Search results for: hybrid generation

Authors: Atilla Bayram

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This paper presents the trajectory tracking control of a spatial redundant hybrid manipulator. This manipulator consists of two parallel manipulators which are a variable geometry truss (VGT) module. In fact, each VGT module with 3-degress of freedom (DOF) is a planar parallel manipulator and their operational planes of these VGT modules are arranged to be orthogonal to each other. Also, the manipulator contains a twist motion part attached to the top of the second VGT module to supply the missing orientation of the endeffector. These three modules constitute totally 7-DOF hybrid (parallel-parallel) redundant spatial manipulator. The forward kinematics equations of this manipulator are obtained, then, according to these equations, the inverse kinematics is solved based on an optimization with the joint limit avoidance. The dynamic equations are formed by using virtual work method. In order to test the performance of the redundant manipulator and the controllers presented, two different desired trajectories are followed by using the computed force control method and a switching control method. The switching control method is combined with the computed force control method and genetic algorithm. In the switching control method, the genetic algorithm is only used for fine tuning in the compensation of the trajectory tracking errors.

Keywords: computed force method, genetic algorithm, hybrid manipulator, inverse kinematics of redundant manipulators, variable geometry truss

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Authors: Radhia Toujani, Jalel Akaichi

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In recent years, the study of community detection in social networks has received great attention. The hierarchical structure of the network leads to the emergence of the convergence to a locally optimal community structure. In this paper, we aim to avoid this local optimum in the introduced hybrid hierarchical method. To achieve this purpose, we present an objective function where we incorporate the value of structural and semantic similarity based modularity and a metaheuristic namely bees colonies algorithm to optimize our objective function on both hierarchical level divisive and agglomerative. In order to assess the efficiency and the accuracy of the introduced hybrid bee colony model, we perform an extensive experimental evaluation on both synthetic and real networks.

Keywords: social network, community detection, agglomerative hierarchical clustering, divisive hierarchical clustering, similarity, modularity, metaheuristic, bee colony

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Authors: Khaoula Bensaida, Osama Eljamal

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The electrical energy generation through Microbial Fuel Cells (MFCs) using microorganisms is a renewable and sustainable approach. It creates truly an efficient technology for power production and wastewater treatment. MFC is an electrochemical device which turns wastewater into electricity. The most important part of MFC is microbes. Nano zero-valent Iron NZVI technique was successfully applied in degrading the chemical pollutants and cleaning wastewater. However, the use of NZVI for enhancing the current production is still not confirmed yet. This study aims to confirm the effect of these particles on the current generation by using MFC. A constructed microbial fuel cell, which utilizes domestic wastewater, has been considered for wastewater treatment and bio-electricity generation. The two electrodes were connected to an external resistor (200 ohms). Experiments were conducted in two steps. First, the MFC was constructed without adding NZVI particles (Control) while at a second step, nanoparticles were added with a concentration of 50mg/L. After 20 hours, the measured voltage increased to 5 and 8mV, respectively. To conclude, the use of zero-valent iron in an MFC system can increase electricity generation.

Keywords: bacterial growth, electricity generation, microbial fuel cell MFC, nano zero-valent iron NZVI.

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Authors: Orose Rugchati, Khumthong Mahawongwiriya

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Dendrobium hybrid cv. Ear-Sakul has become one of the important commercial commodities in Thailand agricultural industry worldwide, either as potted plants or as cut flowers due to the attractive color produced in flower petals. Anthocyanins are the main flower pigments and responsible for the natural attractive display of petal colors. These pigments play an important role in functionality, such as to attract animal pollinators, classification, and grading of these orchids. Dendrobium hybrid cv. Ear-Sakul has been collected from local area farm in different stage flowers (F1, F2-F5, and F6). Anthocyanins pigment were extracted from the fresh flower by solvent extraction (MeOH–TFA 99.5:0.5v/v at 4ºC) and purification with ethyl acetate. The main anthocyanins components are cyanidin, pelargonidin, and delphinidin. Pure anthocyanin contents were analysis by UV-Visible spectroscopy technique at λ max 535, 520 and 546 nm respectively. The anthocyanins contents were converted in term of monomeric anthocyanins pigment (mg/L). The anthocyanins contents of all sample were compared with standard pigments cyanidin, pelargonidin and delphinidin. From this experiment is a simple extraction and analysis anthocyanins content in different stage of flowers results shown that monomeric anthocyanins pigment contents of different stage flowers (F1, F2-F5 and F6 ): cyanidin – 3 – glucoside (mg/l) are 0.85+0.08, 24.22+0.12 and 62.12+0.6; Pelargonidin 3,5-di- glucoside(mg/l) 10.37+0.12, 31.06+0.8 and 81.58+ 0.5; Delphinidin (mg/l) 6.34+0.17, 18.98+0.56 and 49.87+0.7; and the appearance of extraction pure anthocyanins in L(a, b): 2.71(1.38, -0.48), 1.06(0.39,-0.66) and 2.64(2.71,-3.61) respectively. Dendrobium Hybrid cv. Ear-Sakul could be used as a source of anthocyanins by simple solvent extraction and stage of flowers as a guideline for the prediction amount of main anthocyanins components are cyanidin, pelargonidin, and delphinidin could be application and development in quantities, and qualities with the advantage for food pharmaceutical and cosmetic industries.

