Search results for: nanofluid applications

Authors: Pavan Shah

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In an Embedded system, Virtualization and visualization technology can provide us an effective response and measurable work in a software development environment. In addition to work of virtualization and virtualization can be easily deserved to provide the best resource sharing between real-time hardware applications and a healthy environment. However, the virtualization is noticeable work to minimize the I/O work and utilize virtualization & virtualization technology for either a software development environment (SDE) or a runtime environment of real-time embedded systems (RTMES) or real-time operating system (RTOS) eras. In this Paper, we particularly focus on virtualization and visualization overheads data of network which generates the I/O and implementation of standardized I/O (i.e., Virto), which can work as front-end network driver in a real-time operating system (RTOS) hardware module. Even there have been several work studies are available based on the virtualization operating system environment, but for the Virto on a general-purpose OS, my implementation is on the open-source Virto for a real-time operating system (RTOS). In this paper, the measurement results show that implementation which can improve the bandwidth and latency of memory management of the real-time operating system environment (RTMES) for getting more accuracy of the trained model.

Keywords: virtualization, visualization, network driver, operating system

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Authors: Aicha Bouhlala, Sabah Chettibi

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Doping CeO₂ with transition metals is an effective way of tuning its properties. In the present work, we have performed self-consistent ab-initio calculation using the full-potential linearized augmented plane-wave method (FP-LAPW), based on the density functional theory (DFT) as implemented in the Wien2k simulation code to study the structural, electronic, and magnetic properties of the compound Ce₁₋ₓCuₓO₂ (x=12.5%) fluorite type oxide and to explore the effects of dopant Cu in ceria. The exchange correlation potential has been treated using the Perdew-Burke-Eenzerhof revised of solid (PBEsol). In structural properties, the equilibrium lattice constant is observed for the compound, which exists within the value of 5.382 A°. In electronic properties, the spin-polarized electronic bandstructure elucidates the semiconductor nature of the material in both spin channels, with the compound was observed to have a narrow bandgap on the spin-down configuration (0.162 EV) and bandgap on the spin-up (2.067 EV). Hence, the doped atom Cu plays a vital role in increasing the magnetic moments of the supercell, and the value of the total magnetic moment is found to be 2.99438 μB. Therefore, the compound Cu-doped CeO₂ shows a strong ferromagnetic behavior. The predicted results propose the compound could be a good candidate for spintronics applications.

Keywords: Cu-doped CeO₂, DFT, Wien2k, properties

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Authors: Sakir Tasdemir, Mustafa Altin, Gamze Fahriye Pehlivan, Sadiye Didem Boztepe Erkis, Ismail Saritas, Selma Tasdemir

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Artificial intelligence applications are commonly used in industry in many fields in parallel with the developments in the computer technology. In this study, a fire room was prepared for the resistance of wooden construction elements and with the mechanism here, the experiments of polished materials were carried out. By utilizing from the experimental data, an artificial neural network (ANN) was modeled in order to evaluate the final cross sections of the wooden samples remaining from the fire. In modelling, experimental data obtained from the fire room were used. In the system developed, the first weight of samples (ws-gr), preliminary cross-section (pcs-mm2), fire time (ft-minute), fire temperature (t-oC) as input parameters and final cross-section (fcs-mm2) as output parameter were taken. When the results obtained from ANN and experimental data are compared after making statistical analyses, the data of two groups are determined to be coherent and seen to have no meaning difference between them. As a result, it is seen that ANN can be safely used in determining cross sections of wooden materials after fire and it prevents many disadvantages.

Keywords: artificial neural network, final cross-section, fire retardant polishes, fire safety, wood resistance.

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Authors: Sadaf Ilyas

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Recombinant cytokines have been employed successfully as potential therapeutic agent. Some cytokine therapies are already used as a part of clinical practice, ranging from early exploratory trials to well established therapies that have already received approval. Interleukin 15 is a pleiotropic cytokine having multiple roles in peripheral innate and adaptive immune cell function. It regulates the activation, proliferation and maturation of NK cells, T-cells, monocytes/macrophages and granulocytes, and the interactions between them thus acting as a bridge between innate and adaptive immune responses. Unraveling the biology of IL-15 has revealed some interesting surprises that may point toward some of the first therapeutic applications for this cytokine. In this study, the human interleukin 15 gene was isolated, amplified and ligated to a TA vector which was then transfected to a bacterial host, E. coli Top10F’. The sequence of cloned gene was confirmed and it showed 100% homology with the reported sequence. The confirmed gene was then subcloned in pET Expression system to study the IPTG induced expression of IL-15 gene. Positive expression was obtained for number of clones that showed 15 kd band of IL-15 in SDS-PAGE analysis, indicating the successful strain development that can be studied further to assess the potential therapeutic intervention of this cytokine in relevance to human diseases.

