Search results for: gaze tracking

Authors: Claire Biasco, Thaier Hayajneh

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A smart city is the integration of digital technologies in urban environments to enhance the quality of life. Smart cities capture real-time information from devices, sensors, and network data to analyze and improve city functions such as traffic analysis, public safety, and environmental impacts. Current smart cities face controversy due to their reliance on real-time data tracking and surveillance. Internet of Things (IoT) devices and blockchain technology are converging to reshape smart city infrastructure away from its centralized model. Connecting IoT data to blockchain applications would create a peer-to-peer, decentralized model. Furthermore, blockchain technology powers the ability for IoT device data to shift from the ownership and control of centralized entities to individuals or communities with Decentralized Autonomous Organizations (DAOs). In the context of smart cities, DAOs can govern cyber-physical systems to have a greater influence over how urban services are being provided. This paper will explore how the core components of a smart city now apply to DAOs. We will also analyze different definitions of DAOs to determine their most important aspects in relation to smart cities. Both categorizations will provide a solid foundation to conduct a cybersecurity assessment of DAOs in smart cities. It will identify the benefits and risks of adopting DAOs as they currently operate. The paper will then provide several mitigation methods to combat cybersecurity risks of DAO integrations. Finally, we will give several insights into what challenges will be faced by DAO and blockchain spaces in the coming years before achieving a higher level of maturity.

Keywords: blockchain, IoT, smart city, DAO

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Authors: Mohsin Raza, Rizwan Latif, Syed Adnan Qasim, Imran Shafi

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High torque low-speed diesel engine has a wide range of industrial and commercial applications. In literature, it’s found that lot of work has been done for the high-speed diesel engine and research on High Torque low-speed is rare. The fuel injection plays a key role in the efficiency of engine and reduction in exhaust emission. The fuel breakup plays a critical role in air-fuel mixture and spray combustion. The current study explains numerically an important phenomenon in spray combustion which is deformation and breakup of liquid drops in compression ignition internal combustion engine. The secondary breakup and its influence on spray and characteristics of compressed gas in-cylinder have been calculated by using simulation software in the backdrop of high torque low-speed diesel like conditions. The secondary spray breakup is modeled with KH - RT instabilities. The continuous field is described by turbulence model and dynamics of the dispersed droplet is modeled by Lagrangian tracking scheme. The results by using KH - RT model are compared against other default methods in OpenFOAM and published experimental data from research and implemented in CFD (Computational Fluid Dynamics). These numerical simulation, done in OpenFoam and Matlab, results are analyzed for the complete 720- degree 4 stroke engine cycle at a low engine speed, for favorable agreement to be achieved. Results thus obtained will be analyzed for better evaporation in near nozzle region. The proposed analyses will further help in better engine efficiency, low emission and improved fuel economy.

Keywords: diesel fuel, KH-RT, Lagrangian , Open FOAM, secondary breakup

Procedia PDF Downloads 223

Authors: Kyung-Tae Lee, Li Li Wang, Kwang-Woo Jung, Yong-Sun Bahn

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Microtubules are involved in mechanical support, cytoplasmic organization as well as in a number of cellular processes by interacting with diverse microtubule-associated proteins (MAPs), such as plus-end tracking proteins, motor proteins, and tubulin-folding cofactors. A common feature of these proteins is the presence of a cytoskeleton-associated protein-glycine-rich (CAP-Gly) domain, which is evolutionarily conserved and generally considered to bind to α-tubulin to regulate functions of microtubules. However, there has been a dearth of research on CAP-Gly proteins in fungal pathogens, including Cryptococcus neoformans, which causes fatal meningoencephalitis globally. In this study, we identified five CAP-Gly proteins encoding genes in C. neoformans. Among these, Cgp1, encoded by CNAG_06352, has a unique domain structure that has not been reported before in other eukaryotes. Supporting the role of Cpg1 in microtubule-related functions, we demonstrate that deletion or overexpression of CGP1 alters cellular susceptibility to thiabendazole, a microtubule destabilizer, and Cgp1 is co-localized with cytoplasmic microtubules. Related to the cellular functions of microtubules, Cgp1 also governs maintenance of membrane stability and genotoxic stress responses. Furthermore, we demonstrate that Cgp1 uniquely regulates sexual differentiation of C. neoformans with distinct roles in the early and late stage of mating. Our domain analysis reveals that the CAP-Gly domain plays major roles in all the functions of Cgp1. Finally, the cgp1Δ mutant is attenuated in virulence. In conclusion, this novel CAP-Gly protein, Cgp1, has pleotropic roles in regulating growth, stress responses, differentiation and pathogenicity of C. neoformans.