Keywords: analysis, anthocyanins contents, different stage flowers, Dendrobium Hybrid cv. Ear-Sakul

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Authors: Volker Landersheim, Daria Manushyna, Thinh Pham, Dai-Duong Tran, Thomas Geury, Omar Hegazy, Steven Wilkins

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Air pollution is one of the emerging problems in our society. Targets of reduction of CO₂ emissions address low-carbon and resource-efficient transport. (Plug-in) hybrid electric propulsion concepts offer the possibility to reduce total cost of ownership (TCO) and emissions for public transport vehicles (e.g., bus application). In this context, typically, diesel engines are used to form the hybrid propulsion system of the vehicle. Though the technological development of diesel engines experience major advantages, some challenges such as the high amount of particle emissions remain relevant. Gaseous fuels (i.e., compressed natural gases (CNGs) or liquefied petroleum gases (LPGs) represent an attractive alternative to diesel because of their composition. In the framework of the research project 'Optimised Real-world Cost-Competitive Modular Hybrid Architecture' (ORCA), which was funded by the EU, two different hybrid-electric propulsion concepts have been investigated: one using a diesel engine as internal combustion engine and one using CNG as fuel. The aim of the current study is to analyze specific benefits for the aforementioned hybrid propulsion systems for predefined driving scenarios with regard to emissions and total cost of ownership in bus application. Engine models based on experimental data for diesel and CNG were developed. For the purpose of designing optimal energy management strategies for each propulsion system, maps-driven or quasi-static models for specific engine types are used in the simulation framework. An analogous modelling approach has been chosen to represent emissions. This paper compares the two concepts regarding their CO₂ and NOx emissions. This comparison is performed for relevant bus missions (urban, suburban, with and without zero-emission zone) and with different energy management strategies. In addition to the emissions, also the downsizing potential of the combustion engine has been analysed to minimize the powertrain TCO (pTCO) for plug-in hybrid electric buses. The results of the performed analyses show that the hybrid vehicle concept using the CNG engine shows advantages both with respect to emissions as well as to pTCO. The pTCO is 10% lower, CO₂ emissions are 13% lower, and the NOx emissions are more than 50% lower than with the diesel combustion engine. These results are consistent across all usage profiles under investigation.

Keywords: bus transport, emissions, hybrid propulsion, pTCO, CNG

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Authors: Amie Smith, Jodi-Lyn Benjamin

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In 2020, there are currently four generations in the nursing workforce: The Veterans, Boomers, Generation X and Generation Y (Gen Y). Understanding each generation and their growing needs will equip the workforce for when the Boomers prepare for retirement, with majority of nursing leadership positions to be potentially replaced with Gen Y nurses. In SA Medical Imaging(SAMI), at Flinders Medical Centre (FMC), it has been proven that despite challenges in succession planning, Gen Y nurse leaders are able to overcome these obstacles and provide the leadership necessary to meet the changing needs in healthcare and across organisations. Changing the culture in radiology nursing has been seen as an obstacle due to the historical nursing practices and resistance to adapt to current/future practice. As radiology advances so does the role of the nurse in imaging, this has required resilience and strong support through leadership as we change and develop the culture to keep up with the evolution of technology and standard of patient care. As a result of supporting Gen Y nurses in leadership roles, SAMI, FMC has seen a positive change in culture by creating a healthy work environment which has allowed Gen Y nurses to make long lasting contributions to the nursing profession.

Keywords: changing culture, Generation Y, radiology, nursing, leadership

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Authors: Tomomi Uchiyama, Tomoko Okayama, Yukio Ide

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This study is concerned with the development of a micro-hydraulic turbine for power generation installed in sewer pipes. The runner has a circular hollow around the central (rotating) axis so that solid materials included in water can be easily flow through the runner without blocking the turbine. The laboratory experiments are also conducted. The hollow is very effective to make polyester fibers pass through the turbine. The guide vane is useful to heighten the turbine performance. But it is easily blocked by the fibers, making the turbine lose the function.

