Search results for: hybrid recommendation systems
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10613

Search results for: hybrid recommendation systems

10373 Deep Reinforcement Learning with Leonard-Ornstein Processes Based Recommender System

Authors: Khalil Bachiri, Ali Yahyaouy, Nicoleta Rogovschi

Abstract:

Improved user experience is a goal of contemporary recommender systems. Recommender systems are starting to incorporate reinforcement learning since it easily satisfies this goal of increasing a user’s reward every session. In this paper, we examine the most effective Reinforcement Learning agent tactics on the Movielens (1M) dataset, balancing precision and a variety of recommendations. The absence of variability in final predictions makes simplistic techniques, although able to optimize ranking quality criteria, worthless for consumers of the recommendation system. Utilizing the stochasticity of Leonard-Ornstein processes, our suggested strategy encourages the agent to investigate its surroundings. Research demonstrates that raising the NDCG (Discounted Cumulative Gain) and HR (HitRate) criterion without lowering the Ornstein-Uhlenbeck process drift coefficient enhances the diversity of suggestions.

Keywords: recommender systems, reinforcement learning, deep learning, DDPG, Leonard-Ornstein process

Procedia PDF Downloads 109
10372 An Approach to Building a Recommendation Engine for Travel Applications Using Genetic Algorithms and Neural Networks

Authors: Adrian Ionita, Ana-Maria Ghimes

Abstract:

The lack of features, design and the lack of promoting an integrated booking application are some of the reasons why most online travel platforms only offer automation of old booking processes, being limited to the integration of a smaller number of services without addressing the user experience. This paper represents a practical study on how to improve travel applications creating user-profiles through data-mining based on neural networks and genetic algorithms. Choices made by users and their ‘friends’ in the ‘social’ network context can be considered input data for a recommendation engine. The purpose of using these algorithms and this design is to improve user experience and to deliver more features to the users. The paper aims to highlight a broader range of improvements that could be applied to travel applications in terms of design and service integration, while the main scientific approach remains the technical implementation of the neural network solution. The motivation of the technologies used is also related to the initiative of some online booking providers that have made the fact that they use some ‘neural network’ related designs public. These companies use similar Big-Data technologies to provide recommendations for hotels, restaurants, and cinemas with a neural network based recommendation engine for building a user ‘DNA profile’. This implementation of the ‘profile’ a collection of neural networks trained from previous user choices, can improve the usability and design of any type of application.

Keywords: artificial intelligence, big data, cloud computing, DNA profile, genetic algorithms, machine learning, neural networks, optimization, recommendation system, user profiling

Procedia PDF Downloads 141
10371 Real-Time Hybrid Simulation for a Tuned Liquid Column Damper Implementation

Authors: Carlos Riascos, Peter Thomson

Abstract:

Real-time hybrid simulation (RTHS) is a modern cyber-physical technique used for the experimental evaluation of complex systems, that treats the system components with predictable behavior as a numerical substructure and the components that are difficult to model as an experimental substructure. Therefore it is an attractive method for evaluation of the response of civil structures under earthquake, wind and anthropic loads. Another practical application of RTHS is the evaluation of control systems, as these devices are often nonlinear and their characterization is an important step in the design of controllers with the desired performance. In this paper, the response of three-story shear frame controlled by a tuned liquid column damper (TLCD) and subject to base excitation is considered. Both passive and semi-active control strategies were implemented and are compared. While the passive TLCD achieved a reduction of 50% in the acceleration response of the main structure in comparison with the structure without control, the semi-active TLCD achieved a reduction of 70%, and was robust to variations in the dynamic properties of the main structure. In addition, a RTHS was implemented with the main structure modeled as a linear, time-invariant (LTI) system through a state space representation and the TLCD, with both control strategies, was evaluated on a shake table that reproduced the displacement of the virtual structure. Current assessment measures for RTHS were used to quantify the performance with parameters such as generalized amplitude, equivalent time delay between the target and measured displacement of the shake table, and energy error using the measured force, and prove that the RTHS described in this paper is an accurate method for the experimental evaluation of structural control systems.

