Search results for: hybrid UAVs

Authors: Victor Sotero, Cindy Castro, Ena Velazco, Ursula Monteiro, Dora Garcia

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The aim of this study is to carry out the evaluation of the artificial pollination of the female flowers of E. oleifera with pollen of E. guineensis, to obtain the hybrid Palma OXG, which presents two characteristics of interest, such as high resistance to the disease of spear rot and high concentration of oleic acid. The works were carried out with matrices from the experimental fields and INIA in the Province of Colonel Portillo in the Ucayali Region-Peru. From the pollination of five species of E. oleifera, fruits were obtained in two of them, called O7 and O68, with a percentage of 23.6% and 18.6% of fertile fruits. When germination was carried out in a controlled environment of temperature, air, and humidity, only the O17 species were germinated with a yield of 68.7%.

Keywords: Elaeis oleífera, Elaeis guineensis, palm OXG, pollination

Procedia PDF Downloads 142

Authors: Olga Koutsika

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The paper deals primarily with the question of the legal framework of non-orbital flights. The submission is based upon two pillars, starting with the ill-defined current legal regime and proceeding to further recommendations for the prospective legal regime for non-orbital flights. For this reason, the paper focuses on certain key legal aspects of the topic, including among other things liability, responsibility, jurisdiction, registration and authorisation. Furthermore, taking into consideration the hybrid nature of both the craft conducting non-orbital flights and of the flights themselves, which exit airspace but do not enter an orbit in outer space, the paper addresses each legal question from the perspective of both air law and space law and concludes to a number of recommendations regarding the applicability of each legal regime for each legal question individually.

Keywords: current regime, legal framework, non-orbital flights, prospective regime

Procedia PDF Downloads 384

Authors: Abdullah Alotaiq

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The transition to low-carbon power generation is essential for mitigating climate change and achieving sustainability. This process, however, entails considerable costs, and understanding the factors influencing these costs is critical. This is necessary to cater to the increasing demand for low-carbon electricity across the heating, industry, and transportation sectors. A crucial aspect of this transition is identifying cost-effective and feasible paths for decarbonization, which is integral to global climate mitigation efforts. It is concluded that hybrid solutions, combining different low-carbon technologies, are optimal for minimizing costs and enhancing flexibility. These solutions also address the challenges associated with phasing out existing fossil fuel-based power plants and broadening the spectrum of low-carbon power generation options.

Keywords: review, power generation, energy transition, decarbonisation

Procedia PDF Downloads 54

Authors: Daniel A. Walzer

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As the options for course delivery and development expand, plenty of misconceptions still exist concerning e-learning and online course delivery. Classroom instructors often discuss pedagogy, methodologies, and best practices regarding teaching from a singular, traditional in-class perspective. As more professors integrate online, blended, and hybrid courses into their dossier, a clearly defined rubric for gauging online course delivery is essential. The transition from a traditional learning structure towards an updated distance-based format requires careful planning, evaluation, and revision. This paper examines how new media stimulates reflective practice and guided inquiry to improve pedagogy, engage interdisciplinary collaboration, and supply rich qualitative data for future research projects in media arts disciplines.

Keywords: action research, inquiry, new media, reflection

Procedia PDF Downloads 307

Authors: Soulayma Smirani, Mourad Aidi, Taoufik Aguili

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Energy harvesting has arisen as a prominent research area for low power delivery to RF devices. Rectennas have become a key element in this technology. In this paper, electromagnetic modeling of a rectenna system is presented. In our approach, a hybrid technique was demonstrated to associate both the method of auxiliary sources (MAS) and MoM-GEC (the method of moments combined with the generalized equivalent circuit technique). Auxiliary sources were used in order to substitute specific electronic devices. Therefore, a simple and controllable model is obtained. Also, it can easily be interconnected to form different topologies of rectenna arrays for more energy harvesting. At last, simulation results show the feasibility and simplicity of the proposed rectenna model with high precision and computation efficiency.

