Search results for: random effects model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10037

Search results for: random effects model

1097 Mercury Removing Capacity of Multiwall Carbon Nanotubes as Detected by Cold Vapor Atomic Absorption Spectroscopy: Kinetic & Equilibrium Studies

Authors: Yasser M. Moustafa, Rania E. Morsi, Mohammed Fathy

Abstract:

Multiwall carbon nanotubes, prepared by chemical vapor deposition, have an average diameter of 60-100 nm as shown by High Resolution Transmittance Electron Microscope, HR-TEM. The Multiwall carbon nanotubes (MWCNTs) were further characterized using X-ray Diffraction and Raman Spectroscopy. Mercury uptake capacity of MWCNTs was studied using batch adsorption method at different concentration ranges up to 150 ppm. Mercury concentration (before and after the treatment) was measured using cold vapor atomic absorption spectroscopy. The effect of time, concentration, pH and adsorbent dose were studied. MWCNT were found to perform complete absorption in the sub-ppm concentrations (parts per billion levels) while for high concentrations, the adsorption efficiency was 92% at the optimum conditions; 0.1 g of the adsorbent at 150 ppm mercury (II) solution. The adsorption of mercury on MWCNTs was found to follow the Freundlich adsorption isotherm and the pseudo-second order kinetic model.

Keywords: Cold Vapor Atomic Absorption Spectroscopy, Hydride System, Mercury Removing, Multi Wall Carbon Nanotubes.

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1096 Using 3-Glycidoxypropyltrimethoxysilane Functionalized SiO2 Nanoparticles to Improve Flexural Properties of Glass Fibers/Epoxy Grid-Stiffened Composite Panels

Authors: Reza Eslami-Farsani, Hamed Khosravi, Saba Fayazzadeh

Abstract:

Lightweight and efficient structures have the aim to enhance the efficiency of the components in various industries. Toward this end, composites are one of the most widely used materials because of durability, high strength and modulus, and low weight. One type of the advanced composites is grid-stiffened composite (GSC) structures, which have been extensively considered in aerospace, automotive, and aircraft industries. They are one of the top candidates for replacing some of the traditional components, which are used here. Although there are a good number of published surveys on the design aspects and fabrication of GSC structures, little systematic work has been reported on their material modification to improve their properties, to our knowledge. Matrix modification using nanoparticles is an effective method to enhance the flexural properties of the fibrous composites. In the present study, a silanecoupling agent (3-glycidoxypropyltrimethoxysilane/3-GPTS) was introduced onto the silica (SiO2) nanoparticle surface and its effects on the three-point flexural response of isogrid E-glass/epoxy composites were assessed. Based on the Fourier Transform Infrared Spectrometer (FTIR) spectra, it was inferred that the 3-GPTS coupling agent was successfully grafted onto the surface of SiO2 nanoparticles after modification. Flexural test revealed an improvement of 16%, 14%, and 36% in stiffness, maximum load and energy absorption of the isogrid specimen filled with 3 wt.% 3- GPTS/SiO2 compared to the neat one. It would be worth mentioning that in these structures, considerable energy absorption was observed after the primary failure related to the load peak. In addition, 3- GPTMS functionalization had a positive effect on the flexural behavior of the multiscale isogrid composites. In conclusion, this study suggests that the addition of modified silica nanoparticles is a promising method to improve the flexural properties of the gridstiffened fibrous composite structures.

Keywords: Isogrid-stiffened composite panels, silica nanoparticles, surface modification, flexural properties.

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1095 Asymptotic Analysis of Instant Messaging Service with Relay Nodes

Authors: Muhammad T. Alam, Zheng Da Wu

Abstract:

In this paper, we provide complete end-to-end delay analyses including the relay nodes for instant messages. Message Session Relay Protocol (MSRP) is used to provide congestion control for large messages in the Instant Messaging (IM) service. Large messages are broken into several chunks. These chunks may traverse through a maximum number of two relay nodes before reaching destination according to the IETF specification of the MSRP relay extensions. We discuss the current solutions of sending large instant messages and introduce a proposal to reduce message flows in the IM service. We consider virtual traffic parameter i.e., the relay nodes are stateless non-blocking for scalability purpose. This type of relay node is also assumed to have input rate at constant bit rate. We provide a new scheduling policy that schedules chunks according to their previous node?s delivery time stamp tags. Validation and analysis is shown for such scheduling policy. The performance analysis with the model introduced in this paper is simple and straight forward, which lead to reduced message flows in the IM service.

Keywords: Instant messaging, stateless, chunking, MSRP.