Keywords: Interleukin 15, pET expression system, immune therapy, protein purification

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Authors: A. Panacek, M. Kilianova, R. Prucek, V. Husickova, R. Vecerova, M. Kolar, L. Kvitek, R. Zboril

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In this work we describe the preparation of NanoSilver/methylcellulose hydrogel containing silver nanoparticles (NPs) for topical bactericidal applications. Highly concentrated dispersion of silver NPs as high as of 5g/L of silver with diameter of 10nm was prepared by reduction of AgNO3 via strong reducing agent NaBH4. Silver NPs were stabilized by addition of sodium polyacrylate in order to prevent their aggregation at such high concentration. This way synthesized silver NPs were subsequently incorporated into methylcellulose suspension at elevated temperature resulting in formation of NanoSilver/methylcellulose hydrogel when temperature cooled down to laboratory conditions. In vitro antibacterial activity assay proved high bactericidal and fungicidal efficiency of silver NPs alone in the form of dispersion as well as in the form of hydrogel against broad spectrum of bacteria and yeasts including highly multiresistant strains such as methicillin-resistant Staphylococcus aureus. A very low concentrations of silver as low as 0.84mg/L Ag in as-prepared dispersion gave antibacterial performance. NanoSilver/methylcellulose hydrogel showed antibacterial action at the lowest used silver concentration equal to 25mg/L. Such prepared NanoSilver/methylcellulose hydrogel represent promising topical antimicrobial formulation for treatment of burns and wounds.

Keywords: antimicrobial, burn, hydrogel, silver NPs

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Authors: R. Simutis, V. Galvanauskas, D. Levisauskas, J. Repsyte, V. Grincas

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This paper deals with advanced state estimation algorithms for estimation of biomass concentration and specific growth rate in a typical fed-batch biotechnological process. This biotechnological process was represented by a nonlinear mass-balance based process model. Extended Kalman Filter (EKF) and Particle Filter (PF) was used to estimate the unmeasured state variables from oxygen uptake rate (OUR) and base consumption (BC) measurements. To obtain more general results, a simplified process model was involved in EKF and PF estimation algorithms. This model doesn’t require any special growth kinetic equations and could be applied for state estimation in various bioprocesses. The focus of this investigation was concentrated on the comparison of the estimation quality of the EKF and PF estimators by applying different measurement noises. The simulation results show that Particle Filter algorithm requires significantly more computation time for state estimation but gives lower estimation errors both for biomass concentration and specific growth rate. Also the tuning procedure for Particle Filter is simpler than for EKF. Consequently, Particle Filter should be preferred in real applications, especially for monitoring of industrial bioprocesses where the simplified implementation procedures are always desirable.

Keywords: biomass concentration, extended Kalman filter, particle filter, state estimation, specific growth rate

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Authors: Telesphore Tiendrebeogo, Oumarou Sié

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Cloud computing technologies have attracted considerable interest in recent years. Thus, these latters have become more important for many existing database applications. It provides a new mode of use and of offer of IT resources in general. Such resources can be used “on demand” by anybody who has access to the internet. Particularly, the Cloud platform provides an ease to use interface between providers and users, allow providers to develop and provide software and databases for users over locations. Currently, there are many Cloud platform providers support large scale database services. However, most of these only support simple keyword-based queries and can’t response complex query efficiently due to lack of efficient in multi-attribute index techniques. Existing Cloud platform providers seek to improve performance of indexing techniques for complex queries. In this paper, we define a new cloud computing architecture based on a Distributed Hash Table (DHT) and design a prototype system. Next, we perform and evaluate our cloud computing indexing structure based on a hyperbolic tree using virtual coordinates taken in the hyperbolic plane. We show through our experimental results that we compare with others clouds systems to show our solution ensures consistence and scalability for Cloud platform.

Keywords: virtual coordinates, cloud, hyperbolic plane, storage, scalability, consistency

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Authors: S. Larbi, R. Bensaada, S. Djebali, A. Bilek

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The manufacture of composite parts is a major issue in many industrial domains. Polymer composite materials are ideal for structural applications where high strength-to-weight and stiffness-to-weight ratios are required. However, exposition to extreme environment conditions (temperature, humidity) affects mechanical properties of organic composite materials and lead to an undesirable degradation. Aging mechanisms in organic matrix are very diverse and vary according to the polymer and the aging conditions such as temperature, humidity etc. This paper studies the hygrothermal aging effect on the mechanical properties of fiber reinforced plastics laminates at 40 °C in different environment exposure. Two composite materials are used to conduct the study (carbon fiber/epoxy and glass fiber/vinyl ester with two stratifications for both the materials [904/04] and [454/04]). The experimental procedure includes a mechanical characterization of the materials in a virgin state and exposition of specimens to two environments (seawater and demineralized water). Absorption kinetics for the two materials and both the stratifications are determined. Three-point bending test is performed on the aged materials in order to determine the hygrothermal effect on the mechanical properties of the materials.