Keywords: micro-hydraulic turbine, power generation, sewage, sewer pipe

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Authors: Ahmed Mohammed Alsalama

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Recommendation systems are widely used in e-commerce applications. The engine of a current recommendation system recommends items to a particular user based on user preferences and previous high ratings. Various recommendation schemes such as collaborative filtering and content-based approaches are used to build a recommendation system. Most of the current recommendation systems were developed to fit a certain domain such as books, articles, and movies. We propose a hybrid framework recommendation system to be applied on two-dimensional spaces (User x Item) with a large number of Users and a small number of Items. Moreover, our proposed framework makes use of both favorite and non-favorite items of a particular user. The proposed framework is built upon the integration of association rules mining and the content-based approach. The results of experiments show that our proposed framework can provide accurate recommendations to users.

Keywords: data mining, association rules, recommendation systems, hybrid systems

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Authors: Deepa Das, Susmita Das

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Cognitive Radio (CR) is an emerging technology to combat the spectrum scarcity issues. This is achieved by consistently sensing the spectrum, and detecting the under-utilized frequency bands without causing undue interference to the primary user (PU). In soft decision fusion (SDF) based cooperative spectrum sensing, various evolutionary algorithms have been discussed, which optimize the weight coefficient vector for maximizing the detection performance. In this paper, we propose the hybrid invasive weed optimization and particle swarm optimization (IWO/PSO) algorithm as a fast and global optimization method, which improves the detection probability with a lesser sensing time. Then, the efficiency of this algorithm is compared with the standard invasive weed optimization (IWO), particle swarm optimization (PSO), genetic algorithm (GA) and other conventional SDF based methods on the basis of convergence and detection probability.

Keywords: cognitive radio, spectrum sensing, soft decision fusion, GA, PSO, IWO, hybrid IWO/PSO

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Authors: Zakir Husain, Neem Sagar, Neeraj Gupta

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Due to the increased penetration of renewable energy resources in the distribution system, the system is no longer passive in nature. In this paper, a steady state analysis of the distribution system has been done with the inclusion of wind generation. The modeling of wind turbine generator system and wind generator has been made to obtain the average active and the reactive power injection into the system. The study has been conducted on a IEEE-33 bus system with two wind generators. The present research work is useful not only to utilities but also to customers.

Keywords: distributed generation, distribution network, radial network, wind turbine generating system

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Authors: Sophia Shi

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Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

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Authors: Wajahat Hussain Khan, M. Zubair Akbar Qureshi

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The viscous, two-dimensional, incompressible, and laminar time-dependent heat transfer flow through a ferromagnetic fluid is considered in this paper. Flow takes place in a channel between two porous walls under the influence of the magnetic field located beyond the channel. It is assumed that there are no electric field effects and the variation in the magnetic field vector that could occur within the F

Keywords: hybrid ferrofluid, heat transfer, magnetic field, porous channel

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Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

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Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: artificial immune system, breast cancer diagnosis, Euclidean function, Gaussian function

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Authors: Syali Pradhan, Neetu Jha

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The Marigold flower is used in religious places for offering and decoration purpose every day. The flowers are discarded near trees or in aquatic bodies. This floral waste can be used for extracting dyes or oils. Still the secondary waste remains after processing which need to be addressed. This research aims to provide green and clean power using secondary floral waste available after processing. The carbonization of floral waste produce carbon material with high surface area and enhance active site for more reaction. The Hybrid supercapacitors are more stable, offer improved operating temperature and use less toxic material compared to battery. They provide enhanced energy density compared to supercapacitors. Hence, hybrid supercapacitor designed using waste material would be more practicable for future energy application. Here, we present the utilization of carbonized floral waste as supercapacitor electrode material. This material after carbonization gets graphitized and shows high surface area, optimum porosity along with high conductivity. Hence, this material has been tested as cathode electrode material for high performance zinc storage hybrid supercapacitor. High energy storage along with high stability has been obtained using this cathodic waste material as electrode.

Keywords: marigold, flower waste, energy storage, cathode, supercapacitor

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Authors: Mazaher Yarmohamadi-Vasel, Ali Reza Modarresi-Alama, Sahar Shabzendedara