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1094 Order Optimization of a Telecommunication Distribution Center through Service Lead Time

Authors: Tamás Hartványi, Ferenc Tóth

Abstract:

European telecommunication distribution center performance is measured by service lead time and quality. Operation model is CTO (customized to order) namely, a high mix customization of telecommunication network equipment and parts. CTO operation contains material receiving, warehousing, network and server assembly to order and configure based on customer specifications. Variety of the product and orders does not support mass production structure. One of the success factors to satisfy customer is to have a proper aggregated planning method for the operation in order to have optimized human resources and highly efficient asset utilization. Research will investigate several methods and find proper way to have an order book simulation where practical optimization problem may contain thousands of variables and the simulation running times of developed algorithms were taken into account with high importance. There are two operation research models that were developed, customer demand is given in orders, no change over time, customer demands are given for product types, and changeover time is constant.

Keywords: CTO, aggregated planning, demand simulation, changeover time.

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1093 Social Media Impact on Startup Entrepreneurial Intention: Evidence from Greece

Authors: Panagiotis I. Mallios, Vassilis S. Moustakis

Abstract:

The research reported herein presents a conceptual model that explores the relationship between social media factors and entrepreneurial intention, with a focus on the Greek startup ecosystem. The significance of the study is that social media gained importance in explaining the entrepreneurial process, and through them, nascent and potential entrepreneurs seem to get inspired and motivated to initiate their businesses. The research methodology employed in this study included a qualitative research approach, utilizing in-depth interviews with a sample of 15 startup entrepreneurs providing valuable retrospective information. The data collected were analyzed using the content analysis method. The major findings of the study are that social media factors such as usefulness, influence, and credibility have a significant impact on entrepreneurial intention. We also found that social media can be a powerful tool for entrepreneurs to access resources, knowledge and networks that can help them in their venture creation. Overall, this research contributes to the entrepreneurship literature by uncovering the relationship between social media factors and entrepreneurial intention and has implications for entrepreneurial education, policymakers, and official partners, highlighting the potential of social media to enhance the startup ecosystem.

Keywords: Entrepreneurial intention, entrepreneurship, social media, startup ecosystem.

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1092 Design of a Service-Enabled Dependable Integration Environment

Authors: Fuyang Peng, Donghong Li

Abstract:

The aim of information systems integration is to make all the data sources, applications and business flows integrated into the new environment so that unwanted redundancies are reduced and bottlenecks and mismatches are eliminated. Two issues have to be dealt with to meet such requirements: the software architecture that supports resource integration, and the adaptor development tool that help integration and migration of legacy applications. In this paper, a service-enabled dependable integration environment (SDIE), is presented, which has two key components, i.e., a dependable service integration platform and a legacy application integration tool. For the dependable platform for service integration, the service integration bus, the service management framework, the dependable engine for service composition, and the service registry and discovery components are described. For the legacy application integration tool, its basic organization, functionalities and dependable measures taken are presented. Due to its service-oriented integration model, the light-weight extensible container, the service component combination-oriented p-lattice structure, and other features, SDIE has advantages in openness, flexibility, performance-price ratio and feature support over commercial products, is better than most of the open source integration software in functionality, performance and dependability support.

Keywords: Application integration, dependability, legacy, SOA.

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1091 Visual Thing Recognition with Binary Scale-Invariant Feature Transform and Support Vector Machine Classifiers Using Color Information

Authors: Wei-Jong Yang, Wei-Hau Du, Pau-Choo Chang, Jar-Ferr Yang, Pi-Hsia Hung

Abstract:

The demands of smart visual thing recognition in various devices have been increased rapidly for daily smart production, living and learning systems in recent years. This paper proposed a visual thing recognition system, which combines binary scale-invariant feature transform (SIFT), bag of words model (BoW), and support vector machine (SVM) by using color information. Since the traditional SIFT features and SVM classifiers only use the gray information, color information is still an important feature for visual thing recognition. With color-based SIFT features and SVM, we can discard unreliable matching pairs and increase the robustness of matching tasks. The experimental results show that the proposed object recognition system with color-assistant SIFT SVM classifier achieves higher recognition rate than that with the traditional gray SIFT and SVM classification in various situations.

Keywords: Color moments, visual thing recognition system, SIFT, color SIFT.

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1090 Modeling, Analysis and Control of a Smart Composite Structure

Authors: Nader H. Ghareeb, Mohamed S. Gaith, Sayed M. Soleimani

Abstract:

In modern engineering, weight optimization has a priority during the design of structures. However, optimizing the weight can result in lower stiffness and less internal damping, causing the structure to become excessively prone to vibration. To overcome this problem, active or smart materials are implemented. The coupled electromechanical properties of smart materials, used in the form of piezoelectric ceramics in this work, make these materials well-suited for being implemented as distributed sensors and actuators to control the structural response. The smart structure proposed in this paper is composed of a cantilevered steel beam, an adhesive or bonding layer, and a piezoelectric actuator. The static deflection of the structure is derived as function of the piezoelectric voltage, and the outcome is compared to theoretical and experimental results from literature. The relation between the voltage and the piezoelectric moment at both ends of the actuator is also investigated and a reduced finite element model of the smart structure is created and verified. Finally, a linear controller is implemented and its ability to attenuate the vibration due to the first natural frequency is demonstrated.