Keywords: FRP laminates, hygrothermal aging, mechanical properties, theory of laminates

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Authors: M. L. Ibrahim, A. Abdulhamid

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A surface active molecule synthesized by a rhizobacterial strain Bacillus lentus isolated from Cajanus cajan was investigated. The bioemulsifier was extracted, purified and partially characterized using standard methods. Surface properties of the bioemulsifier were determined by studying the emulsification index, solubility test and stability studies. Partial purification of the bioemulsifier was carried out using FT-IR analysis, Silica-gel column chromatography and thin layer chromatography. GC-MS analysis was carried out to detect the composition and mass of the lipids and esters. The isolate showed an emulsifying activity of 57% and surface activity of 36mm. The stability studies revealed that the bioemulsifier had better stability at temperature of 70oC, 8% pH and 8% NaCl concentration. FT-IR indicated the bioemulsifier to contain peptide and aliphatic chain, TLC revealed the compound to be ninhydrin positive and Column chromatography showed the presence of three amino acids namely; glutamine, valine and cysteine. GC-MS indicated the lipid moiety to contain aliphatic chain ranging from C9-C16 and two major peaks of 1,2-benzenedicarboxylic acid diethyl octyl ester. Therefore, surface active agent from Bacillus lentus can be used effectively in a wide range of applications such as in MEOR and in the biosynthesis of plasticizers for industrial uses.

Keywords: Bacillus lentus, bioemulsifiers, phthalic acid ester, Rhizosphere

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Authors: Niels Grataloup, Micael S. Couceiro, Manousos Valyrakis, Javier Escudero, Patricia A. Vargas

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This paper benchmarks the possible underwater communication technologies that can be integrated into a swarm of underwater robots by proposing an underwater robot simulator named CORSICA (Cross platfORm wireleSs communICation simulator). Underwater exploration relies increasingly on the use of mobile robots, called Autonomous Underwater Vehicles (AUVs). These robots are able to reach goals in harsh underwater environments without resorting to human divers. The introduction of swarm robotics in these scenarios would facilitate the accomplishment of complex tasks with lower costs. However, swarm robotics requires implementation of communication systems to be operational and have a non-deterministic behaviour. Inter-robot communication is one of the key challenges in swarm robotics, especially in underwater scenarios, as communication must cope with severe restrictions and perturbations. This paper starts by presenting a list of the underwater propagation models of acoustic and electromagnetic waves, it also reviews existing transmitters embedded in current robots and simulators. It then proposes CORSICA, which allows validating the choices in terms of protocol and communication strategies, whether they are robot-robot or human-robot interactions. This paper finishes with a presentation of possible integration according to the literature review, and the potential to get CORSICA at an industrial level.

Keywords: underwater simulator, robot-robot underwater communication, swarm robotics, transceiver and communication models

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Authors: Vikas Chawla, Buta Singh Sidhu, Amita Rani, Amit Handa

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The main objective of the present work is microstructural and mechanical characterization of the conventional and nanostructured TiAlN and AlCrN coatings deposited on T-11 boiler steel. In case of conventional coatings, Al-Cr and Ti-Al metallic powders were deposited using plasma spray process followed by gas nitriding of the surface which was done in the lab with optimized parameters after conducting several trials on plasma-sprayed coated specimens. The physical vapor deposition process (PAPVD) was employed for depositing nanostructured TiAlN and AlCrN coatings. The field emission scanning electron microscopy (FE-SEM) with energy dispersive X-ray analysis (EDAX) attachment, X-ray diffraction (XRD) analysis, atomic force microscopy (AFM) analysis and the X-Ray mapping analysis techniques have been used to study surface and cross-sectional morphology of the coatings. The surface roughness and micro-hardness were also measured. A good adhesion of the conventional thick TiAlN and AlCrN coatings was found. The coatings under study are recommended for the applications to super-heater and re-heater tubes of the boilers based upon the outcomes of the research work.