Keywords: computational electromagnetics, MoM-GEC method, rectennas, RF energy harvesting

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Authors: Feng-Sheng Wang, Chao-Ting Cheng

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Developing a drug from conception to launch is costly and time-consuming. Computer-aided methods can reduce research costs and accelerate the development process during the early drug discovery and development stages. This study developed a fuzzy multi-objective hierarchical optimization framework for identifying potential anticancer targets in a metabolic model. First, RNA-seq expression data of colorectal cancer samples and their healthy counterparts were used to reconstruct tissue-specific genome-scale metabolic models. The aim of the optimization framework was to identify anticancer targets that lead to cancer cell death and evaluate metabolic flux perturbations in normal cells that have been caused by cancer treatment. Four objectives were established in the optimization framework to evaluate the mortality of cancer cells for treatment and to minimize side effects causing toxicity-induced tumorigenesis on normal cells and smaller metabolic perturbations. Through fuzzy set theory, a multiobjective optimization problem was converted into a trilevel maximizing decision-making (MDM) problem. The applied nested hybrid differential evolution was applied to solve the trilevel MDM problem using two nutrient media to identify anticancer targets in the genome-scale metabolic model of colorectal cancer, respectively. Using Dulbecco’s Modified Eagle Medium (DMEM), the computational results reveal that the identified anticancer targets were mostly involved in cholesterol biosynthesis, pyrimidine and purine metabolisms, glycerophospholipid biosynthetic pathway and sphingolipid pathway. However, using Ham’s medium, the genes involved in cholesterol biosynthesis were unidentifiable. A comparison of the uptake reactions for the DMEM and Ham’s medium revealed that no cholesterol uptake reaction was included in DMEM. Two additional media, i.e., a cholesterol uptake reaction was included in DMEM and excluded in HAM, were respectively used to investigate the relationship of tumor cell growth with nutrient components and anticancer target genes. The genes involved in the cholesterol biosynthesis were also revealed to be determinable if a cholesterol uptake reaction was not induced when the cells were in the culture medium. However, the genes involved in cholesterol biosynthesis became unidentifiable if such a reaction was induced.

Keywords: Cancer metabolism, genome-scale metabolic model, constraint-based model, multilevel optimization, fuzzy optimization, hybrid differential evolution

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Authors: Vahid Bayrami Rad

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Ever since humans developed a collective way of life to the development of urbanization, the concern of security has always been considered one of the most important challenges of life. To protect property, locks have always been a practical tool. With the advancement of technology, the form of locks has changed from mechanical to electric. One of the most widely used fields of using artificial intelligence is its application in the technology of surveillance security systems. Currently, the technologies used in smart anti-theft door handles are one of the most potential fields for using artificial intelligence. Artificial intelligence has the possibility to learn, calculate, interpret and process by analyzing data with the help of algorithms and mathematical models and make smart decisions. We will use Arduino board to process data.

Keywords: arduino board, artificial intelligence, image processing, solenoid lock

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Authors: Xiaoyan Dai, Hsieh Yisan

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Barcode processing of captured images is a huge challenge, as different shooting conditions can result in different barcode appearances. This paper proposes a deep learning-based barcode detection using synthetic-to-real data augmentation. We first augment barcodes themselves; we then augment images containing the barcodes to generate a large variety of data that is close to the actual shooting environments. Comparisons with previous works and evaluations with our original data show that this approach achieves state-of-the-art performance in various real images. In addition, the system uses hybrid resolution for barcode “scan” and is applicable to real-time applications.

Keywords: barcode detection, data augmentation, deep learning, image-based processing

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Authors: Tamanna Jethava, Rahul Joshi

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Frequent Item sets play an essential role in many data Mining tasks that try to find interesting patterns from the database. Typically it refers to a set of items that frequently appear together in transaction dataset. There are several mining algorithm being used for frequent item set mining, yet most do not scale to the type of data we presented with today, so called “BIG DATA”. Big Data is a collection of large data sets. Our approach is to work on the frequent item set mining over the large dataset with scalable and speedy way. Big Data basically works with Map Reduce along with HDFS is used to find out frequent item sets from Big Data on large cluster. This paper focuses on using pre-processing & mining algorithm as hybrid approach for big data over Hadoop platform.