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Purpose/Objectives: The first purpose was synthesize Poly(N-(sulfophenyl)aniline) nanoflowers (PSANFLs) and Poly(N-(sulfophenyl)aniline) nanofibers/titanium dioxide nanoparticles ((PSANFs/TiO2NPs) by a solid-state mechano-chemical reaction and template-free method and use them in hybrid solar cell. Also, our second aim was to increase the solubility and the processability of conjugated nanomaterials in water through polar functionalized materials. poly[N-(4-sulfophenyl)aniline] is easily soluble in water because of the presence of polar groups of sulfonic acid in the polymer chain. Materials/Methods: Iron (III) chloride hexahydrate (FeCl3∙6H2O) were bought from Merck Millipore Company. Titanium oxide nanoparticles (TiO2, <20 nm, anatase) and Sodium diphenylamine-4-sulfonate (99%) were bought from Sigma-Aldrich Company. Titanium dioxide nanoparticles paste (PST-20T) was prepared from Sharifsolar Co. Conductive glasses coated with indium tin oxide (ITO) were bought from Xinyan Technology Co (China). For the first time we used the solid-state mechano-chemical reaction and template-free method to synthesize Poly(N-(sulfophenyl)aniline) nanoflowers. Moreover, for the first time we used the same technique to synthesize nanocomposite of Poly(N-(sulfophenyl)aniline) nanofibers and titanium dioxide nanoparticles (PSANFs/TiO2NPs) also for the first time this nanocomposite was synthesized. Examining the results of electrochemical calculations energy gap obtained by CV curves and UV–vis spectra demonstrate that PSANFs/TiO2NPs nanocomposite is a p-n type material that can be used in photovoltaic cells. Doctor blade method was used to creat films for three kinds of hybrid solar cells in terms of different patterns like ITO│TiO2NPs│Semiconductor sample│Al. In the following, hybrid photovoltaic cells in bilayer and bulk heterojunction structures were fabricated as ITO│TiO2NPs│PSANFLs│Al and ITO│TiO2NPs│PSANFs /TiO2NPs│Al, respectively. Fourier-transform infrared spectra, field emission scanning electron microscopy (FE-SEM), ultraviolet-visible spectra, cyclic voltammetry (CV) and electrical conductivity were the analysis that used to characterize the synthesized samples. Results and Conclusions: FE-SEM images clearly demonstrate that the morphology of the synthesized samples are nanostructured (nanoflowers and nanofibers). Electrochemical calculations of band gap from CV curves demonstrated that the forbidden band gap of the PSANFLs and PSANFs/TiO2NPs nanocomposite are 2.95 and 2.23 eV, respectively. I–V characteristics of hybrid solar cells and their power conversion efficiency (PCE) under 100 mWcm−2 irradiation (AM 1.5 global conditions) were measured that The PCE of the samples were 0.30 and 0.62%, respectively. At the end, all the results of solar cell analysis were discussed. To sum up, PSANFLs and PSANFLs/TiO2NPs were successfully synthesized by an affordable and straightforward mechanochemical reaction in solid-state under the green condition. The solubility and processability of the synthesized compounds have been improved compared to the previous work. We successfully fabricated hybrid photovoltaic cells of synthesized semiconductor nanostructured polymers and TiO2NPs as different architectures. We believe that the synthesized compounds can open inventive pathways for the development of other Poly(N-(sulfophenyl)aniline based hybrid materials (nanocomposites) proper for preparing new generation solar cells.

Keywords: mechanochemical synthesis, PSANFLs, PSANFs/TiO2NPs, solar cell

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Authors: Noor Zuhaira Abd Aziz

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Rice husk and kenaf filled with calcium carbonate (CaCO3) and high density polyethylene (HDPE) composite were prepared separately using twin-screw extruder at 50rpm. Different filler loading up to 30 parts of rice husk particulate and kenaf fiber were mixed with the fixed 30% amount of CaCO3 mineral filler to produce rice husk/CaCO3/HDPE and kenaf/CaCO3/HDPE hybrid composites. In this study, the effects of natural fiber for both rice husk and kenaf in CaCO3/HDPE composite on physical and mechanical properties were investigated. The property analyses showed that water absorption increased with the presence of kenaf and rice husk fillers. Natural fibers in composite significantly influence water absorption properties due to natural characters of fibers which contain cellulose, hemicellulose and lignin structures. The result showed that 10% of additional natural fibers into hybrid composite had caused decreased flexural strength, however additional of high natural fiber (>10%) filler loading has proved to increase its flexural strength.

Keywords: Hybrid composites, Water absorption, Mechanical properties

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Authors: Jang-Hwan Yin, Hae-Jeong Jeong, Hyo-Geun Jeong

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K-water (Korea Water Resources Corporation) conducted basic and working design about floating PV generation system installed above water in the upstream of dam to develop clean energy using water with importance of green growth is magnified ecumenically. PV Generation System on the ground applied considerably until now raise environmental damage by using farmland and forest land, PV generation system on the building roof is already installed at almost the whole place of business and additional installation is almost impossible. Installation space of PV generation system is infinite and efficient national land use is possible because it is installed above water. Also, PV module's efficiency increase by natural water cooling method and no shade. So it is identified that annual power generation is more than PV generation system on the ground by operating performance data. Although it is difficult to design and construct by high cost, little application case, difficult installation of floater, mooring device, underwater cable, etc. However, it has been examined cost reduction plan such as structure weight lightening, floater optimal design, etc. This thesis described basic and working design result systematically about K-water's floating PV generation system development and suggested optimal design method of floating PV generation system. Main contents are photovoltaic array location select, substation location select related underwater cable, PV module and inverter design, transmission and substation equipment design, floater design related structure weight lightening, mooring system design related water level fluctuation, grid connecting technical review, remote control and monitor equipment design, etc. This thesis will contribute to optimal design and business extension of floating PV generation system, and it will be opportunity revitalize clean energy development using water.