Keywords: human fungal pathogen, CAP-Glycine protein, microtubule, meningoencephalitis

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Authors: Michael Karnes, Alper Yilmaz

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This paper presents the application of the omni-modeler towards pedestrian redetection. The pedestrian redetection task creates several challenges when applying deep neural networks (DNN) due to the variety of pedestrian appearance with camera position, the variety of environmental conditions, and the specificity required to recognize one pedestrian from another. DNNs require significant training sets and are not easily adapted for changes in class appearances or changes in the set of classes held in its knowledge domain. Pedestrian redetection requires an algorithm that can actively manage its knowledge domain as individuals move in and out of the scene, as well as learn individual appearances from a few frames of a video. The Omni-Modeler is a dynamically learning few-shot visual recognition algorithm developed for tasks with limited training data availability. The Omni-Modeler adapts the knowledge domain of pre-trained deep neural networks to novel concepts with a calculated localized language encoder. The Omni-Modeler knowledge domain is generated by creating a dynamic dictionary of concept definitions, which are directly updatable as new information becomes available. Query images are identified through nearest neighbor comparison to the learned object definitions. The study presented in this paper evaluates its performance in re-identifying individuals as they move through a scene in both single-camera and multi-camera tracking applications. The results demonstrate that the Omni-Modeler shows potential for across-camera view pedestrian redetection and is highly effective for single-camera redetection with a 93% accuracy across 30 individuals using 64 example images for each individual.

Keywords: dynamic learning, few-shot learning, pedestrian redetection, visual recognition

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Authors: Teng lin, Li Yuxing, Han Hui, Zhao Pengfei, Zhang Datong

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With the development of carbon capture and storage (CCS), the flow assurance of CO2 transportation becomes more important, particularly for supercritical CO2 pipelines. The relieving system using the choke valve is applied to control the pressure in CO2 pipeline. However, the temperature of fluid would drop rapidly because of Joule-Thomson cooling (JTC), which may cause solid CO2 form and block the pipe. In this paper, a Computational Fluid Dynamic (CFD) model, using the modified Lagrangian method, Reynold's Stress Transport model (RSM) for turbulence and stochastic tracking model (STM) for particle trajectory, was developed to predict the deposition characteristic of solid carbon dioxide. The model predictions were in good agreement with the experiment data published in the literature. It can be observed that the particle distribution affected the deposition behavior. In the region of the sudden expansion, the smaller particles accumulated tightly on the wall were dominant for pipe blockage. On the contrary, the size of solid CO2 particles deposited near the outlet usually was bigger and the stacked structure was looser. According to the calculation results, the movement of the particles can be regarded as the main four types: turbulent motion close to the sudden expansion structure, balanced motion at sudden expansion-middle region, inertial motion near the outlet and the escape. Furthermore the particle deposits accumulated primarily in the sudden expansion region, reattachment region and outlet region because of the four type of motion. Also the Stokes number had an effect on the deposition ratio and it is recommended for Stokes number to avoid 3-8St.

Keywords: carbon capture and storage, carbon dioxide pipeline, gas-particle flow, deposition

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Authors: Dachuan Shi, M. Hecht, Y. Ye

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With the trend of digitalization in railway freight transport, a large number of freight wagons in Germany have been equipped with telematics devices, commonly placed on the wagon body. A telematics device contains a GPS module for tracking and a 3-axis accelerometer for shock detection. Besides these basic functions, it is desired to use the integrated accelerometer for condition monitoring without any additional sensors. Wheel flats as a common type of failure on wheel tread cause large impacts on wagons and infrastructure as well as impulsive noise. A large wheel flat may even cause safety issues such as derailments. In this sense, this paper proposes a machine learning approach for wheel flat detection by using car body accelerations. Due to suspension systems, impulsive signals caused by wheel flats are damped significantly and thus could be buried in signal noise and disturbances. Therefore, it is very challenging to detect wheel flats using car body accelerations. The proposed algorithm considers the envelope spectrum of car body accelerations to eliminate the effect of noise and disturbances. Subsequently, a 1-D convolutional neural network (CNN), which is well known as a deep learning method, is constructed to automatically extract features in the envelope-frequency domain and conduct classification. The constructed CNN is trained and tested on field test data, which are measured on the underframe of a tank wagon with a wheel flat of 20 mm length in the operational condition. The test results demonstrate the good performance of the proposed algorithm for real-time fault detection.