Keywords: frequent item set mining, big data, Hadoop, MapReduce

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Authors: Farina Riaz, Shahab Abdulla, Srinjoy Ganguly, Hajime Suzuki, Ravinesh C. Deo, Susan Hopkins

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Recently, quantum machine learning has received significant attention. For various types of data, including text and images, numerous quantum machine learning (QML) models have been created and are being tested. Images are exceedingly complex data components that demand more processing power. Despite being mature, classical machine learning still has difficulties with big data applications. Furthermore, quantum technology has revolutionized how machine learning is thought of, by employing quantum features to address optimization issues. Since quantum hardware is currently extremely noisy, it is not practicable to run machine learning algorithms on it without risking the production of inaccurate results. To discover the advantages of quantum versus classical approaches, this research has concentrated on colored image data. Deep learning classification models are currently being created on Quantum platforms, but they are still in a very early stage. Black and white benchmark image datasets like MNIST and Fashion MINIST have been used in recent research. MNIST and CIFAR-10 were compared for binary classification, but the comparison showed that MNIST performed more accurately than colored CIFAR-10. This research will evaluate the performance of the QML algorithm on the colored benchmark dataset CIFAR-10 to advance QML's real-time applicability. However, deep learning classification models have not been developed to compare colored images like Quantum Convolutional Neural Network (QCNN) to determine how much it is better to classical. Only a few models, such as quantum variational circuits, take colored images. The methodology adopted in this research is a hybrid approach by using penny lane as a simulator. To process the 10 classes of CIFAR-10, the image data has been translated into grey scale and the 28 × 28-pixel image containing 10,000 test and 50,000 training images were used. The objective of this work is to determine how much the quantum approach can outperform a classical approach for a comprehensive dataset of color images. After pre-processing 50,000 images from a classical computer, the QCNN model adopted a hybrid method and encoded the images into a quantum simulator for feature extraction using quantum gate rotations. The measurements were carried out on the classical computer after the rotations were applied. According to the results, we note that the QCNN approach is ~12% more effective than the traditional classical CNN approaches and it is possible that applying data augmentation may increase the accuracy. This study has demonstrated that quantum machine and deep learning models can be relatively superior to the classical machine learning approaches in terms of their processing speed and accuracy when used to perform classification on colored classes.

Keywords: CIFAR-10, quantum convolutional neural networks, quantum deep learning, quantum machine learning

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Authors: Nasser AlShawaaf

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While previous researchers have attempted to explain art museums commercialisation with reference to cultural policies, they have overlooked the phenomenon of globalisation. This study examines the causes and effects of globalisation of art museums in France. Building on arts literature, we show that the cultural policies of the French government since 1980s of cultural democratisation, cultural decentralisation, and implementing market principles on the cultural sector are leading to arts globalisation. Although globalisation is producing economic benefits and enhancing cultural reach, however, the damages include artistic values and creativity, cultural heritage and representation, and the museum itself. Art museums and host cities could overcome negative consequences through a hybrid collection display and develop local collections gradually.

Keywords: cultural policy, cultural decentralisation, cultural globalisation, art museums, contextual analysis, France

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Authors: Haythem Yahyaoui, Samir Moalla, Mounir Bouden, Skander ghorbel

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Nowadays, Cloud environments are becoming a need for companies, this new technology gives the opportunities to access to the data anywhere and anytime, also an optimized and secured access to the resources and gives more security for the data which stored in the platform, however, some companies do not trust Cloud providers, in their point of view, providers can access and modify some confidential data such as bank accounts, many works have been done in this context, they conclude that encryption methods realized by providers ensure the confidentiality, although, they forgot that Cloud providers can decrypt the confidential resources. The best solution here is to apply some modifications on the data before sending them to the Cloud in the objective to make them unreadable. This work aims on enhancing the quality of service of providers and improving the trust of the customers.