Keywords: PV generation system, clean energy, green growth, solar energy

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Authors: Jin-Woo Park, Sung-Soo Lee, Nong-Moon Hwang

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The generation of charged nanoparticles in the gas phase during the Chemical Vapor Deposition (CVD) process has been frequently reported with their subsequent deposition into films and nanostructures in many systems such as carbon, silicon and zinc oxide. The microstructure evolution of films and nanostructures is closely related with the size distribution of charged nanoparticles. To confirm the generation of charged nanoparticles during GaN, the generation of GaN charged nanoparticles was examined in an atmospheric pressure CVD process using a Differential Mobility Analyser (DMA) combined with a Faraday Cup Electrometer (FCE). It was confirmed that GaN charged nanoparticles were generated under the condition where GaN nanostructures were synthesized on the bare and Au-coated Si substrates. In addition, the deposition behaviour depends strongly on the charge transfer rate of metal substrates. On the metal substrates of a lower CTR such as Mo, the deposition rate of GaN was much lower than on those of a higher CTR such as Fe. GaN nanowires tend to grow on the substrates of a lower CTR whereas GaN thin films tend to be deposited on the substrates of a higher CTR.

Keywords: chemical vapour deposition, charged cluster model, generation of charged nanoparticles, deposition behaviour, nanostructures, gan, charged transfer rate

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Authors: Mohammad Najmol Haque, Takeshi Maki, Jun Sasaki

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Headed stud shear connections are widely used in the junction or embedded zone of hybrid girder to achieve whole composite action with continuity that can sustain steel-concrete interfacial tensile and shear forces. In Japan, Japan Road Association (JRA) specifications are used for hybrid girder design that utilizes very low level of stud capacity than those of American Institute of Steel Construction (AISC) specifications, Japan Society of Civil Engineers (JSCE) specifications and EURO code. As low design shear strength is considered in design of connections, the time dependent shear behavior due to sustained external loading is not considered, even not fully studied. In this study, a finite element approach was used to evaluate the time dependent shear behavior for headed studs used as connections at the junction. This study clarified, how the sustained loading distinctively impacted on changing the interfacial shear of connections with time which was sensitive to lodging history, positions of flanges, neighboring studs, position of prestress bar and reinforcing bar, concrete strength, etc. and also identified a shear influence area. Stud strength was also confirmed through pushout tests. The outcome obtained from the study may provide an important basis and reference data in designing connections of hybrid girders with enhanced stud capacity with due consideration of their long-term shear behavior.

Keywords: finite element, hybrid girder, shear connections, sustained loading, time dependent behavior

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Authors: Cesar Hernández, Diego Giral, Ingrid Páez

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This article proposes a hybrid algorithm for spectrum allocation in cognitive radio networks based on the algorithms Analytical Hierarchical Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to improve the performance of the spectrum mobility of secondary users in cognitive radio networks. To calculate the level of performance of the proposed algorithm a comparative analysis between the proposed AHP-TOPSIS, Grey Relational Analysis (GRA) and Multiplicative Exponent Weighting (MEW) algorithm is performed. Four evaluation metrics is used. These metrics are the accumulative average of failed handoffs, the accumulative average of handoffs performed, the accumulative average of transmission bandwidth, and the accumulative average of the transmission delay. The results of the comparison show that AHP-TOPSIS Algorithm provides 2.4 times better performance compared to a GRA Algorithm and, 1.5 times better than the MEW Algorithm.

Keywords: cognitive radio, decision making, hybrid algorithm, spectrum handoff, wireless networks

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Authors: J. D. García Espinel, Paula Pérez Sánchez, Carlos Egea Ruiz, Carlos Lardín Mifsut, Andrés López-Aranguren Oliver