Keywords: Active linear control, Lyapunov stability theorem, piezoelectricity, smart structure, static deflection.

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1089 Material Properties Evolution Affecting Demisability for Space Debris Mitigation

Authors: Chetan Mahawar, Sarath Chandran, Sridhar Panigrahi, V. P. Shaji

Abstract:

The ever-growing advancement in space exploration has led to an alarming concern for space debris removal as it restricts further launch operations and adventurous space missions; hence various technologies and methods are explored for re-entry predictions and material selection processes for mitigating space debris. The selection of material and operating conditions is determined with the objective of lightweight structure and ability to demise faster subject to spacecraft survivability during its mission. The various evolving thermal material properties such as emissivity, specific heat capacity, thermal conductivity, radiation intensity, etc. affect demisability of spacecraft. Thus, this paper presents the analysis of evolving thermal material properties of spacecraft, which affect the demisability process and thus estimate demise time using the demisability model by incorporating evolving thermal properties for sensible heating followed by the complete or partial break-up of spacecraft. The demisability analysis thus concludes that the best suitable spacecraft material is based on the least estimated demise time, which fulfills the criteria of design-for-survivability and as well as of design-for-demisability.

Keywords: Demisability, emissivity, lightweight, re-entry, survivability.

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1088 Advanced Neural Network Learning Applied to Pulping Modeling

Authors: Z. Zainuddin, W. D. Wan Rosli, R. Lanouette, S. Sathasivam

Abstract:

This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of pulping problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified odified problem M-1 Ax= M-1b where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.

Keywords: Convergence, pulping modeling, neural networks, preconditioned conjugate gradient.

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1087 Influence of Thermo-fluid-dynamic Parameters on Fluidics in an Expanding Thermal Plasma Deposition Chamber

Authors: G. Zuppardi, F. Romano

Abstract:

Technology of thin film deposition is of interest in many engineering fields, from electronic manufacturing to corrosion protective coating. A typical deposition process, like that developed at the University of Eindhoven, considers the deposition of a thin, amorphous film of C:H or of Si:H on the substrate, using the Expanding Thermal arc Plasma technique. In this paper a computing procedure is proposed to simulate the flow field in a deposition chamber similar to that at the University of Eindhoven and a sensitivity analysis is carried out in terms of: precursor mass flow rate, electrical power, supplied to the torch and fluid-dynamic characteristics of the plasma jet, using different nozzles. To this purpose a deposition chamber similar in shape, dimensions and operating parameters to the above mentioned chamber is considered. Furthermore, a method is proposed for a very preliminary evaluation of the film thickness distribution on the substrate. The computing procedure relies on two codes working in tandem; the output from the first code is the input to the second one. The first code simulates the flow field in the torch, where Argon is ionized according to the Saha-s equation, and in the nozzle. The second code simulates the flow field in the chamber. Due to high rarefaction level, this is a (commercial) Direct Simulation Monte Carlo code. Gas is a mixture of 21 chemical species and 24 chemical reactions from Argon plasma and Acetylene are implemented in both codes. The effects of the above mentioned operating parameters are evaluated and discussed by 2-D maps and profiles of some important thermo-fluid-dynamic parameters, as per Mach number, velocity and temperature. Intensity, position and extension of the shock wave are evaluated and the influence of the above mentioned test conditions on the film thickness and uniformity of distribution are also evaluated.

Keywords: Deposition chamber, Direct Simulation Mote Carlo method (DSMC), Plasma chemistry, Rarefied gas dynamics.

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1086 Optimal Economic Restructuring Aimed at an Increase in GDP Constrained by a Decrease in Energy Consumption and CO2 Emissions

Authors: Alexander Y. Vaninsky

Abstract:

The objective of this paper is finding the way of economic restructuring - that is, change in the shares of sectoral gross outputs - resulting in the maximum possible increase in the gross domestic product (GDP) combined with decreases in energy consumption and CO2 emissions. It uses an input-output model for the GDP and factorial models for the energy consumption and CO2 emissions to determine the projection of the gradient of GDP, and the antigradients of the energy consumption and CO2 emissions, respectively, on a subspace formed by the structure-related variables. Since the gradient (antigradient) provides a direction of the steepest increase (decrease) of the objective function, and their projections retain this property for the functions' limitation to the subspace, each of the three directional vectors solves a particular problem of optimal structural change. In the next step, a type of factor analysis is applied to find a convex combination of the projected gradient and antigradients having maximal possible positive correlation with each of the three. This convex combination provides the desired direction of the structural change. The national economy of the United States is used as an example of applications.