Keywords: cloud, confidentiality, cryptography, security issues, trust issues

Procedia PDF Downloads 378

Authors: E. Nakamachi, K. Matsumoto, K. Yamamoto, Y. Morita, H. Sakamoto

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In recently, electromagnetic and mechanical stimulations have been recognized as the effective extracellular environment stimulation technique to enhance the defected peripheral nerve tissue regeneration. In this study, we developed a new hybrid bioreactor by adopting 50 Hz uniform alternative current (AC) magnetic stimulation and 4% strain mechanical stimulation. The guide tube for nerve regeneration is mesh structured tube made of biodegradable polymer, such as polylatic acid (PLA). However, when neural damage is large, there is a possibility that peripheral nerve undergoes necrosis. So it is quite important to accelerate the nerve tissue regeneration by achieving enhancement of nerve axonal extension rate. Therefore, we try to design and fabricate the system that can simultaneously load the uniform AC magnetic field stimulation and the stretch stimulation to cells for enhancement of nerve axonal extension. Next, we evaluated systems performance and the effectiveness of each stimulation for rat adrenal pheochromocytoma cells (PC12). First, we designed and fabricated the uniform AC magnetic field system and the stretch stimulation system. For the AC magnetic stimulation system, we focused on the use of pole piece structure to carry out in-situ microscopic observation. We designed an optimum pole piece structure using the magnetic field finite element analyses and the response surface methodology. We fabricated the uniform AC magnetic field stimulation system as a bio-reactor by adopting analytically determined design specifications. We measured magnetic flux density that is generated by the uniform AC magnetic field stimulation system. We confirmed that measurement values show good agreement with analytical results, where the uniform magnetic field was observed. Second, we fabricated the cyclic stretch stimulation device under the conditions of particular strains, where the chamber was made of polyoxymethylene (POM). We measured strains in the PC12 cell culture region to confirm the uniform strain. We found slightly different values from the target strain. Finally, we concluded that these differences were allowable in this mechanical stimulation system. We evaluated the effectiveness of each stimulation to enhance the nerve axonal extension using PC12. We confirmed that the average axonal extension length of PC12 under the uniform AC magnetic stimulation was increased by 16 % at 96 h in our bio-reactor. We could not confirm that the axonal extension enhancement under the stretch stimulation condition, where we found the exfoliating of cells. Further, the hybrid stimulation enhanced the axonal extension. Because the magnetic stimulation inhibits the exfoliating of cells. Finally, we concluded that the enhancement of PC12 axonal extension is due to the magnetic stimulation rather than the mechanical stimulation. Finally, we confirmed that the effectiveness of the uniform AC magnetic field stimulation for the nerve axonal extension using PC12 cells.

Keywords: nerve cell PC12, axonal extension, nerve regeneration, electromagnetic-mechanical stimulation, bioreactor

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Authors: Sanchayan Banerjee, Peter John

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Nudge plus is a modification of the toolkit of behavioural public policy. It incorporates an element of reflection¾the plus¾into the delivery of a nudge, either blended in or made proximate. Nudge plus builds on recent work combining heuristics and deliberation. It may be used to design pro-social interventions that help preserve the autonomy of the agent. The argument turns on seminal work on dual systems, which presents a subtler relationship between fast and slow thinking than commonly assumed in the classic literature in behavioural public policy. We review classic and recent work on dual processes to show that a hybrid is more plausible than the default interventionist or parallel competitive framework. We define nudge plus, set out what reflection could entail, provide examples, outline causal mechanisms, and draw testable implications.

Keywords: nudge, nudge plus, think, dual process theory

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Authors: G. Hemath Kumar, H. Mohit, K. Karthick

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One of the most important issues in the composite technology is the repairing of parts of aircraft structures which is manufactured from composite materials. In such applications and also for joining various composite parts together, they are fastened together either using adhesives or mechanical fasteners. The tensile strength of these joints was carried out using Universal Testing Machine (UTM). A parametric study was also conducted to compare the performance of the hybrid joint with varying adherent thickness, adhesive thickness and overlap length. The composition of the material is combination of epoxy resin and carbon fibre under the method of reinforcement. To utilize the full potential of composite materials as structural elements, the strength and stress distribution of these joints must be understood. The study of tensile strength in the members involved under various design conditions and various joints were took place.

Keywords: carbon fiber, FRP composite, MMC, automotive

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Authors: Diamant Irene, Shklarnik Batya