Keywords: nanostructure, physical vapour deposition, oxides, thin films, electron microscopy

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Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

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This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

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Authors: Sangram Shamrao Patil, Hara Mohan Jena

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Phthalates are among the most common organic pollutant since they have become widespread in the environment and found in sediments, natural waters, soils, plants, landfill leachates, biota including human tissue and aquatic organisms. Diethyl phthalate (DEP) is a low molecular weight phthalate which has wide applications as plasticizer and become a major cause of environmental pollution. Environmental protection agency (EPA) listed DEP as priority pollutant because of its toxicity and they recommended human health ambient water quality criterion for diethyl phthalate (DEP) as 4 mg/l. Therefore, wastes containing phthalates require proper treatment before being discharged into the environment. Biodegradation is attractive and efficient treatment method as it is cost effective and produces non-toxic end products. In the present study, a DEP degrading aerobic bacterium was isolated from soil contaminated with plastic industry wastewater. Morphological and biochemical characteristics of isolate were performed. 16S rRNA sequencing and phylogenetic analysis of isolate was carried out and it was identified as Empedobacter brevis. Isolate has been found to tolerate up to 1650 mg/l of DEP. This study will be significant for exploring an application of microbes for remediation of phthalates and development of a suitable bioreactor.

Keywords: diethyl phthalate, plasticizer, pollutant, biodegradation

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Authors: Josephine Wanja Nyatia

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The relationship between vegetation and soil erosion deserves attention due to its scientific importance and practical applications. A great deal of information is available about the mechanisms and benefits of vegetation in the control of soil erosion, but the effects of soil erosion on vegetation development and succession is poorly documented. Research shows that soil erosion is the most important driving force for the degradation of upland and mountain ecosystems. Soil erosion interferes with the process of plant community development and vegetation succession, commencing with seed formation and impacting throughout the whole growth phase and affecting seed availability, dispersal, germination and establishment, plant community structure and spatial distribution. There have been almost no studies on the effects of soil erosion on seed development and availability, of surface flows on seed movement and redistribution, and their influences on soil seed bank and on vegetation establishment and distribution. However, these effects may be the main cause of low vegetation cover in regions of high soil erosion activity, and these issues need to be investigated. Moreover, soil erosion is not only a negative influence on vegetation succession and restoration but also a driving force of plant adaptation and evolution. Consequently, we need to study the effects of soil erosion on ecological processes and on development and regulation of vegetation succession from the points of view of pedology and vegetation, plant and seed ecology, and to establish an integrated theory and technology for deriving practical solutions to soil erosion problems

Keywords: soil erosion, vegetation, development, seed availability

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Authors: Arunas Stirke, Neringa Bakute, Gatis Mozolevskis

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A technology of microfluidics is an emerging tool in the field of biology, medicine and chemistry. Microfluidic device is also known as ‘lab-on-a-chip’ technology [1]. In moving from macro- to microscale, there is unprecedented control over spatial and temporal gradients and patterns that cannot be captured in conventional Petri dishes and well plates [2]. However, there is not a single standard microfluidic chip designated for all purposes – every different field of studies needs a specific microchip with certain geometries, inlet/outlet, channel depth and other parameters to precisely regulate the required function. Since our group is studying an effect of pulsed electric field (PEF) to the cells, we have manufactured a microfluidic chip designated for high-throughput electroporation of cells. In our microchip, a cell culture chamber is divided into two parallel channels by a membrane, meanwhile electrodes for electroporation are attached to the wall of the channels. Both microchannels have their own inlet and outlet, enabling injection of transfection material separately. Our perspective is to perform electroporation of mammalian cells in two different ways: (1) plasmid and cells are injected in the same microchannel and (2) injected into separate microchannels. Moreover, oxygen and pH sensors are integrated on order to analyse cell viability parameters after PEF treatment.

Keywords: microfluidics, chip, fabrication, electroporation

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Authors: Duyen Lam, Thuong Hoang, Atul Sajjanhar, Feifei Chen

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With the emerging interactive technology applications helping users connect progressively with cultural artefacts in new approaches, the cultural heritage sector gains significantly. The interactive apps’ issues can be tested via several techniques, including usability surveys and usability evaluations. The severe usability problems for museums’ interactive technologies commonly involve interactions, control, and navigation processes. This study confirms the low quality of being immersive for audio guides in navigating the exhibition and involving experience in the virtual environment, which are the most vital features of new interactive technologies such as AR and VR. In addition, our usability surveys and heuristic evaluations disclosed many usability issues of these interactive technologies relating to interaction functions. Additionally, we use the Wayback Machine to examine what interactive apps/technologies were deployed on these websites during the physical visits limited due to the COVID-19 pandemic lockdown. Based on those inputs, we propose the reflection framework to enhance the UX in the cultural heritage domain with detailed guidelines.