Keywords: Economic restructuring, Input-Output analysis, Divisia index, Factorial decomposition, E3 models.

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1085 Heat Transfer to Laminar Flow over a Double Backward-Facing Step

Authors: Hussein Togun, Tuqa Abdulrazzaq, S. N. Kazi, A. Badarudin, M. K. A. Ariffin

Abstract:

Heat transfer and laminar air flow over a double backward-facing step numerically studied in this paper. The simulations was performed by using ANSYS ICEM for meshing process and using ANSYS fluent 14 (CFD) for solving. The k-ɛ standard model adopted with Reynolds number varied between 98.5 to 512 and three step height at constant heat flux (q=2000 W/m2). The top of wall and bottom of upstream are insulated with bottom of downstream is heated. The results show increase in Nusselt number with increases of Reynolds number for all cases and the maximum of Nusselt number happens at the first step in compared to the second step. Due to increase of cross section area of downstream to generate sudden expansion then Nusselt number decrease but the profile of Nusselt number keep same trend for all cases where increase after the first and second steps. Recirculation region after the first and second steps are denoted by contour of streamline velocity. The higher augmentation of heat transfer rate observed for case 1 at Reynolds number of 512 and heat flux q=2000 W/m2.

Keywords: Laminar flow, Double backward, Separation flow, Recirculation flow.

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1084 Performance Improvement of Information System of a Banking System Based on Integrated Resilience Engineering Design

Authors: S. H. Iranmanesh, L. Aliabadi, A. Mollajan

Abstract:

Integrated resilience engineering (IRE) is capable of returning banking systems to the normal state in extensive economic circumstances. In this study, information system of a large bank (with several branches) is assessed and optimized under severe economic conditions. Data envelopment analysis (DEA) models are employed to achieve the objective of this study. Nine IRE factors are considered to be the outputs, and a dummy variable is defined as the input of the DEA models. A standard questionnaire is designed and distributed among executive managers to be considered as the decision-making units (DMUs). Reliability and validity of the questionnaire is examined based on Cronbach's alpha and t-test. The most appropriate DEA model is determined based on average efficiency and normality test. It is shown that the proposed integrated design provides higher efficiency than the conventional RE design. Results of sensitivity and perturbation analysis indicate that self-organization, fault tolerance, and reporting culture respectively compose about 50 percent of total weight.

Keywords: Banking system, data envelopment analysis, DEA, integrated resilience engineering, IRE, performance evaluation, perturbation analysis.

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1083 Simulating Climate Change (Temperature and Soil Moisture) in a Mixed-Deciduous Forest, Ontario, Canada

Authors: David Goldblum, Lesley S. Rigg

Abstract:

To simulate expected climate change, we implemented a two-factor (temperature and soil moisture) field design in a forest in Ontario, Canada. To manipulate moisture input, we erected rain-exclusion structures. Under each structure, plots were watered with one of three treatments and thermally controlled with three heat treatments to simulate changes in air temperature and rainfall based on the climate model (GCM) predictions for the study area. Environmental conditions (including untreated controls) were monitored tracking air temperature, soil temperature, soil moisture, and photosynthetically active radiation. We measured rainfall and relative humidity at the site outside the rain-exclusion structures. Analyses of environmental conditions demonstrates that the temperature manipulation was most effective at maintaining target temperature during the early part of the growing season, but it was more difficult to keep the warmest treatment at 5º C above ambient by late summer. Target moisture regimes were generally achieved however incoming solar radiation was slightly attenuated by the structures.

Keywords: Acer saccharum, climate change, forest, environmental manipulation.

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1082 Facial Expressions Recognition from Complex Background using Face Context and Adaptively Weighted sub-Pattern PCA

Authors: Md. Zahangir Alom, Mei-Lan Piao, Md. Ashraful Alam, Nam Kim, Jae-Hyeung Park

Abstract:

A new approach for facial expressions recognition based on face context and adaptively weighted sub-pattern PCA (Aw-SpPCA) has been presented in this paper. The facial region and others part of the body have been segmented from the complex environment based on skin color model. An algorithm has been proposed to accurate detection of face region from the segmented image based on constant ratio of height and width of face (δ= 1.618). The paper also discusses on new concept to detect the eye and mouth position. The desired part of the face has been cropped to analysis the expression of a person. Unlike PCA based on a whole image pattern, Aw-SpPCA operates directly on its sub patterns partitioned from an original whole pattern and separately extracts features from them. Aw-SpPCA can adaptively compute the contributions of each part and a classification task in order to enhance the robustness to both expression and illumination variations. Experiments on single standard face with five types of facial expression database shows that the proposed method is competitive.