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In on to its widespread effects on health and economic issues, Covid-19 shook the work and employment world. Among the prominent changes during the pandemic is the work-from-home trend, complete or partial, as part of social distancing. In fact, these changes accelerated an existing tendency of work flexibility already underway before the pandemic. Technology and means of advanced communications led to a re-assessment of “place of work” as a physical space in which work takes place. Today workers can remotely carry out meetings, manage projects, work in groups, and different research studies point to the fact that this type of work has no adverse effect on productivity. However, from the worker’s perspective, despite numerous advantages associated with work from home, such as convenience, flexibility, and autonomy, various drawbacks have been identified such as loneliness, reduction of commitment, home-work boundary erosion, all risk factors relating to the quality of life and burnout. Thus, a real need has arisen in exploring differences in work-from-home experiences and understanding the relationship between psychological characteristics and the prevalence of burnout. This understanding may be of significant value to organizations considering a future hybrid work model combining in-office and remote working. Based on Hobfoll’s Theory of Conservation of Resources, we hypothesized that burnout would mainly be found among workers whose physical remoteness from the workplace threatens or hinders their ability to retain significant individual resources. In the present study, we compared fully remote and partially remote workers (hybrid work), and we examined psychological characteristics and their connection to the formation of burnout. Based on the conceptualization of Place Attachment as the cognitive-emotional bond of an individual to a meaningful place and the need to maintain closeness to it, we assumed that individuals characterized with Place Attachment to the workplace would suffer more from burnout when working from home. We also assumed that extrovert individuals, characterized by the need of social interaction at the workplace and individuals with segmentationpreference – a need for separation between different life domains, would suffer more from burnout, especially among fully remote workers relative to partially remote workers. 194 workers, of which 111 worked from home in full and 83 worked partially from home, aged 19-53, from different sectors, were tested using an online questionnaire through social media. The results of the study supported our assumptions. The repercussions of these findings are discussed, relating to future occupational experience, with an emphasis on suitable occupational adjustment according to the psychological characteristics and needs of workers.

Keywords: working from home, burnout, place attachment, extraversion, segmentation preference, Covid-19

Procedia PDF Downloads 191

Authors: Luvisa Kusuma, Panji Yudha Prakasa

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Cloud storage, as a subservice of infrastructure as a service (IaaS) in Cloud Computing, is the model of nerworked storage where data can be stored in server. In this paper, we propose a secure cloud storage system consisting of two main components; client as a user who uses the cloud storage service and server who provides the cloud storage service. In this system, we propose the protocol schemes to guarantee against security attacks in the data transmission. The protocols are login protocol, upload data protocol, download protocol, and push data protocol, which implement hybrid cryptographic mechanism based on data encryption before it is sent to the cloud, so cloud storage provider does not know the user's data and cannot analysis user’s data, because there is no correspondence between data and user.

Keywords: cloud storage, security, cryptographic protocol, artificial intelligence

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Authors: Yashfeen Khan, Anees Ahmad

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In the last few decades, nano-composites have been the topic of interest. Presently, the modern era enlightens the synthesis of hybrid nano-composites over their individual counterparts because of higher application potentials and synergism. Recently, CNT hybrids have demonstrated their pronounced capability as effective sorbents for the removal of heavy metal ions (the root trouble) and organic contaminants due to their high specific surface area, enhanced reactivity, and sequestration characteristics. The present abstract discusses removal efficiencies of organic, inorganic pollutants through CNT/PANI/ composites. It also represents the widespread applications of CNT like monitoring biological systems, biosensors, as heat resources for treating cancer, fire retardant applications of polymer/CNT composites etc. And considering the same, this article aims to brief the scenario of CNT-PANI nano-composites.

Keywords: biosensors, CNT, hybrids, polyaniline, synergism

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Authors: Syed Auon Raza, Tahir Mahmood, Syed Basit Ali Bukhari

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In power system properly coordinated protection scheme is designed to make sure that only the faulty part of the system will be isolated when abnormal operating condition of the system will reach. The complexity of the system as well as the increased user demand and the deregulated environment enforce the utilities to improve system reliability by using a properly coordinated protection scheme. This paper presents overview of over current relay coordination techniques. Different techniques such as Deterministic Techniques, Meta Heuristic Optimization techniques, Hybrid Optimization Techniques, and Trial and Error Optimization Techniques have been reviewed in terms of method of their implementation, operation modes, nature of distribution system, and finally their advantages as well as the disadvantages.

Keywords: distribution system, relay coordination, optimization, Plug Setting Multiplier (PSM)

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Authors: Balarabe Nkom, Adam P. R. Taylor, Craig Baguley

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Power Line Communications (PLC) is being employed in existing power systems, despite the infrastructure not being designed with PLC considerations in mind. Given that power transformers can last for decades, the distribution transformer in particular exists as a relic of un-optimized technology. To determine issues that may need to be addressed in subsequent designs of such transformers, it is essential to have a highly accurate transformer model for simulations and subsequent optimization for the PLC environment, with a view to increase data speed, throughput, and efficiency, while improving overall system stability and reliability. This paper reviews various methods currently available for creating transformer models and provides insights into the requirements of each for obtaining high accuracy. The review indicates that a combination of traditional analytical methods using a hybrid approach gives good accuracy at reasonable costs.

