47% and 13.75% reduction in average waiting time relative to first come first served policy.

Keywords: queueing network, discrete-event simulation, health applications, SPT

Procedia PDF Downloads 183
7589 Development of Energy Management System Based on Internet of Things Technique

Authors: Wen-Jye Shyr, Chia-Ming Lin, Hung-Yun Feng

Abstract:

The purpose of this study was to develop an energy management system for university campuses based on the Internet of Things (IoT) technique. The proposed IoT technique based on WebAccess is used via network browser Internet Explore and applies TCP/IP protocol. The case study of IoT for lighting energy usage management system was proposed. Structure of proposed IoT technique included perception layer, equipment layer, control layer, application layer and network layer.

Keywords: energy management, IoT technique, sensor, WebAccess

Procedia PDF Downloads 331
7588 Using Two-Mode Network to Access the Connections of Film Festivals

Authors: Qiankun Zhong

Abstract:

In a global cultural context, film festival awards become authorities to define the aesthetic value of films. To study which genres and producing countries are valued by different film festivals and how those evaluations interact with each other, this research explored the interactions between the film festivals through their selection of movies and the factors that lead to the tendency of film festivals to nominate the same movies. To do this, the author employed a two-mode network on the movies that won the highest awards at five international film festivals with the highest attendance in the past ten years (the Venice Film Festival, the Cannes Film Festival, the Toronto International Film Festival, Sundance Film Festival, and the Berlin International Film Festival) and the film festivals that nominated those movies. The title, genre, producing country and language of 50 movies, and the range (regional, national or international) and organizing country or area of 129 film festivals were collected. These created networks connected by nominating the same films and awarding the same movies. The author then assessed the density and centrality of these networks to answer the question: What are the film festivals that tend to have more shared values with other festivals? Based on the Eigenvector centrality of the two-mode network, Palm Springs, Robert Festival, Toronto, Chicago, and San Sebastian are the festivals that tend to nominate commonly appreciated movies. In contrast, Black Movie Film Festival has the unique value of generally not sharing nominations with other film festivals. A homophily test was applied to access the clustering effects of film and film festivals. The result showed that movie genres (E-I index=0.55) and geographic location (E-I index=0.35) are possible indicators of film festival clustering. A blockmodel was also created to examine the structural roles of the film festivals and their meaning in real-world context. By analyzing the same blocks with film festival attributes, it was identified that film festivals either organized in the same area, with the same history, or with the same attitude on independent films would occupy the same structural roles in the network. Through the interpretation of the blocks, language was identified as an indicator that contributes to the role position of a film festival. Comparing the result of blockmodeling in the different periods, it is seen that international film festivals contrast with the Hollywood industry’s dominant value. The structural role dynamics provide evidence for a multi-value film festival network.

Keywords: film festivals, film studies, media industry studies, network analysis

Procedia PDF Downloads 312
7587 Statistical Modeling of Constituents in Ash Evolved From Pulverized Coal Combustion

Authors: Esam Jassim

Abstract:

Industries using conventional fossil fuels have an interest in better understanding the mechanism of particulate formation during combustion since such is responsible for emission of undesired inorganic elements that directly impact the atmospheric pollution level. Fine and ultrafine particulates have tendency to escape the flue gas cleaning devices to the atmosphere. They also preferentially collect on surfaces in power systems resulting in ascending in corrosion inclination, descending in the heat transfer thermal unit, and severe impact on human health. This adverseness manifests particularly in the regions of world where coal is the dominated source of energy for consumption. This study highlights the behavior of calcium transformation as mineral grains verses organically associated inorganic components during pulverized coal combustion. The influence of existing type of calcium on the coarse, fine and ultrafine mode formation mechanisms is also presented. The impact of two sub-bituminous coals on particle size and calcium composition evolution during combustion is to be assessed. Three mixed blends named Blends 1, 2, and 3 are selected according to the ration of coal A to coal B by weight. Calcium percentage in original coal increases as going from Blend 1 to 3. A mathematical model and a new approach of describing constituent distribution are proposed. Analysis of experiments of calcium distribution in ash is also modeled using Poisson distribution. A novel parameter, called elemental index λ, is introduced as a measuring factor of element distribution. Results show that calcium in ash that originally in coal as mineral grains has index of 17, whereas organically associated calcium transformed to fly ash shown to be best described when elemental index λ is 7. As an alkaline-earth element, calcium is considered the fundamental element responsible for boiler deficiency since it is the major player in the mechanism of ash slagging process. The mechanism of particle size distribution and mineral species of ash particles are presented using CCSEM and size-segregated ash characteristics. Conclusions are drawn from the analysis of pulverized coal ash generated from a utility-scale boiler.