Keywords: fault detection, wheel flat, convolutional neural network, machine learning

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Authors: Rihab Hamdi, Amel Hadri Hamida, Fatiha Khelili, Sakina Zerouali, Ouafae Bennis

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This paper features a comparative study performance of sliding mode controller (SMC) for closed-loop voltage control of direct current to direct current (DC-DC) three-cells buck converter connected in parallel, operating in continuous conduction mode (CCM), based on pulse-width modulation (PWM) with SMC based on hysteresis modulation (HM) where an adaptive feedforward technique is adopted. On one hand, for the PWM-based SM, the approach is to incorporate a fixed-frequency PWM scheme which is effectively a variant of SM control. On the other hand, for the HM-based SM, oncoming an adaptive feedforward control that makes the hysteresis band variable in the hysteresis modulator of the SM controller in the aim to restrict the switching frequency variation in the case of any change of the line input voltage or output load variation are introduced. The results obtained under load change, input change and reference change clearly demonstrates a similar dynamic response of both proposed techniques, their effectiveness is fast and smooth tracking of the desired output voltage. The PWM-based SM technique has greatly improved the dynamic behavior with a bit advantageous compared to the HM-based SM technique, as well as provide stability in any operating conditions. Simulation studies in MATLAB/Simulink environment have been performed to verify the concept.

Keywords: DC-DC converter, hysteresis modulation, parallel multi-cells converter, pulse-width modulation, robustness, sliding mode control

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Authors: Syed Asif Hassan, Tabrej Khan, Ibrahim Manssor Al Najar, Mohammed Nasser

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The incredible accomplishment achieved by e-commerce in consumer durable area encouraged us to implement the online e-commerce model to tap the business benefits of electronic pharmacy in Saudi Arabia. The Kingdom of Saudi Arabia is famous for traditional herbal medicine. The rich heritage of traditional medicine has helped the mushrooming of regional pharmaceutical industries manufacturing drugs and other therapeutic against various diseases. However, the implementation of e-commerce in pharmacy has not been employed in the Kingdom of Saudi Arabia. The electronic pharmacy (E-Pharm) is an important sector that is flourishing across the globe and providing benefits of E-Pharm to the customers and suppliers all around the world. In this context, our web-based application of electronic pharmacy is the one of its kind in the Kingdom of Saudi Arabia. Surveys and personal interviews were used to identify key objectives of the proposed web-based portal. As per the findings of the surveys and personal interviews, following key objectives were identified: (a) The online platform will be used for ordering of prescription based medications for consumers. (b) The e-portal will provide space for pharmaceutical retailers who do not have an electronic platform to upload and sell their therapeutic products in an organized way. (c) The web portal will provide a tracking system to track the customer’s behavior like choice, offer, order, shipment, payment, etc. The web-based e-pharmacy portal will be developed using MySQL and PHP. The development of e-pharmacy web portal and e-prescription practices will not only improve the growth of electronic pharmacy but would also decrease the possibility of prescription alteration thus providing safety and improving the quality of service provided to the patient or consumers.

Keywords: e-commerce, E-Pharm, MySQL, PHP

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Authors: Gwi Hyun Lee, Mun Soo Na