Keywords: framework, user experience, cultural heritage, interactive technology, museum, COVID-19 pandemic, usability survey, heuristic evaluation, guidelines

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Authors: Harsh Sadawarti, Kamal Malik

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Humans are the unique and the most powerful creature on this planet just because of the high level of intelligence gifted by nature. Computational Intelligence is highly influenced by the term natural intelligence, neurosciences and mathematics. To deal with the in-depth study of computational intelligence and to utilize it in real-life applications, it is quite important to understand its simulation with the human brain. In this paper, the three important parts, Frontal Lobe, Occipital Lobe and Parietal Lobe of the human brain, are compared with the ANN(Artificial Neural Network), CNN(Convolutional Neural network), and RNN(Recurrent Neural Network), respectively. Intelligent computational systems are created by combining deductive reasoning, logical concepts and high-level algorithms with the simulation and study of the human brain. Human brain is a combination of Physiology, Psychology, emotions, calculations and many other parameters which are of utmost importance that determines the overall intelligence. To create intelligent algorithms, smart machines and to simulate the human brain in an effective manner, it is quite important to have an insight into the human brain and the basic concepts of biological neurosciences.

Keywords: computational intelligence, neurosciences, convolutional neural network, recurrent neural network, artificial neural network, frontal lobe, occipital lobe, parietal lobe

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Authors: Vanja Misic, Mohamed El-Mogy, Yousef Haj-Ahmad

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Endonuclease G (EndoG) is a well conserved mitochondrio-nuclear nuclease with dual lethal and vital roles in the cell. The aim of our study was to examine whether EndoG exerts its nuclease activity on exogenous DNA substrates such as plasmid DNA (pDNA), considering their importance in gene therapy applications. The effects of EndoG knockdown on pDNA stability and levels of encoded reporter gene expression were evaluated in the cervical carcinoma HeLa cells. Transfection of pDNA vectors encoding short-hairpin RNAs (shRNAs) reduced levels of EndoG mRNA and nuclease activity in HeLa cells. In physiological circumstances, EndoG knockdown did not have an effect on the stability of pDNA or the levels of encoded transgene expression as measured over a four day time-course. However, when endogenous expression of EndoG was induced by an extrinsic stimulus, targeting of EndoG by shRNA improved the perceived stability and transgene expression of pDNA vectors. Therefore, EndoG is not a mediator of exogenous DNA clearance, but in non-physiological circumstances it may non-specifically cleave intracellular DNA regardless of its origin. These findings make it unlikely that targeting of EndoG is a viable strategy for improving the duration and level of transgene expression from non-viral DNA vectors in gene therapy efforts.

Keywords: EndoG, silencing, exogenous DNA stability, HeLa cells

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Authors: Fatma El-Zahraa El-Taher, Ayman Taha, Jane Courtney, Susan Mckeever

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Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions, is critical to decisions such as crossing roads or selecting the safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer the state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset is examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of the detection of intersections in satellite images is evaluated.

Keywords: satellite images, remote sensing images, data acquisition, autonomous vehicles

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Authors: Dalal N. Hammod, Ekhlas K. Gbashi

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Today, cryptography is used in many applications to achieve high security in data transmission and in real-time communications. AES has long gained global acceptance and is used for securing sensitive data in various industries but has suffered from slow processing and take a large time to transfer data. This paper suggests a method to enhance Advance Encryption Standard (AES) Algorithm based on time and permutation. The suggested method (MAES) is based on modifying the SubByte and ShiftRrows in the encryption part and modification the InvSubByte and InvShiftRows in the decryption part. After the implementation of the proposal and testing the results, the Modified AES achieved good results in accomplishing the communication with high performance criteria in terms of randomness, encryption time, storage space, and avalanche effects. The proposed method has good randomness to ciphertext because this method passed NIST statistical tests against attacks; also, (MAES) reduced the encryption time by (10 %) than the time of the original AES; therefore, the modified AES is faster than the original AES. Also, the proposed method showed good results in memory utilization where the value is (54.36) for the MAES, but the value for the original AES is (66.23). Also, the avalanche effects used for calculating diffusion property are (52.08%) for the modified AES and (51.82%) percentage for the original AES.

Keywords: modified AES, randomness test, encryption time, avalanche effects

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Authors: Jamshaid Ul Rahman, Faiza Makhdoom, Dianchen Lu

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Activation functions play a decisive role in determining the capacity of Deep Neural Networks (DNNs) as they enable neural networks to capture inherent nonlinearities present in data fed to them. The prior research on activation functions primarily focused on the utility of monotonic or non-oscillatory functions, until Growing Cosine Unit (GCU) broke the taboo for a number of applications. In this paper, a Convolutional Neural Network (CNN) model named as ASU-CNN is proposed which utilizes recently designed activation function ASU across its layers. The effect of this non-monotonic and oscillatory function is inspected through feature map visualizations from different convolutional layers. The optimization of proposed network is offered by Adam with a fine-tuned adjustment of learning rate. The network achieved promising results on both training and testing data for the classification of CIFAR-10. The experimental results affirm the computational feasibility and efficacy of the proposed model for performing tasks related to the field of computer vision.