Keywords: coal combustion, inorganic element, calcium evolution, fluid dynamics

Procedia PDF Downloads 331
7586 Automating 2D CAD to 3D Model Generation Process: Wall pop-ups

Authors: Mohit Gupta, Chialing Wei, Thomas Czerniawski

Abstract:

In this paper, we have built a neural network that can detect walls on 2D sheets and subsequently create a 3D model in Revit using Dynamo. The training set includes 3500 labeled images, and the detection algorithm used is YOLO. Typically, engineers/designers make concentrated efforts to convert 2D cad drawings to 3D models. This costs a considerable amount of time and human effort. This paper makes a contribution in automating the task of 3D walls modeling. 1. Detecting Walls in 2D cad and generating 3D pop-ups in Revit. 2. Saving designer his/her modeling time in drafting elements like walls from 2D cad to 3D representation. An object detection algorithm YOLO is used for wall detection and localization. The neural network is trained over 3500 labeled images of size 256x256x3. Then, Dynamo is interfaced with the output of the neural network to pop-up 3D walls in Revit. The research uses modern technological tools like deep learning and artificial intelligence to automate the process of generating 3D walls without needing humans to manually model them. Thus, contributes to saving time, human effort, and money.

Keywords: neural networks, Yolo, 2D to 3D transformation, CAD object detection

Procedia PDF Downloads 142
7585 Non-Linear Finite Element Analysis of Bonded Single Lap Joint in Composite Material

Authors: A. Benhamena, L. Aminallah, A. Aid, M. Benguediab, A. Amrouche

Abstract:

The goal of this work is to analyze the severity of interfacial stress distribution in the single lap adhesive joint under tensile loading. The three-dimensional and non-linear finite element method based on the computation of the peel and shear stresses was used to analyze the fracture behaviour of single lap adhesive joint. The effect of the loading magnitude and the overlap length on the distribution of peel and shear stresses was highlighted. A good correlation was found between the FEM simulations and the analytical results.

Keywords: aluminum 2024-T3 alloy, single-lap adhesive joints, Interface stress distributions, material nonlinear analysis, adhesive, bending moment, finite element method

Procedia PDF Downloads 567
7584 Impact of Reclamation on the Water Exchange in Bohai Bay

Authors: Luyao Liu, Dekui Yuan, Xu Li

Abstract:

As one of the most important bays of China, the water exchange capacity of Bohai Bay can influence the economic development and urbanization of surrounding cities. However, the rapid reclamation has influenced the weak water exchange capacity of this semi-enclosed bay in recent years. This paper sets two hydrodynamic models of Bohai Bay with two shorelines before and after reclamation. The mean value and distribution of Turn-over Time, the distribution of residual current, and the feature of the tracer path are compared. After comparison, it is found that Bohai Bay keeps these characteristics; the spending time of water exchange in the northern is longer than southern, and inshore is longer than offshore. However, the mean water exchange time becomes longer after reclamation. In addition, the material spreading is blocked because of the inwardly extending shorelines, and the direction changed from along the shoreline to towards the center after reclamation.

Keywords: Bohai Bay, water exchange, reclamation, turn-over time

Procedia PDF Downloads 136
7583 Thick Data Analytics for Learning Cataract Severity: A Triplet Loss Siamese Neural Network Model

Authors: Jinan Fiaidhi, Sabah Mohammed

Abstract:

Diagnosing cataract severity is an important factor in deciding to undertake surgery. It is usually conducted by an ophthalmologist or through taking a variety of fundus photography that needs to be examined by the ophthalmologist. This paper carries out an investigation using a Siamese neural net that can be trained with small anchor samples to score cataract severity. The model used in this paper is based on a triplet loss function that takes the ophthalmologist best experience in rating positive and negative anchors to a specific cataract scaling system. This approach that takes the heuristics of the ophthalmologist is generally called the thick data approach, which is a kind of machine learning approach that learn from a few shots. Clinical Relevance: The lens of the eye is mostly made up of water and proteins. A cataract occurs when these proteins at the eye lens start to clump together and block lights causing impair vision. This research aims at employing thick data machine learning techniques to rate the severity of the cataract using Siamese neural network.