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This paper shortly describes three main actuations over a Waste Water Treatment Plant (WWTP) for reducing its energy consumption: Optimization of the biological reactor in the aeration stage by including new control algorithms and introducing new efficient equipment, the installation of an innovative hybrid system with zero Grid injection (formed by 100kW of PV energy and 5 kW of mini-wind energy generation) and an intelligent management system for load consumption and energy generation control in the most optimum way. This project called RENEWAT, involved in the European Commission call LIFE 2013, has the main objective of reducing the energy consumptions through different actions on the processes which take place in a WWTP and introducing renewable energies on these treatment plants, with the purpose of promoting the usage of treated waste water for irrigation and decreasing the C02 gas emissions. WWTP is always required before waste water can be reused for irrigation or discharged in water bodies. However, the energetic demand of the treatment process is high enough for making the price of treated water to exceed the one for drinkable water. This makes any policy very difficult to encourage the re-use of treated water, with a great impact on the water cycle, particularly in those areas suffering hydric stress or deficiency. The cost of treating waste water involves another climate-change related burden: the energy necessary for the process is obtained mainly from the electric network, which is, in most of the cases in Europe, energy obtained from the burning of fossil fuels. The innovative part of this project is based on the implementation, adaptation and integration of solutions for this problem, together with a new concept of the integration of energy input and operative energy demand. Moreover, there is an important qualitative jump between the technologies used and the alleged technologies to use in the project which give it an innovative character, due to the fact that there are no similar previous experiences of a WWTP including an intelligent discrimination of energy sources, integrating renewable ones (PV and Wind) and the grid.

Keywords: aeration system, biological reactor, CO2 emissions, energy efficiency, hybrid systems, LIFE 2013 call, process optimization, renewable energy sources, wasted water treatment plants

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Authors: Paramjit Kaur, Harish Kundra

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In the recent years, swarm intelligence based firefly algorithm has become a great focus for the researchers to solve the real time optimization problems. Here, firefly algorithm is used for the application of satellite image classification. For experimentation, Alwar area is considered to multiple land features like vegetation, barren, hilly, residential and water surface. Alwar dataset is considered with seven band satellite images. Firefly Algorithm is based on the attraction of less bright fireflies towards more brightener one. For the evaluation of proposed concept accuracy assessment parameters are calculated using error matrix. With the help of Error matrix, parameters of Kappa Coefficient, Overall Accuracy and feature wise accuracy parameters of user’s accuracy & producer’s accuracy can be calculated. Overall results are compared with BBO, PSO, Hybrid FPAB/BBO, Hybrid ACO/SOFM and Hybrid ACO/BBO based on the kappa coefficient and overall accuracy parameters.

Keywords: image classification, firefly algorithm, satellite image classification, terrain classification

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Authors: Vesile Unver, Tulay Basak, Hatice Ayhan, Ilknur Cinar, Emine Iyigun, Nuran Tosun

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The aim of this study is to analyze the effects of the hybrid simulation. In this simulation, types standardized patients and task trainers are employed simultaneously. For instance, in order to teach the IV activities standardized patients and IV arm models are used. The study was designed as a quasi-experimental research. Before the implementation an ethical permission was taken from the local ethical commission and administrative permission was granted from the nursing school. The universe of the study included second-grade nursing students (n=77). The participants were selected through simple random sample technique and total of 39 nursing students were included. The views of the participants were collected through a feedback form with 12 items. The form was developed by the authors and “Patient intervention self-confidence/competence scale”. Participants reported advantages of the hybrid simulation practice. Such advantages include the following: developing connections between the simulated scenario and real life situations in clinical conditions; recognition of the need for learning more about clinical practice. They all stated that the implementation was very useful for them. They also added three major gains; improvement of critical thinking skills (94.7%) and the skill of making decisions (97.3%); and feeling as if a nurse (92.1%). In regard to the mean scores of the participants in the patient intervention self-confidence/competence scale, it was found that the total mean score for the scale was 75.23±7.76. The findings obtained in the study suggest that the hybrid simulation has positive effects on the integration of theoretical and practical activities before clinical activities for the nursing students.

Keywords: hybrid simulation, clinical practice, nursing education, nursing students

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Authors: Moataz Ammar, Ahdab Elmorshedy

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The distributed generation hosting capacity of a distribution network is typically limited at a given connection point by the upper voltage limit that can be violated due to the injection of active power into the distribution network. The upper voltage limit violation concern becomes more important as the network equivalent resistance increases with respect to its equivalent reactance. This paper investigates the impact of modifying the distribution network equivalent reactance at the point of connection such that the upper voltage limit is violated at a higher distributed generation penetration, than it would without the addition of series reactive compensation. The results show that series reactive compensation proves efficient in certain situations (based on the ratio of equivalent network reactance to equivalent network resistance at the point of connection). As opposed to the conventional case of capacitive compensation of a distribution network to reduce voltage drop, inductive compensation is seen to be more appropriate for alleviation of distributed-generation-induced voltage rise.