Keywords: Aw-SpPC, Expressoin Recognition, Face context, Face Detection, PCA

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1081 A Hidden Markov Model-Based Isolated and Meaningful Hand Gesture Recognition

Authors: Mahmoud Elmezain, Ayoub Al-Hamadi, Jörg Appenrodt, Bernd Michaelis

Abstract:

Gesture recognition is a challenging task for extracting meaningful gesture from continuous hand motion. In this paper, we propose an automatic system that recognizes isolated gesture, in addition meaningful gesture from continuous hand motion for Arabic numbers from 0 to 9 in real-time based on Hidden Markov Models (HMM). In order to handle isolated gesture, HMM using Ergodic, Left-Right (LR) and Left-Right Banded (LRB) topologies is applied over the discrete vector feature that is extracted from stereo color image sequences. These topologies are considered to different number of states ranging from 3 to 10. A new system is developed to recognize the meaningful gesture based on zero-codeword detection with static velocity motion for continuous gesture. Therefore, the LRB topology in conjunction with Baum-Welch (BW) algorithm for training and forward algorithm with Viterbi path for testing presents the best performance. Experimental results show that the proposed system can successfully recognize isolated and meaningful gesture and achieve average rate recognition 98.6% and 94.29% respectively.

Keywords: Computer Vision & Image Processing, Gesture Recognition, Pattern Recognition, Application

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1080 Study the Efficacies of Green Manure Application as Chickpea Pre Plant

Authors: Khosro Mohammadi, Amir Ghalavand, Majid Aghaalikhani

Abstract:

In order to Study the efficacy application of green manure as chickpea pre plant, field experiments were carried out in 2007 and 2008 growing seasons. In this research the effects of different strategies for soil fertilization were investigated on grain yield and yield component, minerals, organic compounds and cooking time of chickpea. Experimental units were arranged in splitsplit plots based on randomized complete blocks with three replications. Main plots consisted of (G1): establishing a mixed vegetation of Vicia panunica and Hordeum vulgare and (G2): control, as green manure levels. Also, five strategies for obtaining the base fertilizer requirement including (N1): 20 t.ha-1 farmyard manure; (N2): 10 t.ha-1 compost; (N3): 75 kg.ha-1 triple super phosphate; (N4): 10 t.ha-1 farmyard manure + 5 t.ha-1 compost and (N5): 10 t.ha-1 farmyard manure + 5 t.ha-1 compost + 50 kg.ha-1 triple super phosphate were considered in sub plots. Furthermoree four levels of biofertilizers consisted of (B1): Bacillus lentus + Pseudomonas putida; (B2): Trichoderma harzianum; (B3): Bacillus lentus + Pseudomonas putida + Trichoderma harzianum; and (B4): control (without biofertilizers) were arranged in sub-sub plots. Results showed that integrating biofertilizers (B3) and green manure (G1) produced the highest grain yield. The highest amounts of yield were obtained in G1×N5 interaction. Comparison of all 2-way and 3-way interactions showed that G1N5B3 was determined as the superior treatment. Significant increasing of N, P2O5, K2O, Fe and Mg content in leaves and grains emphasized on superiority of mentioned treatment because each one of these nutrients has an approved role in chlorophyll synthesis and photosynthesis abilities of the crops. The combined application of compost, farmyard manure and chemical phosphorus (N5) in addition to having the highest yield, had the best grain quality due to high protein, starch and total sugar contents, low crude fiber and reduced cooking time.

Keywords: chickpea, biofertilizer, nitrogen fixation.

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1079 Blockchain for IoT Security and Privacy in Healthcare Sector

Authors: Umair Shafique, Hafiz Usman Zia, Fiaz Majeed, Samina Naz, Javeria Ahmed, Maleeha Zainab

Abstract:

The Internet of Things (IoT) has become a hot topic for the last couple of years. This innovative technology has shown promising progress in various areas and the world has witnessed exponential growth in multiple application domains. Researchers are working to investigate its aptitudes to get the best from it by harnessing its true potential. But at the same time, IoT networks open up a new aspect of vulnerability and physical threats to data integrity, privacy, and confidentiality. It is due to centralized control, data silos approach for handling information, and a lack of standardization in the IoT networks. As we know, blockchain is a new technology that involves creating secure distributed ledgers to store and communicate data. Some of the benefits include resiliency, integrity, anonymity, decentralization, and autonomous control. The potential for blockchain technology to provide the key to managing and controlling IoT has created a new wave of excitement around the idea of putting that data back into the hands of the end-users. In this manuscript, we have proposed a model that combines blockchain and IoT networks to address potential security and privacy issues in the healthcare domain and how various stakeholders will interact with the system.