Keywords: structural control, hybrid simulation, tuned liquid column damper, semi-active sontrol strategy

Procedia PDF Downloads 275
10370 Voltage Stabilization of Hybrid PV and Battery Systems by Considering Temperature and Irradiance Changes in Standalone Operation

Authors: S. Jalilzadeh, S. M. Mohseni Bonab

Abstract:

Solar and battery energy storage systems are very useful for consumers who live in deprived areas and do not have access to electricity distribution networks. Nowadays one of the problems that photo voltaic systems (PV) have changing of output power in temperature and irradiance variations, which directly affects the load that is connected to photo voltaic systems. In this paper, with considering the fact that the solar array varies with change in temperature and solar power radiation, a voltage stabilizer system of a load connected to photo voltaic array is designed to stabilize the load voltage and to transfer surplus power of the battery. Also, in proposed hybrid system, the needed load power amount is supplemented considering the voltage stabilization in standalone operation for supplying unbalanced AC load. Electrical energy storage system for voltage control and improvement of the performance of PV by a DC/DC converter is connected to the DC bus. The load is also feed by an AC/DC converter. In this paper, when the voltage increases in its reference limit, the battery gets charged by the photo voltaic array and when it decreases in its defined limit, the power gets injected to the DC bus by this battery. The constant of DC bus Voltage is the cause for the reduced harmonics generated by the inverter. In addition, a series of filters are provided in the inverter output in to reduced harmonics. The inverter control circuit is designed that the voltage and frequency of the load remain almost constant at different load conditions. This paper has focused on controlling strategies of converters to improve their performance.

Keywords: photovoltaic array (PV), DC/DC Boost converter, battery converter, inverters control

Procedia PDF Downloads 455
10369 Optimal Design of Redundant Hybrid Manipulator for Minimum Singularity

Authors: Arash Rahmani, Ahmad Ghanbari, Abbas Baghernezhad, Babak Safaei

Abstract:

In the design of parallel manipulators, usually mean value of a dexterity measure over the workspace volume is considered as the objective function to be used in optimization algorithms. The mentioned indexes in a hybrid parallel manipulator (HPM) are quite complicated to solve thanks to infinite solutions for every point within the workspace of the redundant manipulators. In this paper, spatial isotropic design axioms are extended as a well-known method for optimum design of manipulators. An upper limit for the isotropy measure of HPM is calculated and instead of computing and minimizing isotropy measure, minimizing the obtained limit is considered. To this end, two different objective functions are suggested which are obtained from objective functions of comprising modules. Finally, by using genetic algorithm (GA), the best geometric parameters for a specific hybrid parallel robot which is composed of two modified Gough-Stewart platforms (MGSP) are achieved.

Keywords: hybrid manipulator, spatial isotropy, genetic algorithm, optimum design

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10368 Methodology of Choosing Technology and Sizing of the Hybrid Energy Storage Based on Cost-benefit Analysis

Authors: Krzysztof Rafał, Weronika Radziszewska, Hubert Biedka, Oskar Grabowski, Krzysztof Mik

Abstract:

We present a method to choose energy storage technologies and their parameters for the economic operation of a microgrid. A grid-connected system with local loads and PV generation is assumed, where an energy storage system (ESS) is attached to minimize energy cost by providing energy balancing and arbitrage functionalities. The ESS operates in a hybrid configuration and consists of two unique technologies operated in a coordinated way. Based on given energy profiles and economical data a model calculates financial flow for ESS investment, including energy cost and ESS depreciation resulting from degradation. The optimization strategy proposes a hybrid set of two technologies with their respective power and energy ratings to minimize overall system cost in a given timeframe. Results are validated through microgrid simulations using real-life input profiles.

Keywords: energy storage, hybrid energy storage, cost-benefit analysis, microgrid, battery sizing

Procedia PDF Downloads 184
10367 Developing a Recommendation Library System based on Android Application

Authors: Kunyanuth Kularbphettong, Kunnika Tenprakhon, Pattarapan Roonrakwit

Abstract:

In this paper, we present a recommendation library application on Android system. The objective of this system is to support and advice user to use library resources based on mobile application. We describe the design approaches and functional components of this system. The system was developed based on under association rules, Apriori algorithm. In this project, it was divided the result by the research purposes into 2 parts: developing the Mobile application for online library service and testing and evaluating the system. Questionnaires were used to measure user satisfaction with system usability by specialists and users. The results were satisfactory both specialists and users.