Keywords: distributed generation, distribution networks, series compensation, voltage rise

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Authors: Nidhi Gupta, Omita Nanda, Rakhi Grover, Kanchan Saxena

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Hybrid perovskite is new class of material which has gained much attention due to their different crystal structure and interesting optical and electrical properties. Easy fabrication, high absorption coefficient, and photoluminescence properties make them a strong candidate for various applications such as sensors, photovoltaics, photodetectors, etc. In perovskites, ions arrange themselves in a special type of crystal structure with chemical formula ABX3, where A is organic species like CH3NH3+, B is metal ion (e.g., Pb, Sn, etc.) and X is halide (Cl-, Br-, I-). In crystal structure, A is present at corner position, B at center of the crystal lattice and halide ions at the face centers. High stability and sensitivity of nanostructured perovskite make them suitable for chemical sensors. Researchers have studied sensing properties of perovskites for number of analytes such as 2,4,6-trinitrophenol, ethanol and other hazardous chemical compounds. Ammonia being highly toxic agent makes it a reason of concern for the environment. Thus the detection of ammonia is extremely important. Our present investigation deals with organic inorganic hybrid perovskite based ammonia sensor. Various methods like sol-gel, solid state synthesis, thermal vapor deposition etc can be used to synthesize Different hybrid perovskites. In the present work, a novel hybrid perovskite has been synthesized by a single step method. Ethylenediammnedihalide and lead halide were used as precursor. Formation of hybrid perovskite was confirmed by FT-IR and XRD. Morphological characterization of the synthesized material was performed using scanning electron microscopy (SEM). SEM analysis revealed the formation of one dimensional nanowire perovskite with mean diameter of 200 nm. Measurements for sensing properties of halide perovskite for ammonia vapor were carried out. Perovskite thin films showed a color change from yellow to orange on exposure of ammonia vapor. Electro-optical measurements show that sensor based on lead halide perovskite has high sensitivity towards ammonia with effective selectivity and reversibility. Sensor exhibited rapid response time of less than 20 seconds.

Keywords: hybrid perovskite, ammonia, sensor, nanostructure, thin film

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Authors: Mohamed E. Harb, Enas Moustafa, Shaker Ebrahim, Moataz Soliman

Abstract:

In this paper pressure detectors were synthesized and characterized using hybrid perovskite/PVDF composites as an active layer. Methylammonium lead iodide (MAPbI₃) was synthesized from methylammonium iodide (MAI) (CH₃NH₃I) and lead iodide (PbI₂). Composites of perovskite/PVDF using different weight ratio were prepared as the active material. PVDF with weights percentages of 6%, 8%, and 10% was used. All prepared materials were investigated by x-ray diffraction (XRD), Fourier transforms infrared spectrum (FTIR) and scanning electron microscopy (SEM). A Versastat 4 Potentiostat Galvanostat instrument was used to perform the current-voltage characteristics of the fabricated sensors. The pressure sensors exhibited a voltage increase with applying different forces. Also, the current-voltage characteristics (CV) showed different effects with applying forces. So, the results showed a good pressure sensing performance.

Keywords: perovskite semiconductor, hybrid perovskite, PVDF, Pressure sensing

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Authors: Mui Joo Tang, Eang Teng Chan

Abstract:

Advertising is commonly used to foster sales and reputation of an institution. It is at first the growth of print advertising that has increased the population and number of periodicals of newspaper and its circulation. The rise of Internet and online media has somehow blurred the role of media and advertising though the intention is still to reach out to audience and to increase sales. The relationship between advertising and audience on a product purchase through persuasion has been developing from print media to online media. From the changing media environment and audience, it is the concern of this research to study the impact of online advertising to such a relationship cycle. The content of online advertisements is much of text, multimedia, photo, audio and video. The messages of such content format may indeed bring impacts to its audience and its credibility. This study is therefore reflecting the effectiveness of online advertisement and its influences on generation Y in their purchasing behavior. This study uses Media Dependency Theory to analyze the relationship between the impact of online advertisement and media usage pattern of generation Y. Hierarchy of Effectiveness Model is used as a marketing communication model to study the effectiveness of advertising and further to determine the impact of online advertisement on generation Y in their purchasing decision making. This research uses online survey to reach out the sample of generation Y. The results have shown that online advertisements do not affect much on purchase decision making even though generation Y relies much on the media content including online advertisement for its information and believing in its credibility. There are few other external factors that may interrupt the effectiveness of online advertising. The very obvious influence of purchasing behavior is actually derived from the peers.