Keywords: amplifying sine unit, activation function, convolutional neural networks, oscillatory activation, image classification, CIFAR-10

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Authors: Harshan Baskar, Anirudh S. Chakravarthy, Prateek Garg, Divyam Goel, Abhijith S. Raj, Kshitij Kumar, Lakshya, Ravichandra Parvatham, V. Sushant, Bijay Kumar Rout

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In this paper, we introduce a new computer vision task called nighttime dehaze-enhancement. This task aims to jointly perform dehazing and lightness enhancement. Our task fundamentally differs from nighttime dehazing – our goal is to jointly dehaze and enhance scenes, while nighttime dehazing aims to dehaze scenes under a nighttime setting. In order to facilitate further research on this task, we release a new benchmark dataset called Reside-β Night dataset, consisting of 4122 nighttime hazed images from 2061 scenes and 2061 ground truth images. Moreover, we also propose a new network called NDENet (Nighttime Dehaze-Enhancement Network), which jointly performs dehazing and low-light enhancement in an end-to-end manner. We evaluate our method on the proposed benchmark and achieve SSIM of 0.8962 and PSNR of 26.25. We also compare our network with other baseline networks on our benchmark to demonstrate the effectiveness of our approach. We believe that nighttime dehaze-enhancement is an essential task, particularly for autonomous navigation applications, and we hope that our work will open up new frontiers in research. Our dataset and code will be made publicly available upon acceptance of our paper.

Keywords: dehazing, image enhancement, nighttime, computer vision

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Authors: Han Longxiang

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In the process of treating industrial oil wastewater with complex components, the traditional treatment methods (flotation, coagulation, microwave heating, etc.) often produce high operating costs, secondary pollution, and other problems. In order to solve these problems, the materials with high flux and stability applied to surfactant-stabilized emulsions separation have gained huge attention in the treatment of oily wastewater. Nevertheless, four stable oil-in-water emulsions can be formed due to different surfactants (surfactant-free, anionic surfactant, cationic surfactant, and non-ionic surfactant), and the previous advanced materials can only separate one or several of them, cannot effectively separate in one step. Herein, a facile synthesis method of graphene-based multilevel filter materials (GMFM) can efficiently separate the oil-in-water emulsions stabilized with different surfactants only through its gravity. The prepared materials with high stability of 20 cycles show a high flux of ~ 5000 L m-2 h-1 with a high separation efficiency of > 99.9 %. GMFM can effectively separate the emulsion stabilized by mixed surfactants and oily wastewater from factories. The results indicate that the GMFM has a wide range of applications in oil-in-water emulsions separation in industry and environmental science.

Keywords: emulsion, filtration, graphene, one-step

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Authors: Francisco J. Arias

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Consideration is given to a mechanism of heat and mass transport in solutions similar than that of natural convection but with one important difference. Here the mechanism is not promoted by density differences in the fluid occurring due to temperature gradients (coefficient of thermal expansion) but rather by solubility differences due to the thermal dependence of the solubility (coefficient of thermal solubility). Utilizing a simplified physical model, it is shown that by the proper choice of the concentration of a given solution, convection might be induced by the alternating precipitation of the solute -when the solution becomes supersaturated, and its posterior recombination when changes in temperature occurs. The spontaneous change in the Gibbs free energy during the mixing is the driven force for the mechanism. The maximum extractable energy from this new type of thermal convection was derived. Experimental data from a closed-loop circuit was obtained demonstrating the feasibility for continuous separation and recombination of the solution. This type of heat and mass transport -which doesn’t depend on gravity, might potentially be interesting for heat and mass transport downwards (as in solar-roof collectors to inside homes), horizontal (e.g., microelectronic applications), and in microgravity (space technology). Also, because the coefficient of thermal solubility could be positive or negative, the investigated thermo-osmosis convection can be used either for heating or cooling.