Keywords: distribution transformer, modelling, optimization, power line communications

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Authors: Bandar Ali Al-Asbahi, Mohammad Hafizuddin Haji Jumali

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Forster energy transfer between poly (9,9'-di-n-octylfluorenyl-2,7-diyl) (PFO)/TiO2 nanoparticles (NPs) as a donor and Fluorol 7GA as an acceptor has been studied. The energy transfer parameters were calculated by using mathematical models. The dominant mechanism responsible for the energy transfer between the donor and acceptor molecules was Forster-type, as evidenced by large values of quenching rate constant, energy transfer rate constant and critical distance of energy transfer. Moreover, these composites which were used as an emissive layer in organic light emitting diodes, were investigated in terms of current density–voltage and electroluminescence spectra.

Keywords: energy transfer parameters, forster-type, electroluminescence, organic light emitting diodes

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Authors: Budimir S. Sudimac, Andjela N. Dubljevic

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The aim of thisresearch paper is to consider possibilities for improving the street lighting on the E75 highway, which passes through Serbia, using renewable sources of energy. In this paper, we analyzed the possibilities for installing sound barriers along the highway and integrating photovoltaic (PV) modules, which would generate electrical energy to power the lighting on the section of the highway running through Belgrade. The main aim of this paper is to analyze, show and promote innovative, hybrid, multi-functional solar technology using PV modules as an element of sound barriers in urban areas. The paper seeks to show the hybridity of using sustainable technologies in solving environmental issues. This structure solves the problem of noise in populated areas and provides the electricity from renewable source.

Keywords: noise, PV modules, solar energy, sound barriers

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Authors: Boukhatem Mohammed Belkaid, Lahdir Mourad

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In this paper, we propose a new encryption system for security issues meteorological images from Meteosat Second Generation (MSG), which generates 12 images every 15 minutes. The hybrid encryption scheme is based on AES and RSA algorithms to validate the three security services are authentication, integrity and confidentiality. Privacy is ensured by AES, authenticity is ensured by the RSA algorithm. Integrity is assured by the basic function of the correlation between adjacent pixels. Our system generates a unique password every 15 minutes that will be used to encrypt each frame of the MSG meteorological basis to strengthen and ensure his safety. Several metrics have been used for various tests of our analysis. For the integrity test, we noticed the efficiencies of our system and how the imprint cryptographic changes at reception if a change affects the image in the transmission channel.

Keywords: AES, RSA, integrity, confidentiality, authentication, satellite MSG, encryption, decryption, key, correlation

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Authors: Tarek Aboueldahab, Amin Mohamed Nassar

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Wind energy is a fluctuating energy source unlike conventional power plants, thus, it is necessary to accurately predict short term wind speed to integrate wind energy in the electricity supply structure. To do so, we present a hybrid artificial intelligence model of short term wind speed prediction based on passive aggregation of the particle swarm optimization and neural networks. As a result, improvement of the prediction accuracy is obviously obtained compared to the standard artificial intelligence method.

Keywords: artificial intelligence, neural networks, particle swarm optimization, passive aggregation, wind speed prediction

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Authors: Elizabeth O. Odewale, Sachithra T. Wanasinghe, Aaron S. Rury