Keywords: thick data analytics, siamese neural network, triplet-loss model, few shot learning

Procedia PDF Downloads 105
7582 Assessment of Water Quality Network in Karoon River by Dynamic Programming Approach (DPA)

Authors: M. Nasri Nasrabadi, A. A. Hassani

Abstract:

Karoon is one of the greatest and longest rivers of Iran, which because of the existence of numerous industrial, agricultural centers and drinking usage, has a strategic situation in the west and southwest parts of Iran, and the optimal monitoring of its water quality is an essential and indispensable national issue. Due to financial constraints, water quality monitoring network design is an efficient way to manage water quality. The most crucial part is to find appropriate locations for monitoring stations. Considering the objectives of water usage, we evaluate existing water quality sampling stations of this river. There are several methods for assessment of existing monitoring stations such as Sanders method, multiple criteria decision making and dynamic programming approach (DPA) which DPA opted in this study. The results showed that due to the drinking water quality index out of 20 existing monitoring stations, nine stations should be retained on the river, that include of Gorgor-Band-Ghir of A zone, Dez-Band-Ghir of B zone, Teir, Pole Panjom and Zargan of C zone, Darkhoein, Hafar, Chobade, and Sabonsazi of D zone. In additional, stations of Dez river have the best conditions.

Keywords: DPA, karoon river, network monitoring, water quality, sampling site

Procedia PDF Downloads 373
7581 Relocation of the Air Quality Monitoring Stations Network for Aburrá Valley Based on Local Climatic Zones

Authors: Carmen E. Zapata, José F. Jiménez, Mauricio Ramiréz, Natalia A. Cano

Abstract:

The majority of the urban areas in Latin America face the challenges associated with city planning and development problems, attributed to human, technical, and economical factors; therefore, we cannot ignore the issues related to climate change because the city modifies the natural landscape in a significant way transforming the radiation balance and heat content in the urbanized areas. These modifications provoke changes in the temperature distribution known as “the heat island effect”. According to this phenomenon, we have the need to conceive the urban planning based on climatological patterns that will assure its sustainable functioning, including the particularities of the climate variability. In the present study, it is identified the Local Climate Zones (LCZ) in the Metropolitan Area of the Aburrá Valley (Colombia) with the objective of relocate the air quality monitoring stations as a partial solution to the problem of how to measure representative air quality levels in a city for a local scale, but with instruments that measure in the microscale.

Keywords: air quality, monitoring, local climatic zones, valley, monitoring stations

Procedia PDF Downloads 267
7580 Buckling Behavior of FGM Plates Using a Simplified Shear Deformation Theory

Authors: Mokhtar Bouazza

Abstract:

In this paper, the simplified theory will be used to predict the thermoelastic buckling behavior of rectangular functionally graded plates. The material properties of the functionally graded plates are assumed to vary continuously through the thickness, according to a simple power law distribution of the volume fraction of the constituents. The simplified theory is used to obtain the buckling of the plate under different types of thermal loads. The thermal loads are assumed to be uniform, linear, and non-linear distribution through the thickness. Additional numerical results are presented for FGM plates that show the effects of various parameters on thermal buckling response.

Keywords: buckling, functionally graded, plate, simplified higher-order deformation theory, thermal loading

Procedia PDF Downloads 376
7579 Smart Defect Detection in XLPE Cables Using Convolutional Neural Networks

Authors: Tesfaye Mengistu

Abstract:

Power cables play a crucial role in the transmission and distribution of electrical energy. As the electricity generation, transmission, distribution, and storage systems become smarter, there is a growing emphasis on incorporating intelligent approaches to ensure the reliability of power cables. Various types of electrical cables are employed for transmitting and distributing electrical energy, with cross-linked polyethylene (XLPE) cables being widely utilized due to their exceptional electrical and mechanical properties. However, insulation defects can occur in XLPE cables due to subpar manufacturing techniques during production and cable joint installation. To address this issue, experts have proposed different methods for monitoring XLPE cables. Some suggest the use of interdigital capacitive (IDC) technology for online monitoring, while others propose employing continuous wave (CW) terahertz (THz) imaging systems to detect internal defects in XLPE plates used for power cable insulation. In this study, we have developed models that employ a custom dataset collected locally to classify the physical safety status of individual power cables. Our models aim to replace physical inspections with computer vision and image processing techniques to classify defective power cables from non-defective ones. The implementation of our project utilized the Python programming language along with the TensorFlow package and a convolutional neural network (CNN). The CNN-based algorithm was specifically chosen for power cable defect classification. The results of our project demonstrate the effectiveness of CNNs in accurately classifying power cable defects. We recommend the utilization of similar or additional datasets to further enhance and refine our models. Additionally, we believe that our models could be used to develop methodologies for detecting power cable defects from live video feeds. We firmly believe that our work makes a significant contribution to the field of power cable inspection and maintenance. Our models offer a more efficient and cost-effective approach to detecting power cable defects, thereby improving the reliability and safety of power grids.

Keywords: artificial intelligence, computer vision, defect detection, convolutional neural net

Procedia PDF Downloads 106
7578 Analysis of the IEEE 802.15.4 MAC Parameters to Achive Lower Packet Loss Rates

Authors: Imen Bouazzi

Abstract:

The IEEE-802.15.4 standard utilizes the CSMA-CA mechanism to control nodes access to the shared wireless communication medium. It is becoming the popular choice for various applications of surveillance and control used in wireless sensor network (WSN). The benefit of this standard is evaluated regarding of the packet loss probability who depends on the configuration of IEEE 802.15.4 MAC parameters and the traffic load. Our exigency is to evaluate the effects of various configurable MAC parameters on the performance of beaconless IEEE 802.15.4 networks under different traffic loads, static values of IEEE 802.15.4 MAC parameters (macMinBE, macMaxCSMABackoffs, and macMaxFrame Retries) will be evaluated. To performance analysis, we use ns-2[2] network simulator.

Keywords: WSN, packet loss, CSMA/CA, IEEE-802.15.4

Procedia PDF Downloads 336
7577 A Neural Network System for Predicting the Hardness of Titanium Aluminum Nitrite (TiAlN) Coatings

Authors: Omar M. Elmabrouk

Abstract:

The cutting tool, in the high-speed machining process, is consistently dealing with high localized stress at the tool tip, tip temperature exceeds 800°C and the chip slides along the rake face. These conditions are affecting the tool wear, the cutting tool performances, the quality of the produced parts and the tool life. Therefore, a thin film coating on the cutting tool should be considered to improve the tool surface properties while maintaining its bulks properties. One of the general coating processes in applying thin film for hard coating purpose is PVD magnetron sputtering. In this paper, the prediction of the effects of PVD magnetron sputtering coating process parameters, sputter power in the range of (4.81-7.19 kW), bias voltage in the range of (50.00-300.00 Volts) and substrate temperature in the range of (281.08-600.00 °C), were studied using artificial neural network (ANN). The results were compared with previously published results using RSM model. It was found that the ANN is more accurate in prediction of tool hardness, and hence, it will not only improve the tool life of the tool but also significantly enhances the efficiency of the machining processes.

Keywords: artificial neural network, hardness, prediction, titanium aluminium nitrate coating

Procedia PDF Downloads 551
7576 Schrödinger Equation with Position-Dependent Mass: Staggered Mass Distributions

Authors: J. J. Peña, J. Morales, J. García-Ravelo, L. Arcos-Díaz

Abstract:

The Point canonical transformation method is applied for solving the Schrödinger equation with position-dependent mass. This class of problem has been solved for continuous mass distributions. In this work, a staggered mass distribution for the case of a free particle in an infinite square well potential has been proposed. The continuity conditions as well as normalization for the wave function are also considered. The proposal can be used for dealing with other kind of staggered mass distributions in the Schrödinger equation with different quantum potentials.