Keywords: online library, Apriori algorithm, Android application, black box

Procedia PDF Downloads 456
10366 Deep Learning for SAR Images Restoration

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

Procedia PDF Downloads 44
10365 Small Wind Turbine Hybrid System for Remote Application: Egyptian Case Study

Authors: M. A. Badr, A. N. Mohib, M. M. Ibrahim

Abstract:

The objective of this research is to study the technical and economic performance of wind/diesel/battery (W/D/B) system supplying a remote small gathering of six families using HOMER software package. The electrical energy is to cater for the basic needs for which the daily load pattern is estimated. Net Present Cost (NPC) and Cost of Energy (COE) are used as economic criteria, while the measure of performance is % of power shortage. Technical and economic parameters are defined to estimate the feasibility of the system under study. Optimum system configurations are estimated for two sites. Using HOMER software, the simulation results showed that W/D/B systems are economical for the assumed community sites as the price of generated electricity is about 0.308 $/kWh, without taking external benefits into considerations. W/D/B systems are more economical than W/B or diesel alone systems, as the COE is 0.86 $/kWh for W/B and 0.357 $/kWh for diesel alone.

Keywords: optimum energy systems, remote electrification, renewable energy, wind turbine systems

Procedia PDF Downloads 379
10364 Deep Learning Based Polarimetric SAR Images Restoration

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

Procedia PDF Downloads 50
10363 Hybrid Adaptive Modeling to Enhance Robustness of Real-Time Optimization

Authors: Hussain Syed Asad, Richard Kwok Kit Yuen, Gongsheng Huang

Abstract:

Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.

Keywords: energy performance, hybrid adaptive modeling, hybrid genetic algorithms, real-time optimization, heating, ventilation, and air-conditioning

Procedia PDF Downloads 386
10362 Cost-Effective Hybrid Cloud Framework for Higher Educational Institutes

Authors: Shah Muhammad Butt, Ahmed Masaud Ansair

Abstract:

Present financial crisis in Higher Educational Institutes (HEIs) is causing lots of problems such as considerable budget cuts, which makes it difficult to meet the ever growing IT based research and learning needs. Institutions are rapidly planning and promoting cloud based approaches for their academic and research needs. A cost-effective hybrid cloud framework for HEIs will provide educational services for campus or intercampus communication. Hybrid cloud framework comprises private and public cloud approaches. This paper will propose the framework based on the Open Source Cloud (OpenNebula for Virtualization, Eucalyptus for Infrastructure and Aneka for programming development environment) combined with CSPs services which are delivered to the end-user via the internet from public clouds such as Google, Microsoft, Zoho, and Salesforce.

Keywords: educational services, hybrid campus cloud, open source, higher educational institutes

Procedia PDF Downloads 451
10361 A Comparative Study of GTC and PSP Algorithms for Mining Sequential Patterns Embedded in Database with Time Constraints

Authors: Safa Adi

Abstract:

This paper will consider the problem of sequential mining patterns embedded in a database by handling the time constraints as defined in the GSP algorithm (level wise algorithms). We will compare two previous approaches GTC and PSP, that resumes the general principles of GSP. Furthermore this paper will discuss PG-hybrid algorithm, that using PSP and GTC. The results show that PSP and GTC are more efficient than GSP. On the other hand, the GTC algorithm performs better than PSP. The PG-hybrid algorithm use PSP algorithm for the two first passes on the database, and GTC approach for the following scans. Experiments show that the hybrid approach is very efficient for short, frequent sequences.

Keywords: database, GTC algorithm, PSP algorithm, sequential patterns, time constraints

Procedia PDF Downloads 357
10360 Optimal Design of a PV/Diesel Hybrid System for Decentralized Areas through Economic Criteria

Authors: David B. Tsuanyo, Didier Aussel, Yao Azoumah, Pierre Neveu

Abstract:

An innovative concept called “Flexy-Energy”is developing at 2iE. This concept aims to produce electricity at lower cost by smartly mix different available energies sources in accordance to the load profile of the region. With a higher solar irradiation and due to the fact that Diesel generator are massively used in sub-Saharan rural areas, PV/Diesel hybrid systems could be a good application of this concept and a good solution to electrify this region, provided they are reliable, cost effective and economically attractive to investors. Presentation of the developed approach is the aims of this paper. The PV/Diesel hybrid system designed consists to produce electricity and/or heat from a coupling between Diesel gensets and PV panels without batteries storage, while ensuring the substitution of gasoil by bio-fuels available in the area where the system will be installed. The optimal design of this system is based on his technical performances; the Life Cycle Cost (LCC) and Levelized Cost of Energy are developed and use as economic criteria. The Net Present Value (NPV), the internal rate of return (IRR) and the discounted payback (DPB) are also evaluated according to dual electricity pricing (in sunny and unsunny hours). The PV/Diesel hybrid system obtained is compared to the standalone Diesel gensets. The approach carried out in this paper has been applied to Siby village in Mali (Latitude 12 ° 23'N 8 ° 20'W) with 295 kWh as daily demand. This approach provides optimal physical characteristics (size of the components, number of component) and dynamical characteristics in real time (number of Diesel generator on, their load rate, fuel specific consumptions, and PV penetration rate) of the system. The system obtained is slightly cost effective; but could be improved with optimized tariffing strategies.