Keywords: Internet of Things, IoT, blockchain, data integrity, authentication, data privacy.

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1078 Aerodynamics and Optimization of Airfoil Under Ground Effect

Authors: Kyoungwoo Park, Byeong Sam Kim, Juhee Lee, Kwang Soo Kim

Abstract:

The Prediction of aerodynamic characteristics and shape optimization of airfoil under the ground effect have been carried out by integration of computational fluid dynamics and the multiobjective Pareto-based genetic algorithm. The main flow characteristics around an airfoil of WIG craft are lift force, lift-to-drag ratio and static height stability (H.S). However, they show a strong trade-off phenomenon so that it is not easy to satisfy the design requirements simultaneously. This difficulty can be resolved by the optimal design. The above mentioned three characteristics are chosen as the objective functions and NACA0015 airfoil is considered as a baseline model in the present study. The profile of airfoil is constructed by Bezier curves with fourteen control points and these control points are adopted as the design variables. For multi-objective optimization problems, the optimal solutions are not unique but a set of non-dominated optima and they are called Pareto frontiers or Pareto sets. As the results of optimization, forty numbers of non- dominated Pareto optima can be obtained at thirty evolutions.

Keywords: Aerodynamics, Shape optimization, Airfoil on WIGcraft, Genetic algorithm, Computational fluid dynamics (CFD).

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1077 Studies on Lucrative Design of Waste Heat Recovery System for Air Conditioners

Authors: Ashwin Bala, K. Panthalaraja Kumaran, S. Prithviraj, R. Pradeep, J. Udhayakumar, S. Ajith

Abstract:

In this paper comprehensive studies have been carried out for the design optimization of a waste heat recovery system for effectively utilizing the domestic air conditioner heat energy for producing hot water. Numerical studies have been carried for the geometry optimization of a waste heat recovery system for domestic air conditioners. Numerical computations have been carried out using a validated 2d pressure based, unsteady, 2nd-order implicit, SST k-ω turbulence model. In the numerical study, a fully implicit finite volume scheme of the compressible, Reynolds-Averaged, Navier- Stokes equations is employed. At identical inflow and boundary conditions various geometries were tried and effort has been taken for proposing the best design criteria. Several combinations of pipe line shapes viz., straight and spiral with different number of coils for the radiator have been attempted and accordingly the design criteria has been proposed for the waste heat recovery system design. We have concluded that, within the given envelope, the geometry optimization is a meaningful objective for getting better performance of waste heat recovery system for air conditioners.

Keywords: Air-conditioning system, Energy conversion system, Hot water production from waste heat, Waste heat recovery system.

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1076 Data Mining Techniques in Computer-Aided Diagnosis: Non-Invasive Cancer Detection

Authors: Florin Gorunescu

Abstract:

Diagnosis can be achieved by building a model of a certain organ under surveillance and comparing it with the real time physiological measurements taken from the patient. This paper deals with the presentation of the benefits of using Data Mining techniques in the computer-aided diagnosis (CAD), focusing on the cancer detection, in order to help doctors to make optimal decisions quickly and accurately. In the field of the noninvasive diagnosis techniques, the endoscopic ultrasound elastography (EUSE) is a recent elasticity imaging technique, allowing characterizing the difference between malignant and benign tumors. Digitalizing and summarizing the main EUSE sample movies features in a vector form concern with the use of the exploratory data analysis (EDA). Neural networks are then trained on the corresponding EUSE sample movies vector input in such a way that these intelligent systems are able to offer a very precise and objective diagnosis, discriminating between benign and malignant tumors. A concrete application of these Data Mining techniques illustrates the suitability and the reliability of this methodology in CAD.

Keywords: Endoscopic ultrasound elastography, exploratorydata analysis, neural networks, non-invasive cancer detection.

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1075 An In-Depth Inquiry into the Impact of Poor Teacher-Student Relationships on Chronic Absenteeism in Secondary Schools of West Java Province, Indonesia

Authors: Yenni Anggrayni

Abstract:

The lack of awareness of the significant prevalence of school absenteeism in Indonesia, which ultimately results in high rates of school dropouts, is an unresolved issue. Therefore, this study aims to investigate the root causes of chronic absenteeism qualitatively and quantitatively using the bioecological systems paradigm in secondary schools for any reason. This study used an open-ended questionnaire to collect data from 1,148 students in six West Java Province districts/cities. Univariate and stepwise multiple logistic regression analyses produced a prediction model for the components. Analysis results show that poor teacher-student relationships, bullying by peers or teachers, negative perception of education, and lack of parental involvement in learning activities are the leading causes of chronic absenteeism. Another finding is to promote home-school partnerships to improve school climate and parental involvement in learning to address chronic absenteeism.