Keywords: free particle, point canonical transformation method, position-dependent mass, staggered mass distribution

Procedia PDF Downloads 397
7575 Stereotypical Motor Movement Recognition Using Microsoft Kinect with Artificial Neural Network

Authors: M. Jazouli, S. Elhoufi, A. Majda, A. Zarghili, R. Aalouane

Abstract:

Autism spectrum disorder is a complex developmental disability. It is defined by a certain set of behaviors. Persons with Autism Spectrum Disorders (ASD) frequently engage in stereotyped and repetitive motor movements. The objective of this article is to propose a method to automatically detect this unusual behavior. Our study provides a clinical tool which facilitates for doctors the diagnosis of ASD. We focus on automatic identification of five repetitive gestures among autistic children in real time: body rocking, hand flapping, fingers flapping, hand on the face and hands behind back. In this paper, we present a gesture recognition system for children with autism, which consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using artificial neural network (ANN). The first one uses the Microsoft Kinect sensor, the second one chooses points of interest from the 3D skeleton to characterize the gestures, and the last one proposes a neural connectionist model to perform the supervised classification of data. The experimental results show that our system can achieve above 93.3% recognition rate.

Keywords: ASD, artificial neural network, kinect, stereotypical motor movements

Procedia PDF Downloads 302
7574 Urban Neighborhood Center Location Evaluating Method Based On UNA the GIS Spatial Analysis Tools: Kerman's Neighborhood in Tehran Case

Authors: Sepideh Jabbari Behnam, Shadabeh Gashtasbi Iraei, Elnaz Mohsenin, MohammadAli Aghajani

Abstract:

Urban neighborhoods, as important urban forming cells, play a key role in creating urban texture and integrated form. Nowadays, most of neighborhood divisions are based on urban management systems but without considering social issues and the other aspects of urban life. This can cause problems such as providing inappropriate services for city dwellers, the loss of local identity and etc. In this regard for regenerating of such neighborhoods, it is essential to locate neighborhood centers with appropriate access and services for all residents. The main objective of this article is reaching to the location of neighborhood centers in a way that, most of issues relating to the physical features (such as the form of access network and texture permeability and etc.) and other qualities such as land uses, densities and social and economic features can be done simultaneously. This paper attempts to use methods of spatial analysis in order to surveying spatial structure and space syntax of urban textures and Urban Network Analysis Systems. This can be done by one of GIS toolbars which is named UNA (Urban Network Analysis) with the use of its five functions (include: Reach, Betweenness, Gravity, Closeness, Straightness).These functions were written according to space syntax theory and offer its relating output. This paper tries to locate and evaluate the optimal location of neighborhood centers in order to create local centers. This is done through weighing of each of these functions and taking into account of spatial features.

Keywords: evaluate optimal location, Local centers, location of neighborhood centers, Spatial analysis, Urban network

Procedia PDF Downloads 460
7573 Lee-Carter Mortality Forecasting Method with Dynamic Normal Inverse Gaussian Mortality Index

Authors: Funda Kul, İsmail Gür

Abstract:

Pension scheme providers have to price mortality risk by accurate mortality forecasting method. There are many mortality-forecasting methods constructed and used in literature. The Lee-Carter model is the first model to consider stochastic improvement trends in life expectancy. It is still precisely used. Mortality forecasting is done by mortality index in the Lee-Carter model. It is assumed that mortality index fits ARIMA time series model. In this paper, we propose and use dynamic normal inverse gaussian distribution to modeling mortality indes in the Lee-Carter model. Using population mortality data for Italy, France, and Turkey, the model is forecasting capability is investigated, and a comparative analysis with other models is ensured by some well-known benchmarking criterions.