Keywords: investments criteria, optimization, PV hybrid, sizing, rural electrification

Procedia PDF Downloads 409
10359 Hybrid System Configurations and Charging Strategies for Isolated Electric Tuk-Tuk Charging Station in South Africa

Authors: L. Bokopane, K. Kusakana, H. J. Vermaark

Abstract:

The success of renewable powered electric vehicle charging station in isolated areas depends highly on the availability and sustainability of renewable resources all year round at a selected location. The main focus of this paper is to discuss the possible charging strategies that could be implemented to find the best possible configuration of an electric Tuk-Tuk charging station at a given location within South Africa. The charging station is designed, modeled and simulated to evaluate its performances. The techno-economic analysis of different feasible supply configurations of the charging station using renewable energies is simulated using HOMER software and the results compared in order to select the best possible charging strategies in terms of cost of energy consumed.

Keywords: electric tuk-tuk, renewable energy, energy Storage, hybrid systems, HOMER

Procedia PDF Downloads 495
10358 Physiological Responses of the Heterobranchus bidorsalis (Male) X Clarias gariepinus (Female) Hybrid (Heteroclarias) Fingerlings to Different Temperature Levels under Laboratory Conditions

Authors: A. V. Ayanwale, S. M. Tsadu, S. L. Lamai, R. J. Kolo, Y. I. Auta, A. Z. Mohammed

Abstract:

A twelve weeks experiment was carried out on Heteroclarias freshwater hybrid fish fingerlings under laboratory conditions to study the effects of different temperature levels, 26.91 (control), 28.00, 30.00, 32.00°C respectively and their physiological responses to oxygen consumption, ammonia excretion and opercular respiratory beats were evaluated. The oxygen consumption, ammonia excretion and opercular respiratory beats were determined weekly based on standard procedures. The findings revealed that the oxygen consumption of Heteroclarias hybrid fingerlings significantly (p<0.05) increased with increase in temperature. The ammonia excretion were not significantly different (p>0.05) in all the temperature levels. The opercular respiratory beats per minutes showed similar trend in weeks 1,2,4 and 8 but indicated significantly higher (p<0.05) opercular respiratory beats (range= 117.10±2.26 at 30oC to 142.75±3.04 opercular beat at 32oC in week 8) at highest tested temperature levels. However, there was a decreasing trend in the opercular respiratory beats per minute of the controlled fingerlings. Generally, the opercular respiratory beats per minute decreased with increase in fish size. The findings of this study confirmed that increase in water temperature affects the physiology of Heteroclarias hybrid and hence for effective rearing and for profit making, it is essential for the hybrid to be cultured in the temperature range between 26.91°C (control) and 28.00°C.

Keywords: heteroclarias, hybrid, physiological responses, temperature

Procedia PDF Downloads 449
10357 A Hybrid ICA-GA Algorithm for Solving Multiobjective Optimization of Production Planning Problems

Authors: Omar Ramzi Jasim, Jalal Sultan Ashour

Abstract:

Production Planning or Master Production Schedule (MPS) is a key interface between marketing and manufacturing, since it links customer service directly to efficient use of production resources. Mismanagement of the MPS is considered as one of fundamental problems in operation and it can potentially lead to poor customer satisfaction. In this paper, a hybrid evolutionary algorithm (ICA-GA) is presented, which integrates the merits of both imperialist competitive algorithm (ICA) and genetic algorithm (GA) for solving multi-objective MPS problems. In the presented algorithm, the colonies in each empire has be represented a small population and communicate with each other using genetic operators. By testing on 5 production scenarios, the numerical results of ICA-GA algorithm show the efficiency and capabilities of the hybrid algorithm in finding the optimum solutions. The ICA-GA solutions yield the lower inventory level and keep customer satisfaction high and the required overtime is also lower, compared with results of GA and SA in all production scenarios.