Keywords: natural convection, thermal gradient, solubility, osmotic pressure

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Authors: My Ali El Khakani

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Single-wall Carbon nanotubes (SWCNTs) possess an unprecedented combination of unique properties that make them highly promising for suitable for a new generation of photovoltaic (PV) devices. Prior to discussing the integration of SWCNTs films into effective PV devices, we will briefly highlight our work on the synthesis of SWCNTs by means of the KrF pulsed laser deposition technique, their purification and transfer onto n-silicon substrates to form p-n junctions. Some of the structural and optoelectronic properties of SWCNTs relevant to PV applications will be emphasized. By varying the SWCNTs film density (µg/cm2), we were able to point out the existence of an optimum value that yields the highest photoconversion efficiency (PCE) of ~10%. Further control of the doping of the p-SWCNTs films, through their exposure to nitric acid vapors, along with the insertion of an optimized hole-extraction-layer in the p-SWCNTs/n-Si hybrid devices permitted to achieve a PCE value as high as 14.2%. Such a high PCE value demonstrates the full potential of these p-SWCNTs/n-Si devices for sunlight photoconversion. On the other hand, by examining both the optical transmission and electrical conductance of the SWCNTs’ films, we established a figure of merit (FOM) that was shown to correlate well with the PCE performance. Such a direct relationship between the FOM and the PCE can be used as a guide for further PCE enhancement of these novel p-SWCNTs/n-Si PV devices.

Keywords: carbon nanotubes (CNTs), CNTs-silicon hybrid devices, photoconversion, photovoltaic devices, pulsed laser deposition

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Authors: Chul-Hee Jo, Do-Youb Kim, Seok-Jin Cho, Yu-Ho Rho

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The Catenary Anchor Leg Mooring (CALM) Single Point Mooring (SPM) buoy system is the most popular and widely used type of offshore loading terminals. SPM buoy mooring systems have been deployed worldwide for a variety of applications, water depths and vessel sizes ranging from small production carriers to Very Large Crude Carriers (VLCCs). Because of safe and easy berthing and un-berthing operations, the SPM buoy mooring system is also preferred for offshore terminals. The SPM buoy consists of a buoy that is permanently moored to the seabed by means of multiple mooring lines. The buoy contains a bearing system that allows a part of it to rotate around the moored geostatic part. When moored to the rotating part of the buoy, a vessel is able to freely weathervane around the buoy. This study was verified the effects of design variables in order to design an SPM buoy mooring system through parametric analysis. The design variables have independent and nonlinear characteristics. Using parametric analysis, this research was found that the fairlead departure angle, wave height and period, chain diameter and line length effect to the mooring top tension, buoy excursion and line layback.

Keywords: Single Point Mooring (SPM), Catenary Anchor Leg Mooring(CALM), design variables, parametric analysis, mooring system optimization

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Authors: Sophio Kobauri, Temur Kantaria, Nina Kulikova, David Tugushi, Ramaz Katsarava

Abstract:

Polymeric nanoparticles-based drug delivery systems and therapeutics have a great potential in the treatment of a numerous diseases, due to they are characterizing the flexible properties which is giving possibility to modify their structures with a complex definition over their structures, compositions and properties. Important characteristics of the polymeric nanoparticles (PNPs) used as drug carriers are high particle’s stability, high carrier capacity, feasibility of encapsulation of both hydrophilic and hydrophobic drugs, and feasibility of variable routes of administration, including oral application and inhalation; NPs are especially effective for intracellular drug delivery since they penetrate into the cells’ interior though endocytosis. A variety of PNPs based drug delivery systems including charged and neutral, degradable and non-degradable polymers of both natural and synthetic origin have been developed. Among these huge varieties the biodegradable PNPs which can be cleared from the body after the fulfillment of their function could be considered as one of the most promising. For intracellular uptake it is highly desirable to have positively charged PNPs since they can penetrate deep into cell membranes. For long-lasting circulation of PNPs in the body it is important they have so called “stealth coatings” to protect them from the attack of immune system of the organism. One of the effective ways to render the PNPs “invisible” for immune system is their PEGylation which represent the process of pretreatment of polyethylene glycol (PEG) on the surface of PNPs. The present work deals with constructing PNPs from amino acid based biodegradable polymers – regular poly(ester amide) (PEA) composed of sebacic acid, leucine and 1,6-hexandiol (labeled as 8L6), cationic PEA composed of sebacic acid, arginine and 1,6-hexandiol (labeled as 8R6), and comb-like co-PEA composed of sebacic acid, malic acid, leucine and 1,6-hexandiol (labeled as PEG-PEA). The PNPs were fabricated using the polymer deposition/solvent displacement (nanoprecipitation) method. The regular PEA 8L6 form stable negatively charged (zeta-potential within 2-12 mV) PNPs of desired size (within 150-200 nm) in the presence of various surfactants (Tween 20, Tween 80, Brij 010, etc.). Blending the PEAs 8L6 and 8R6 gave the 130-140 nm sized positively charged PNPs having zeta-potential within +20 ÷ +28 mV depending 8L6/8R6 ratio. The PEGylating PEA PEG-PEA was synthesized by interaction of epoxy-co-PEA [8L6]0,5-[tES-L6]0,5 with mPEG-amine-2000 The stable and positively charged PNPs were fabricated using pure PEG-PEA as a surfactant. A firm anchoring of the PEG-PEA with 8L6/8R6 based PNPs (owing to a high afinity of the backbones of all three PEAs) provided good stabilization of the NPs. In vitro biocompatibility study of the new PNPs with four different stable cell lines: A549 (human), U-937 (human), RAW264.7 (murine), Hepa 1-6 (murine) showed they are biocompatible. Considering high stability and cell compatibility of the elaborated PNPs one can conclude that they are promising for subsequent therapeutic applications. This work was supported by the joint grant from the Science and Technology Center in Ukraine and Shota Rustaveli National Science Foundation of Georgia #6298 “New biodegradable cationic polymers composed of arginine and spermine-versatile biomaterials for various biomedical applications”.