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Cavity polaritons form when molecular excitons strongly couple to photons in carefully constructed optical cavities. These polaritons, which are hybrid light-matter states possessing a unique combination of photonic and excitonic properties, present the opportunity to manipulate the properties of various semiconductor materials. The systematic manipulation of materials through polariton formation could potentially improve the functionalities of many optoelectronic devices such as lasers, light-emitting diodes, photon-based quantum computers, and solar cells. However, the prospects of leveraging polariton formation for novel devices and device operation depend on more complete connections between the properties of molecular chromophores, and the hybrid light-matter states they form, which remains an outstanding scientific goal. Specifically, for most optoelectronic applications, it is paramount to understand how polariton formation affects the spectra of light absorbed by molecules coupled strongly to cavity photons. An essential feature of a polariton state is its dispersive energy, which occurs due to the enhanced spatial delocalization of the polaritons relative to bare molecules. To leverage the spatial delocalization of cavity polaritons, angle-resolved photoluminescence excitation spectroscopy was employed in characterizing light emission from the polaritonic states. Using lasers of appropriate energies, the polariton branches were resonantly excited to understand how molecular light absorption changes under different strong light-matter coupling conditions. Since an excited state has a finite lifetime, the photon absorbed by the polariton decays non-radiatively into lower-lying molecular states, from which radiative relaxation to the ground state occurs. The resulting fluorescence is collected across several angles of excitation incidence. By modeling the behavior of the light emission observed from the lower-lying molecular state and combining this result with the output of angle-resolved transmission measurements, inferences are drawn about how the behavior of molecules changes when they form polaritons. These results show how the intrinsic properties of molecules, such as the excitonic lifetime, affect the rate at which the polaritonic states relax. While it is true that the lifetime of the photon mediates the rate of relaxation in a cavity, the results from this study provide evidence that the lifetime of the molecular exciton also limits the rate of polariton relaxation.

Keywords: flourescece, molecules in cavityies, optical cavity, photoluminescence excitation, spectroscopy, strong coupling

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Authors: Pakize Neslihan Taslı, Alev Cumbul, Gul Merve Yalcın, Fikrettin Sahin

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A key experimental trial in the regeneration of large oral and craniofacial defects is the neogenesis of osseous and ligamentous interfacial structures. Currently, oral regenerative medicine strategies are unpredictable for repair of tooth supporting tissues destroyed as a consequence of trauma, chronic infection or surgical resection. A different approach combining the gel-casting method with Hydroxy Apatite HA-based scaffold and different cell lineages as a hybrid system leads to successively mimic the early stage of tooth development, in vitro. HA is widely accepted as a bioactive material for guided bone and tooth regeneration. In this study, it was reported that, HA porous scaffold preparation, characterization and evaluation of structural and chemical properties. HA is the main factor that exists in tooth and it is in harmony with structural, biological, and mechanical characteristics. Here, this study shows mimicking immature tooth at the late bell stage design and construction of HA scaffolds for cell transplantation of human Adipose Stem Cells (hASCs), human Bone Marrow Stem Cells (hBMSCs) and Gingival Epitelial cells for the formation of human tooth dentin-pulp-enamel complexes in vitro. Scaffold characterization was demonstrated by SEM, FTIR and pore size and density measurements. The biological contraction of dental tissues against each other was demonstrated by mRNA gene expressions, histopatologic observations and protein release profile by ELISA tecnique. The tooth shaped constructs with a pore size ranging from 150 to 300 µm arranged by gathering right amounts of materials provide interconnected macro-porous structure. The newly formed tissue like structures that grow and integrate within the HA designed constructs forming tooth cementum like tissue, pulp and bone structures. These findings are important as they emphasize the potential biological effect of the hybrid scaffold system. In conclusion, this in vitro study clearly demonstrates that designed 3D scaffolds shaped as a immature tooth at the late bell stage were essential to form enamel-dentin-pulp interfaces with an appropriate cell and biodegradable material combination. The biomimetic architecture achieved here is providing a promising platform for dental tissue engineering.

Keywords: tooth regeneration, tissue engineering, adipose stem cells, hydroxyapatite tooth engineering, porous scaffold

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Authors: Swati Tomar, Sunil Kumar Gupta