Keywords: master production scheduling, genetic algorithm, imperialist competitive algorithm, hybrid algorithm

Procedia PDF Downloads 445
10356 Hybrid Materials Obtained via Sol-Gel Way, by the Action of Teraethylorthosilicate with 1, 3, 4-Thiadiazole 2,5-Bifunctional Compounds

Authors: Afifa Hafidh, Fathi Touati, Ahmed Hichem Hamzaoui, Sayda Somrani

Abstract:

The objective of the present study has been to synthesize and to characterize silica hybrid materials using sol-gel technic and to investigate their properties. Silica materials were successfully fabricated using various bi-functional 1,3,4-thiadiazoles and tetraethoxysilane (TEOS) as co-precursors via a facile one-pot sol-gel pathway. TEOS was introduced at room temperature with 1,3,4-thiadiazole 2,5-difunctiunal adducts, in ethanol as solvent and using HCl acid as catalyst. The sol-gel process lead to the formation of monolithic, coloured and transparent gels. TEOS was used as a principal network forming agent. The incorporation of 1,3,4-thiadiazole molecules was realized by attachment of these later onto a silica matrix. This allowed covalent linkage between organic and inorganic phases and lead to the formation of Si-N and Si-S bonds. The prepared hybrid materials were characterized by Fourier transform infrared, NMR ²⁹Si and ¹³C, scanning electron microscopy and nitrogen absorption-desorption measurements. The optic and magnetic properties of hybrids are studied respectively by ultra violet-visible spectroscopy and electron paramagnetic resonance. It was shown in this work, that heterocyclic moieties were successfully attached in the hybrid skeleton. The formation of the Si-network composed of cyclic units (Q3 structures) connected by oxygen bridges (Q4 structures) was proved by ²⁹Si NMR spectroscopy. The Brunauer-Elmet-Teller nitrogen adsorption-desorption method shows that all the prepared xerogels have isotherms type IV and are mesoporous solids. The specific surface area and pore volume of these materials are important. The obtained results show that all materials are paramagnetic semiconductors. The data obtained by Nuclear magnetic resonance ²⁹Si and Fourier transform infrared spectroscopy, show that Si-OH and Si-NH groups existing in silica hybrids can participate in adsorption interactions. The obtained materials containing reactive centers could exhibit adsorption properties of metal ions due to the presence of OH and NH functionality in the mesoporous frame work. Our design of a simple method to prepare hybrid materials may give interest of the development of mesoporous hybrid systems and their use within the domain of environment in the future.

Keywords: hybrid materials, sol-gel process, 1, 3, 4-thiadaizole, TEOS

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10355 Design, Modeling, Fabrication, and Testing of a Scaled down Hybrid Rocket Engine

Authors: Pawthawala Nancy Manish, Syed Alay Hashim

Abstract:

A hybrid rocket is a rocket engine which uses propellants in two different states of matter- one is in solid and the other either gas or liquid. A hybrid rocket exhibit advantages over both liquid rockets and solid rockets especially in terms of simplicity, stop-start-restart capabilities, safety and cost. This paper deals the design and development of a hybrid rocket having paraffin wax as solid fuel and liquid oxygen as oxidizer. Due to variation of pressure in combustion chamber there is significantly change in mass flow rate, burning rate and uneven regression along the length of the grain. This project describes the working model of a hybrid propellant rocket motor. We have designed a hybrid rocket thrust chamber based on the predetermined combustion chamber pressure and the properties of hybrid propellant. This project is all ready in working condition with normal oxygen injector. Now we have planned to modify the injector design to improve the combustion property. We will use spray type injector for injecting the oxidizer. This idea will increase the performance followed by the regression rate of the solid fuel. By employing mass conservation law, oxygen mass flux, oxidizer/fuel ratio and regression rate the thrust coefficient can be obtained for our current design. CATIA V5 R20 is our design software for the complete setup. This project is fully based on experimental evaluation and the collection of combustion and flow parameters. The thrust chamber is made of stainless steel and the duration of test is around 15-20 seconds (Maximum). These experiments indicates that paraffin based fuel provides the opportunity to satisfy a broad range of mission requirements for the next generation of the hybrid rocket system.