Keywords: Bullying, chronic absenteeism, dropout of school, home-school partnerships, parental involvement.

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1074 Adaptive PID Controller based on Reinforcement Learning for Wind Turbine Control

Authors: M. Sedighizadeh, A. Rezazadeh

Abstract:

A self tuning PID control strategy using reinforcement learning is proposed in this paper to deal with the control of wind energy conversion systems (WECS). Actor-Critic learning is used to tune PID parameters in an adaptive way by taking advantage of the model-free and on-line learning properties of reinforcement learning effectively. In order to reduce the demand of storage space and to improve the learning efficiency, a single RBF neural network is used to approximate the policy function of Actor and the value function of Critic simultaneously. The inputs of RBF network are the system error, as well as the first and the second-order differences of error. The Actor can realize the mapping from the system state to PID parameters, while the Critic evaluates the outputs of the Actor and produces TD error. Based on TD error performance index and gradient descent method, the updating rules of RBF kernel function and network weights were given. Simulation results show that the proposed controller is efficient for WECS and it is perfectly adaptable and strongly robust, which is better than that of a conventional PID controller.

Keywords: Wind energy conversion systems, reinforcementlearning; Actor-Critic learning; adaptive PID control; RBF network.

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1073 Ultrasound Therapy: Amplitude Modulation Technique for Tissue Ablation by Acoustic Cavitation

Authors: Fares A. Mayia, Mahmoud A. Yamany, Mushabbab A. Asiri

Abstract:

In recent years, non-invasive Focused Ultrasound (FU) has been utilized for generating bubbles (cavities) to ablate target tissue by mechanical fractionation. Intensities >10 kW/cm2 are required to generate the inertial cavities. The generation, rapid growth, and collapse of these inertial cavities cause tissue fractionation and the process is called Histotripsy. The ability to fractionate tissue from outside the body has many clinical applications including the destruction of the tumor mass. The process of tissue fractionation leaves a void at the treated site, where all the affected tissue is liquefied to particles at sub-micron size. The liquefied tissue will eventually be absorbed by the body. Histotripsy is a promising non-invasive treatment modality. This paper presents a technique for generating inertial cavities at lower intensities (< 1 kW/cm2). The technique (patent pending) is based on amplitude modulation (AM), whereby a low frequency signal modulates the amplitude of a higher frequency FU wave. Cavitation threshold is lower at low frequencies; the intensity required to generate cavitation in water at 10 kHz is two orders of magnitude lower than the intensity at 1 MHz. The Amplitude Modulation technique can operate in both continuous wave (CW) and pulse wave (PW) modes, and the percentage modulation (modulation index) can be varied from 0 % (thermal effect) to 100 % (cavitation effect), thus allowing a range of ablating effects from Hyperthermia to Histotripsy. Furthermore, changing the frequency of the modulating signal allows controlling the size of the generated cavities. Results from in vitro work demonstrate the efficacy of the new technique in fractionating soft tissue and solid calcium carbonate (Chalk) material. The technique, when combined with MR or Ultrasound imaging, will present a precise treatment modality for ablating diseased tissue without affecting the surrounding healthy tissue.

Keywords: Focused ultrasound therapy, Histotripsy, generation of inertial cavitation, mechanical tissue ablation.

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1072 Visualized Flow Patterns around and inside a Two-Sided Wind-Catcher in the Presence of Upstream Structures

Authors: M. Afshin, A. Sohankar, M. Dehghan Manshadi, M. R. Daneshgar, G. R. Dehghan Kamaragi

Abstract:

In this paper, the influence of upstream structures on the flow patternaround and inside the wind-catcher is experimentally investigated by smoke flow visualization techniques. Wind-catchers are an important part of natural ventilation in residential buildings or public places such as shopping centers, libraries, etc. Wind-catchers might be also used in places of high urban densities; hence their potential to provide natural ventilation is dependent on the presence of upstream structures. In this study, the two-sided wind-catcher model was based on a real wind-catcher observed in the city of Yazd, Iran. The present study focuses on the flow patterns around and inside the isolated two-sided wind-catcher, and on a two-sided wind-catcher in the presence of an upstream structure. The results show that the presence of an upstream structure influences the airflow pattern force and direction. Placing a high upstream structure reverses the airflow direction inside the wind-catcher.

Keywords: Natural Ventilation, Smoke Flow Visualization, Two-Sided Wind-Catcher.