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Anammox is a novel and promising technology that has changed the traditional concept of biological nitrogen removal. The process facilitates direct oxidation of ammonical nitrogen under anaerobic conditions with nitrite as an electron acceptor without the addition of external carbon sources. The present study investigated the feasibility of anammox hybrid reactor (AHR) combining the dual advantages of suspended and attached growth media for biodegradation of ammonical nitrogen in wastewater. The experimental unit consisted of 4 nos. of 5L capacity AHR inoculated with mixed seed culture containing anoxic and activated sludge (1:1). The process was established by feeding the reactors with synthetic wastewater containing NH4-H and NO2-N in the ratio 1:1 at HRT (hydraulic retention time) of 1 day. The reactors were gradually acclimated to higher ammonium concentration till it attained pseudo steady state removal at a total nitrogen concentration of 1200 mg/l. During this period, the performance of the AHR was monitored at twelve different HRTs varying from 0.25-3.0 d with increasing NLR from 0.4 to 4.8 kg N/m3d. AHR demonstrated significantly higher nitrogen removal (95.1%) at optimal HRT of 1 day. Filter media in AHR contributed an additional 27.2% ammonium removal in addition to 72% reduction in the sludge washout rate. This may be attributed to the functional mechanism of filter media which acts as a mechanical sieve and reduces the sludge washout rate many folds. This enhances the biomass retention capacity of the reactor by 25%, which is the key parameter for successful operation of high rate bioreactors. The effluent nitrate concentration, which is one of the bottlenecks of anammox process was also minimised significantly (42.3-52.3 mg/L). Process kinetics was evaluated using first order and Grau-second order models. The first-order substrate removal rate constant was found as 13.0 d-1. Model validation revealed that Grau second order model was more precise and predicted effluent nitrogen concentration with least error (1.84±10%). A new mathematical model based on mass balance was developed to predict N2 gas in AHR. The mass balance model derived from total nitrogen dictated significantly higher correlation (R2=0.986) and predicted N2 gas with least error of precision (0.12±8.49%). SEM study of biomass indicated the presence of the heterogeneous population of cocci and rod shaped bacteria of average diameter varying from 1.2-1.5 mm. Owing to enhanced NRE coupled with meagre production of effluent nitrate and its ability to retain high biomass, AHR proved to be the most competitive reactor configuration for dealing with nitrogen laden wastewater.

Keywords: anammox, filter media, kinetics, nitrogen removal

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Authors: Muhammad Abid

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Utilization of renewable energy resources for energy conservation, pollution prevention, resource efficiency and systems integration is very important for sustainable development. In this study, we perform energy and exergy analyses of a wind turbine, located on the roof of Mechanical Engineering Department, King Saud University, and Riyadh, Saudi Arabia. The turbine is part of a hybrid photovoltaic (PV)-wind system with hydrogen storage. The power output from this turbine varies between 1.5 and 5.5 kW with a rated wind speed of 12 m/s and a cut-in wind speed of 2.4 m/s. We utilize a wide range of experimental data in the analysis and assessment. We determine energy and exergy efficiencies. The energy efficiency changes between 0% to 45% while the exergy efficiency varies between 0% and 31.3%. We also determined some of the exergoeconomic parameters that are the ratios of energy and exergy loss rates to the capital cost (R en and R ex), respectively. (R en) changes between 0.96% and 59.03% for different values of velocity while R ex has a maximum value of 53.62% for the highest wind speed.

Keywords: exergy, efficiency, performance evaluation, wind energy

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Authors: G. Gurguze, I. Turkoglu

Abstract:

Today, the developing features of technological tools with limited energy resources have made it necessary to use energy efficiently. Energy management techniques have emerged for this purpose. As with every field, energy management is vital for robots that are being used in many areas from industry to daily life and that are thought to take up more spaces in the future. Particularly, effective power management in autonomous and multi robots, which are getting more complicated and increasing day by day, will improve the performance and success. In this study, robot management algorithms, usage of renewable and hybrid energy sources, robot motion patterns, robot designs, sharing strategies of workloads in multiple robots, road and mission planning algorithms are discussed for efficient use of energy resources by mobile robots. These techniques have been evaluated in terms of efficient use of existing energy resources and energy management in robots.

Keywords: energy management, mobile robot, robot administration, robot management, robot planning

Procedia PDF Downloads 269

Authors: Mohamed Roudane

Abstract:

The objective of this study is to know the dynamic behavior of a multi swirling jet used for air conditioning inside a room. To conduct this study, we designed a facility to ensure proper conditions of confinement in which we placed five air blowing devices with adjustable vanes, providing multiple swirling turbulent jets. The jets were issued in the same direction and the same spacing defined between them. This study concerned the numerical simulation of the dynamic mixing of confined swirling multi-jets, and examined the influence of important parameters of a swirl diffuser system on the dynamic performance characteristics. The CFD investigations are carried out by a hybrid mesh to discretize the computational domain. In this work, the simulations have been performed using the finite volume method and FLUENT solver, in which the standard k-ε RNG turbulence model was used for turbulence computations.

Keywords: simulation, dynamic behavior, swirl, turbulent jet

Procedia PDF Downloads 399