Keywords: burning rate, liquid oxygen, mass flow rate, paraffin wax and sugar

Procedia PDF Downloads 306
10354 Hybrid Antenna Array with the Bowtie Elements for Super-Resolution and 3D Scanning Radars

Authors: Somayeh Komeylian

Abstract:

The antenna arrays for the entire 3D spherical coverage have been developed for their potential use in variety of applications such as radars and body-worn devices of the body area networks. In this study, we have rigorously revamped the hybrid antenna array using the optimum geometry of bowtie elements for achieving a significant improvement in the angular discrimination capability as well as in separating two adjacent targets. In this scenario, we have analogously investigated the effectiveness of increasing the virtual array length in fostering and enhancing the directivity and angular resolution in the 10 GHz frequency. The simulation results have extensively verified that the proposed antenna array represents a drastic enhancement in terms of size, directivity, side lobe level (SLL) and, especially resolution compared with the other available geometries. We have also verified that the maximum directivities of the proposed hybrid antenna array represent the robustness to the all  variations, which is accompanied by the uniform 3D scanning characteristic.

Keywords: bowtie antenna, hybrid antenna array, array signal processing, body area networks

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10353 Compressive Strength and Microstructure of Hybrid Alkaline Cements

Authors: Z. Abdollahnejad, P. Torgal, J. Barroso Aguiar

Abstract:

Publications on the field of alkali-activated binders, state that this new material is likely to have high potential to become an alternative to Portland cement. Classical alkali-activated cements could be made more eco-efficient if the use of sodium silicate is avoided. Besides, most alkali-activated cements suffer from severe efflorescence originated by the fact that alkaline and/or soluble silicates that are added during processing cannot be totally consumed. This paper presents experimental results on hybrid alkaline cements. Compressive strength results and efflorescence’s observations show that the new mixes already analyzed are promising. SEM results show that no traditional porous ITZ was detected in these binders.

Keywords: hybrid alkaline cements, compressive strength, efflorescence, SEM, ITZ

Procedia PDF Downloads 266
10352 Dynamics of Hybrid Language in Urban and Rural Uttar Pradesh India

Authors: Divya Pande

Abstract:

The dynamics of culture expresses itself in language. Even after India got independence in 1947 English subtly crept in the language of the masses with a silent and powerful flow towards the vernacular. The culture contact resulted in learning and emergence of a new language across the Hindi speaking belt of Northern and Central India. The hybrid words thus formed displaced the original word and got contextualized and absorbed in the language of the common masses. The research paper explores the interesting new vocabulary used extensively in the urban and rural districts of the state of Uttar- Pradesh which is the most populous state of India. The paper adopts a two way classification- formal and contextual for the analysis of the hybrid vocabulary of the linguistic items where one element is necessarily from the English language and the other from the Hindi. The new vocabulary represents languages of the wider world cutting across the geographical and the cultural barriers. The paper also broadly points out to the Hinglish commonly used in the state.

Keywords: assimilation, culture contact, Hinglish, hybrid words

Procedia PDF Downloads 377
10351 Intelligent Path Tracking Hybrid Fuzzy Controller for a Unicycle-Type Differential Drive Robot

Authors: Abdullah M. Almeshal, Mohammad R. Alenezi, Muhammad Moaz

Abstract:

In this paper, we discuss the performance of applying hybrid spiral dynamic bacterial chemotaxis (HSDBC) optimisation algorithm on an intelligent controller for a differential drive robot. A unicycle class of differential drive robot is utilised to serve as a basis application to evaluate the performance of the HSDBC algorithm. A hybrid fuzzy logic controller is developed and implemented for the unicycle robot to follow a predefined trajectory. Trajectories of various frictional profiles and levels were simulated to evaluate the performance of the robot at different operating conditions. Controller gains and scaling factors were optimised using HSDBC and the performance is evaluated in comparison to previously adopted optimisation algorithms. The HSDBC has proven its feasibility in achieving a faster convergence toward the optimal gains and resulted in a superior performance.

Keywords: differential drive robot, hybrid fuzzy controller, optimization, path tracking, unicycle robot

Procedia PDF Downloads 439
10350 A Universal Hybrid Adsorbent Based on Chitosan for Water Treatment

Authors: Sandrine Delpeux-Ouldriane, Min Cai, Laurent Duclaux, Laurence Reinert, Fabrice Muller

Abstract:

A novel hybrid adsorbent, based on chitosan biopolymer, clays and activated carbon was prepared. Hybrid chitosan beads containing dispersed clays and activated carbons were prepared by precipitation in basic medium. Such a composite material is still very porous and presents a wide adsorption spectrum. The obtained composite adsorbent is able to handle all the pollution types including heavy metals, polar and hydrophobic organic molecules and nitrates. It could find a place of choice in tertiary water treatment processes or for an ‘at source’ treatment concerning chemical or pharmaceutical industries.