Keywords: biodegradable poly(ester amide)s, cationic poly(ester amide), pegylating poly(ester amide), nanoparticles

Procedia PDF Downloads 121

Authors: Armin Amindari

Abstract:

Hermetic compressors are used widely for refrigeration, heat pump, and air conditioning applications. With the improvement of energy conservation and environmental protection requirements, inverter compressors that operates at different speeds have become increasingly attractive in the industry. Although speed change capability is more efficient, passing through resonant frequencies may lead to excessive vibrations. In this work, an integrated vibration control approach based on flexible multi-body dynamics theory is used for optimizing the vibration amplitudes of the compressor at different operating speeds. To examine the compressor vibrations, all the forces and moments exerted on the cylinder block were clarified and minimized using balancers attached to the upper and lower ends of the motor rotor and crankshaft. The vibration response of the system was simulated using Motionview™ software. In addition, mass-spring optimization was adopted to shift the resonant frequencies out of the operating speeds. The modal shapes of the system were studied using Optistruct™ solver. Using this approach, the vibrations were reduced up to 56% through dynamic simulations. The results were in high agreement with various experimental test data. In addition, the vibration resonance problem observed at low speeds was solved by shifting the resonant frequencies through optimization studies.

Keywords: vibration, MBD, compressor, hermetic

Procedia PDF Downloads 100

Authors: Long Pham, Julia Blanke

Abstract:

An increasingly popular way of establishing citizen engagement within communities is through ‘city apps’. Currently, most of these mobile applications seem to be extensions of the existing communication media, sometimes merely replicating the information available on the classical city web sites, and therefore provide minimal additional impact on citizen behavior and engagement. In order to overcome this challenge, we propose to use a holistic behavioral model to generate dynamic and contextualized app content based on optimizing well defined city-related performance goals constrained by the proposed behavioral model. In this paper, we will show how the data collected by the CorkCitiEngage project in the Irish city of Cork can be utilized to calibrate aspects of the proposed model enabling the design of a personalized citizen engagement app aiming at positively influencing people’s behavior towards more active participation in their communities. We will focus on the important aspect of intentions to act, which is essential for understanding the reasons behind the common value-action-gap being responsible for the mismatch between good intentions and actual observable behavior, and will discuss how customized app design can be based on a rigorous model of behavior optimized towards maximizing well defined city-related performance goals.

Keywords: city apps, holistic behaviour model, intention to act, value-action-gap, citizen engagement

Procedia PDF Downloads 226

Authors: Abhilasha Mishra, Neha Bhatt

Abstract:

Super-hydrophobicity is an effect in which a surface roughness and chemical composition are combined to produce unusual water and dust repellent surface. The super-hydrophobic surface is widely used in many applications such as windshields of the automobile, aircraft, lens, solar cells, roofing, boat hull, paints, etc. Four coating solutions were prepared by varying compositions of 1,1,1,3,3,3 hexametyldisilazane (HDMS) and tetraethylorthosilicate (TEOS) sol. These solutions were coated on glass slides by a spin coating method and etched at a high temperature ranging 250 -350 oC. All the coatings were studied for its different properties like water repellent, anti-dust, and transparency and contact angle measurements. Stability of coatings was also studied with respect to temperature, external environment, and pH. It was found that all coatings impart a significant super-hydrophobicity on a glass surface with contact angle ranging from 156o to 162o and have good stability in the external environment. The results of the different coatings were observed and compared with each other. On increasing layers of coatings the super-hydrophobicity and anti-dust properties increases but after 3 coatings the transparency of coating starts decreasing.

Keywords: super-hydrophobic, contact angle, coating, anti-dust

Procedia PDF Downloads 259