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1071 An Efficient Architecture for Dynamic Customization and Provisioning of Virtual Appliance in Cloud Environment

Authors: Rajendar Kandan, Mohammad Zakaria Alli, Hong Ong

Abstract:

Cloud computing is a business model which provides an easier management of computing resources. Cloud users can request virtual machine and install additional softwares and configure them if needed. However, user can also request virtual appliance which provides a better solution to deploy application in much faster time, as it is ready-built image of operating system with necessary softwares installed and configured. Large numbers of virtual appliances are available in different image format. User can download available appliances from public marketplace and start using it. However, information published about the virtual appliance differs from each providers leading to the difficulty in choosing required virtual appliance as it is composed of specific OS with standard software version. However, even if user choses the appliance from respective providers, user doesn’t have any flexibility to choose their own set of softwares with required OS and application. In this paper, we propose a referenced architecture for dynamically customizing virtual appliance and provision them in an easier manner. We also add our experience in integrating our proposed architecture with public marketplace and Mi-Cloud, a cloud management software.

Keywords: Cloud computing, marketplace, virtualization, virtual appliance.

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1070 Studies on Microstructure and Mechanical Properties of Simulated Heat Affected Zone in a Micro Alloyed Steel

Authors: Sanjeev Kumar, S. K. Nath

Abstract:

Proper selection of welding parameters for getting excellent weld is a challenge. HAZ simulation helps in identifying suitable welding parameters like heating rate, cooling rate, peak temperature, and energy input. In this study, the influence of weld thermal cycle of heat affected zone (HAZ) is simulated for Submerged Arc Welding (SAW) using Gleeble ® 3800 thermomechanical simulator. A (Micro-alloyed) MA steel plate of thickness 18 mm having yield strength 450MPa is used for making test specimens. Determination of the mechanical properties of weld simulated specimens including Charpy V-notch toughness and hardness is performed. Peak temperatures of 1300°C, 1150°C, 1000°C, 900°C, 800°C, heat energy input of 22KJ/cm and preheat temperatures of 30°C have been used with Rykalin-3D simulation model. It is found that the impact toughness (75J) is the best for the simulated HAZ specimen at the peak temperature 900ºC. For parent steel, impact toughness value is 26.8J at -50°C in transverse direction.

Keywords: HAZ Simulation, Mechanical Properties, Peak Temperature, Ship hull steel, and Weldability.

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1069 A Novel Approach to Handle Uncertainty in Health System Variables for Hospital Admissions

Authors: Manisha Rathi, Thierry Chaussalet

Abstract:

Hospital staff and managers are under pressure and concerned for effective use and management of scarce resources. The hospital admissions require many decisions that have complex and uncertain consequences for hospital resource utilization and patient flow. It is challenging to predict risk of admissions and length of stay of a patient due to their vague nature. There is no method to capture the vague definition of admission of a patient. Also, current methods and tools used to predict patients at risk of admission fail to deal with uncertainty in unplanned admission, LOS, patients- characteristics. The main objective of this paper is to deal with uncertainty in health system variables, and handles uncertain relationship among variables. An introduction of machine learning techniques along with statistical methods like Regression methods can be a proposed solution approach to handle uncertainty in health system variables. A model that adapts fuzzy methods to handle uncertain data and uncertain relationships can be an efficient solution to capture the vague definition of admission of a patient.

Keywords: Admission, Fuzzy, Regression, Uncertainty

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1068 Yield and Sward Composition Responses of Natural Grasslands to Treatments Meeting Sustainability

Authors: D. Díaz Fernández, I. Csízi, K. Pető, G. Nagy

Abstract:

An outstanding part of the animal products are based on the grasslands, due to the fact that the grassland ecosystems can be found all over the globe. In places where economical and successful crop production cannot be managed, the grassland based animal husbandry can be an efficient way of food production. In addition, these ecosystems have an important role in carbon sequestration, and with their rich flora – and fauna connected to it – in conservation of biodiversity. The protection of nature, and the sustainable agriculture is getting more and more attention in the European Union, but, looking at the consumers’ needs, the production of healthy food cannot be neglected either. Because of these facts, the effects of two specific composts - which are officially authorized in organic farming, in Agri-environment Schemes and Natura 2000 programs – on grass yields and sward compositions were investigated in a field trial. The investigation took place in Hungary, on a natural grassland based on solonetz soil. Three rates of compost (10 t/ha, 20 t/ha, 30 t/ha) were tested on 3 m X 10 m experimental plots. Every treatment had four replications and both type of compost had four-four control plots too, this way 32 experimental plots were included in the investigations. The yield of the pasture was harvested two-times (in May and in September) and before cutting the plots, measurements on botanical compositions were made. Samples for laboratory analysis were also taken. Dry matter yield of pasture showed positive responses to the rates of composts. The increase in dry matter yield was partly due to some positive changes in sward composition. It means that the proportions of grass species with higher yield potential increased in ground cover of the sward without depressing out valuable native species of diverse natural grasslands. The research results indicate that the use of organic compost can be an efficient way to increase grass yields in a sustainable way.

Keywords: Compost application, crude protein content, dry matter yield, native grassland, sward composition.

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