Keywords: adsorption, chitosan, clay mineral, activated carbon

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10349 Mechanical and Tribological Properties of Al7075 Reinforced with Graphene-Beryl Hybrid Metal Matrix Composites

Authors: Mohamed Haneef, Shanawaz Patil, Syed Zameer, Mohammed Mohsin Ali

Abstract:

The emerging technologies and trends of present generation requires downsizing the unwieldy structures to light weight structures on one hand and integration of varied properties on other hand to meet the application demands. In the present investigation an attempt is made to familiarize and best possibilities of reinforcing agent in aluminum 7075 matrix with naturally occurring beryl (Be) and graphene (Gr) to develop a new hybrid composite material. A stir casting process was used to fabricate with fixed volume fraction of 6wt% weight beryl and various volume fractions of 0.5wt%, 1wt%, 1.5wt% and 2wt% of graphene. The properties such as tensile strength, hardness and dry sliding wear behavior of hybrid composites were examined. The crystallite size and morphology of the graphene and beryl particles were analyzed with X-ray diffraction (XRD) and scanning electron microscopy (SEM) respectively. It was observed that ultimate tensile strength and hardness of the hybrid composite increased with increasing reinforcement volume fraction as compared to specimen without reinforcement additions. The dry sliding wear behavior of the hybrid composites decreases as compared to Al7075 alloy without reinforcement.

Keywords: Al7075, beryl, graphene, TEM, wear

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10348 Semantic-Based Collaborative Filtering to Improve Visitor Cold Start in Recommender Systems

Authors: Baba Mbaye

Abstract:

In collaborative filtering recommendation systems, a user receives suggested items based on the opinions and evaluations of a community of users. This type of recommendation system uses only the information (notes in numerical values) contained in a usage matrix as input data. This matrix can be constructed based on users' behaviors or by offering users to declare their opinions on the items they know. The cold start problem leads to very poor performance for new users. It is a phenomenon that occurs at the beginning of use, in the situation where the system lacks data to make recommendations. There are three types of cold start problems: cold start for a new item, a new system, and a new user. We are interested in this article at the cold start for a new user. When the system welcomes a new user, the profile exists but does not have enough data, and its communities with other users profiles are still unknown. This leads to recommendations not adapted to the profile of the new user. In this paper, we propose an approach that improves cold start by using the notions of similarity and semantic proximity between users profiles during cold start. We will use the cold-metadata available (metadata extracted from the new user's data) useful in positioning the new user within a community. The aim is to look for similarities and semantic proximities with the old and current user profiles of the system. Proximity is represented by close concepts considered to belong to the same group, while similarity groups together elements that appear similar. Similarity and proximity are two close but not similar concepts. This similarity leads us to the construction of similarity which is based on: a) the concepts (properties, terms, instances) independent of ontology structure and, b) the simultaneous representation of the two concepts (relations, presence of terms in a document, simultaneous presence of the authorities). We propose an ontology, OIVCSRS (Ontology of Improvement Visitor Cold Start in Recommender Systems), in order to structure the terms and concepts representing the meaning of an information field, whether by the metadata of a namespace, or the elements of a knowledge domain. This approach allows us to automatically attach the new user to a user community, partially compensate for the data that was not initially provided and ultimately to associate a better first profile with the cold start. Thus, the aim of this paper is to propose an approach to improving cold start using semantic technologies.

Keywords: visitor cold start, recommender systems, collaborative filtering, semantic filtering

Procedia PDF Downloads 195
10347 A Teaching Learning Based Optimization for Optimal Design of a Hybrid Energy System

Authors: Ahmad Rouhani, Masood Jabbari, Sima Honarmand

Abstract:

This paper introduces a method to optimal design of a hybrid Wind/Photovoltaic/Fuel cell generation system for a typical domestic load that is not located near the electricity grid. In this configuration the combination of a battery, an electrolyser, and a hydrogen storage tank are used as the energy storage system. The aim of this design is minimization of overall cost of generation scheme over 20 years of operation. The Matlab/Simulink is applied for choosing the appropriate structure and the optimization of system sizing. A teaching learning based optimization is used to optimize the cost function. An overall power management strategy is designed for the proposed system to manage power flows among the different energy sources and the storage unit in the system. The results have been analyzed in terms of technics and economics. The simulation results indicate that the proposed hybrid system would be a feasible solution for stand-alone applications at remote locations.