Keywords: mortality, forecasting, lee-carter model, normal inverse gaussian distribution

Procedia PDF Downloads 356
7572 Metazoan Meiofauna and Their Abundance in Relation to Environmental Variables in the Northern Red Sea

Authors: Hamed A. El-Serehy, Khaled A. Al-Rasheid, Fahad A. Al-Misned

Abstract:

The composition and distribution of the benthic meiofauna assemblages of the Egyptian coasts along the Red Sea are described in relation to abiotic variables. Sediment samples were collected seasonally from twelve stations chosen along the northern part of the Red Sea to observe the meiofaunal community structure, its temporal distribution and horizontal fluctuation in relation to environmental conditions of the Red Sea marine ecosystem. The meiofaunal assemblage in the area of study was well diversified including 140 taxa. The temperature, salinity, pH, dissolved oxygen, and redox potential were measured at the time of collection. The water content of the sediments, total organic matters and chlorophyll a values were determined, and sediment samples were subjected to granulometric analysis. A total of 10 meiofauna taxa were identified, with the meiofauna being primarily represented by nematodes (on annual average from 42% to 84%), harpacticoids, polycheates and ostracodes; and the meiofauna abundances ranging from 41- to 167 ind. / 10 cm2. The meiofaunal population density fluctuated seasonally with a peak of 192.52 ind. / 10 cm2 during summer at station II. The vertical zonation in the distribution of meiofaunal community was significantly correlated with interstitial water, chlorophyll a and total organic matter values. The present study indicates that the existing of well diversified meiofaunal group which can serve as food for higher trophic levels in the Red Sea interstitial environment.

Keywords: benthos, diversity, meiofauna, Red Sea

Procedia PDF Downloads 385
7571 New Kinetic Effects in Spatial Distribution of Electron Flux and Excitation Rates in Glow Discharge Plasmas in Middle and High Pressures

Authors: Kirill D. Kapustin, Mikhail B. Krasilnikov, Anatoly A. Kudryavtsev

Abstract:

Physical formation mechanisms of differential electron fluxes is high pressure positive column gas discharge are discussed. It is shown that the spatial differential fluxes of the electrons are directed both inward and outward depending on the energy relaxation law. In some cases the direction of energy differential flux at intermediate energies (5-10eV) in whole volume, except region near the wall, appeared to be down directed, so electron in this region dissipate more energy than gain from axial electric field. Paradoxical behaviour of electron flux in spatial-energy space is presented.

Keywords: plasma kinetics, electron distribution function, excitation and radiation rates, local and nonlocal EDF

Procedia PDF Downloads 396
7570 Microfluidic Continuous Approaches to Produce Magnetic Nanoparticles with Homogeneous Size Distribution

Authors: Ane Larrea, Victor Sebastian, Manuel Arruebo, Jesus Santamaria

Abstract:

We present a gas-liquid microfluidic system as a reactor to obtain magnetite nanoparticles with an excellent degree of control regarding their crystalline phase, shape and size. Several types of microflow approaches were selected to prevent nanomaterial aggregation and to promote homogenous size distribution. The selected reactor consists of a mixer stage aided by ultrasound waves and a reaction stage using a N2-liquid segmented flow to prevent magnetite oxidation to non-magnetic phases. A milli-fluidic reactor was developed to increase the production rate where a magnetite throughput close to 450 mg/h in a continuous fashion was obtained.

Keywords: continuous production, magnetic nanoparticles, microfluidics, nanomaterials

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7569 Heavy Minerals Distribution in the Recent Stream Sediments of Diyala River Basin, Northeastern Iraq

Authors: Abbas R. Ali, Daroon Hasan Khorsheed

Abstract:

Twenty one samples of stream sediments were collected from the Diyala River Basin (DRB), which represent one of three major tributaries of the Tigris River at northeastern Iraq. This study is concerned with the heavy minerals (HM) analysis in the + 63μ m fraction of the Diyala River sediments, distribution pattern in the various river basin sectors, as well as comparing the present results with previous works.The metastable heavy minerals (epidote, staurolite, garnet) represent more than (30%) Whereas the ultrastable heavy minerals (pyroxene and amphibole) make only about (19 %). Opaques are present in high proportions reaching about (29%) as an average. The ultrastable (zircon, tourmaline, rutile) heavy minerals are the miner constituents (7%) in the sediments.According to the laboratory analytical data of heavy mineral distributions the studied sediments are derived from mafic and ultramafic rocks are found in northeastern Iraq that represent Walash – Nawpordan Series and Mawat complexes in Zagros zones. The presence of zircon and tourmaline in trace amounts may give an indication for the weak role of acidic rocks in the source area whereas the epidote group minerals give an indication for the role of metamorphic rocks.

Keywords: heavy minerals, mineral distribution, recent stream sediment, Diyala river, northeastern Iraq

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