Keywords: generation Y, purchase decision, print media, online advertising, persuasion

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Authors: Gondrexon, Gonon, Mendil-Jakani, Mareau

Abstract:

Proton Exchange Membrane Fuel Cells (PEMFCs) seems to be a promising device used for converting hydrogen into electricity. PEMFC is made of a Membrane Electrode Assembly (MEA) composed of a Proton Exchange Membrane (PEM) sandwiched by two catalytic layers. Nowadays, specific performances are targeted in order to ensure the long-term expansion of this technology. Current polymers used (perfluorinated as Nafion®) are unsuitable (loss of mechanical properties) for the high-temperature range. To overcome this issue, sulfonated polyaromatic polymers appear to be a good alternative since it has very good thermomechanical properties. However, their proton conductivity and chemical stability (oxidative resistance to H2O2 formed during fuel cell (FC) operating) are very low. In our team, we patented an original concept of hybrid membranes able to fulfill the specific requirements for PEMFC. This idea is based on the improvement of commercialized polymer membrane via an easy and processable stabilization thanks to sol-gel (SG) chemistry with judicious embeded chemical functions. This strategy is thus breaking up with traditional approaches (design of new copolymers, use of inorganic charges/additives). In 2020, we presented the elaboration and functional properties of a 1st generation of hybrid membranes with promising performances and durability. The latter was made by self-condensing a SG phase with 3(mercaptopropyl)trimethoxysilane (MPTMS) inside a commercial sPEEK host membrane. The successful in-situ condensation reactions of the MPTMS was demonstrated by measures of mass uptakes, FTIR spectroscopy (presence of C-Haliphatics) and solid state NMR 29Si (T2 & T3 signals of self-condensation products). The ability of the SG phase to prevent the oxidative degradation of the sPEEK phase (thanks to thiol chemical functions) was then proved with H2O2 accelerating tests and FC operating tests. A 2nd generation made of thiourea functionalized SG precursors (named HTU & TTU) was made after. By analysing in depth the morphologies of these different hybrids by direct space analysis (AFM/SEM/TEM) and reciprocal space analysis (SANS/SAXS/WAXS), we highlighted that both SG phase morphology and its localisation into the host has a huge impact on the PEM functional properties observed. This relationship is also dependent on the chemical function embedded. The hybrids obtained have shown very good chemical resistance during aging test (exposed to H2O2) compared to the commercial sPEEK. But the chemical function used is considered as “sacrificial” and cannot react indefinitely with H2O2. Thus, we are now working on a 3rd generation made of both sacrificial/regenerative chemical functions which are expected to inhibit the chemical aging of sPEEK more efficiently. With this work, we are confident to reach a predictive approach of the key parameters governing the final properties.

Keywords: fuel cells, ionomers, membranes, sPEEK, chemical stability

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Authors: Daofan Guo, Dong Yang

Abstract:

For decades, well logging with coiled tubing has relied solely on surface data such as pump pressure, wellhead pressure, depth counter, and weight indicator readings. While this data serves the oil industry well, modern smart logging utilizes real-time downhole information, which automatically increases operational efficiency and optimizes intervention qualities. For example, downhole pressure, temperature, and depth measurement data can be transmitted through the electro-optical hybrid cable in the coiled tubing to surface operators on a real-time base. This paper mainly introduces the unique structural features and various applications of the electro-optical hybrid cables which were deployed into downhole with the help of coiled tubing technology. Fiber optic elements in the cable enable optical communications and distributed measurements, such as distributed temperature and acoustic sensing. The electrical elements provide continuous surface power for downhole tools, eliminating the limitations of traditional batteries, such as temperature, operating time, and safety concerns. The electrical elements also enable cable telemetry operation of cable tools. Both power supply and signal transmission were integrated into an electro-optical hybrid cable, and the downhole information can be captured by downhole electrical sensors and distributed optical sensing technologies, then travels up through an optical fiber to the surface, which greatly improves the accuracy of measurement data transmission.

Keywords: electro-optical hybrid cable, underground photoelectric composite cable, seismic cable, coiled tubing, real-time monitoring

Procedia PDF Downloads 127

Authors: Soha A. Bahanshal, Byung G. Kim

Abstract:

Identification of patients at high risk for hospital readmission is of crucial importance for quality health care and cost reduction. Predicting hospital readmissions among diabetic patients has been of great interest to many researchers and health decision makers. We build a prediction model to predict hospital readmission for diabetic patients within 30 days of discharge. The core of the prediction model is a modified k Nearest Neighbor called Hybrid Fuzzy Weighted k Nearest Neighbor algorithm. The prediction is performed on a patient dataset which consists of more than 70,000 patients with 50 attributes. We applied data preprocessing using different techniques in order to handle data imbalance and to fuzzify the data to suit the prediction algorithm. The model so far achieved classification accuracy of 80% compared to other models that only use k Nearest Neighbor.

Keywords: machine learning, prediction, classification, hybrid fuzzy weighted k-nearest neighbor, diabetic hospital readmission

Procedia PDF Downloads 174