Keywords: hybrid energy system, optimum sizing, power management, TLBO

Procedia PDF Downloads 545
10346 Temperature Distribution Inside Hybrid photovoltaic-Thermoelectric Generator Systems and their Dependency on Exposition Angles

Authors: Slawomir Wnuk

Abstract:

Due to widespread implementation of the renewable energy development programs the, solar energy use increasing constantlyacross the world. Accordingly to REN21, in 2020, both on-grid and off-grid solar photovoltaic systems installed capacity reached 760 GWDCand increased by 139 GWDC compared to previous year capacity. However, the photovoltaic solar cells used for primary solar energy conversion into electrical energy has exhibited significant drawbacks. The fundamentaldownside is unstable andlow efficiencythe energy conversion being negatively affected by a rangeof factors. To neutralise or minimise the impact of those factors causing energy losses, researchers have come out withvariedideas. One ofpromising technological solutionsoffered by researchers is PV-MTEG multilayer hybrid system combiningboth photovoltaic cells and thermoelectric generators advantages. A series of experiments was performed on Glasgow Caledonian University laboratory to investigate such a system in operation. In the experiments, the solar simulator Sol3A series was employed as a stable solar irradiation source, and multichannel voltage and temperature data loggers were utilised for measurements. The two layer proposed hybrid systemsimulation model was built up and tested for its energy conversion capability under a variety of the exposure angles to the solar irradiation with a concurrent examination of the temperature distribution inside proposed PV-MTEG structure. The same series of laboratory tests were carried out for a range of various loads, with the temperature and voltage generated being measured and recordedfor each exposure angle and load combination. It was found that increase of the exposure angle of the PV-MTEG structure to an irradiation source causes the decrease of the temperature gradient ΔT between the system layers as well as reduces overall system heating. The temperature gradient’s reduction influences negatively the voltage generation process. The experiments showed that for the exposureangles in the range from 0° to 45°, the ‘generated voltage – exposure angle’ dependence is reflected closely by the linear characteristics. It was also found that the voltage generated by MTEG structures working with the optimal load determined and applied would drop by approximately 0.82% per each 1° degree of the exposure angle increase. This voltage drop occurs at the higher loads applied, getting more steep with increasing the load over the optimal value, however, the difference isn’t significant. Despite of linear character of the generated by MTEG voltage-angle dependence, the temperature reduction between the system structure layers andat tested points on its surface was not linear. In conclusion, the PV-MTEG exposure angle appears to be important parameter affecting efficiency of the energy generation by thermo-electrical generators incorporated inside those hybrid structures. The research revealedgreat potential of the proposed hybrid system. The experiments indicated interesting behaviour of the tested structures, and the results appear to provide valuable contribution into thedevelopment and technological design process for large energy conversion systems utilising similar structural solutions.

Keywords: photovoltaic solar systems, hybrid systems, thermo-electrical generators, renewable energy

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10345 On Multiobjective Optimization to Improve the Scalability of Fog Application Deployments Using Fogtorch

Authors: Suleiman Aliyu

Abstract:

Integrating IoT applications with Fog systems presents challenges in optimization due to diverse environments and conflicting objectives. This study explores achieving Pareto optimal deployments for Fog-based IoT systems to address growing QoS demands. We introduce Pareto optimality to balance competing performance metrics. Using the FogTorch optimization framework, we propose a hybrid approach (Backtracking search with branch and bound) for scalable IoT deployments. Our research highlights the advantages of Pareto optimality over single-objective methods and emphasizes the role of FogTorch in this context. Initial results show improvements in IoT deployment cost in Fog systems, promoting resource-efficient strategies.

Keywords: pareto optimality, fog application deployment, resource allocation, internet of things

Procedia PDF Downloads 46
10344 Speed Control of Hybrid Stepper Motor by Using Adaptive Neuro-Fuzzy Controller

Authors: Talha Ali Khan

Abstract:

This paper presents an adaptive neuro-fuzzy interference system (ANFIS), which is applied to a hybrid stepper motor (HSM) to regulate its speed. The dynamic response of the HSM with the ANFIS controller is studied during the starting process and under different load disturbance. The effectiveness of the proposed controller is compared with that of the conventional PI controller. The proposed method solves the problem of nonlinearities and load changes of the HSM drives. The proposed controller ensures fast and precise dynamic response with an excellent steady state performance. Matlab/Simulink program is used for this dynamic simulation study.

Keywords: stepper motor, hybrid, ANFIS, speed control

Procedia PDF Downloads 515