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Solar energy has many advantages of infinite and clean source, and also it can be used for reduction of greenhouse gases and environment pollution. Concentrated solar system is a very useful to achieve reasonably high thermal efficiency. Different types of solar concentrating systems have been developed such as parabolic trough and parabolic dish. Conical solar concentrator is one of the most reliable and promising renewable energy systems for higher temperature applications. The objectives of this study were to investigate the influence of flow rate affecting the thermal efficiency of a conical solar collector, which has a double tube absorber placed at focal axis for collecting solar radiation. A conical solar concentrator consists of a conical reflector, which reflects direct solar radiation into an absorber. A double tube absorber was placed at the center of focal axis for collecting the solar radiation reflected from a conical reflector. A dual tracking system consists of a linear actuator and slew drive with driving cycle of 6 seconds. Water was used as circulating fluid, which flows from inlet to outlet of an absorber for collecting solar radiation. Three identical conical solar concentrator systems were installed side by side at the same place for the accurate performance analysis under the same environmental conditions. Performance evaluations were carried out with different volumetric flow rate of 2, 4 and 6 L/min to find the influence of flow rate affecting on thermal efficiency. The results indicated that average thermal efficiency was 73.24%, 81.96%, and 79.78% for each flow rate of 2 L/min, 4 L/min, and 6 L/min. It shows that the flow rate of circulating water has a significant effect on the thermal efficiency of the conical solar concentrator. It is concluded that an optimum flow rate of conical solar concentrator is 6 L/min.

Keywords: conical solar concentrator, performance evaluation, solar energy, solar energy system

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Authors: H. Heidari-Bafroui, B. Ribeiro, A. Charbaji, C. Anagnostopoulos, M. Faghri

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In this paper, we report the development of a portable and inexpensive infrared lightbox for improving the detection limits of paper-based phosphate devices. Commercial paper-based devices utilize the molybdenum blue protocol to detect phosphate in the environment. Although these devices are easy to use and have a long shelf life, their main deficiency is their low sensitivity based on the qualitative results obtained via a color chart. To improve the results, we constructed a compact infrared lightbox that communicates wirelessly with a smartphone. The system measures the absorbance of radiation for the molybdenum blue reaction in the infrared region of the spectrum. It consists of a lightbox illuminated by four infrared light-emitting diodes, an infrared digital camera, a Raspberry Pi microcontroller, a mini-router, and an iPhone to control the microcontroller. An iPhone application was also developed to analyze images captured by the infrared camera in order to quantify phosphate concentrations. Additionally, the app connects to an online data center to present a highly scalable worldwide system for tracking and analyzing field measurements. In this study, the detection limits for two popular commercial devices were improved by a factor of 4 for the Quantofix devices (from 1.3 ppm using visible light to 300 ppb using infrared illumination) and a factor of 6 for the Indigo units (from 9.2 ppm to 1.4 ppm) with repeatability of less than or equal to 1.2% relative standard deviation (RSD). The system also provides more granular concentration information compared to the discrete color chart used by commercial devices and it can be easily adapted for use in other applications.

Keywords: infrared lightbox, paper-based device, phosphate detection, smartphone colorimetric analyzer

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Authors: Jia Li, Huacong Li, Xiaobao Han

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Due to the more variable geometry parameters of VCE (variable cycle aircraft engine), presents an adaptive controller method based on the full-state linear model of VCE and has simulated to solve the multivariate controller design problem of the whole flight envelops. First, analyzes the static and dynamic performances of bypass ratio and other state parameters caused by variable geometric components, and develops nonlinear component model of VCE. Then based on the component model, through small deviation linearization of main fuel (Wf), the area of tail nozzle throat (A8) and the angle of rear bypass ejector (A163), setting up multiple linear model which variable geometric parameters can be inputs. Second, designs the adaptive controllers for VCE linear models of different nominal points. Among them, considering of modeling uncertainties and external disturbances, derives the adaptive law by lyapunov function. The simulation results showed that, the adaptive controller method based on full-state linear model used the angle of rear bypass ejector as input and effectively solved the multivariate control problems of VCE. The performance of all nominal points could track the desired closed-loop reference instructions. The adjust time was less than 1.2s, and the system overshoot was less than 1%, at the same time, the errors of steady states were less than 0.5% and the dynamic tracking errors were less than 1%. In addition, the designed controller could effectively suppress interference and reached the desired commands with different external random noise signals.

Keywords: variable cycle engine (VCE), full-state linear model, adaptive control, by-pass ratio

Procedia PDF Downloads 291

Authors: Li Yang

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Tourism is employed by many countries to facilitate socioeconomic development and to assist in the heritage preservation. An “ethnic culture boom” is currently driving the tourism industry in China. Ethnic minorities, commonly portrayed as primitive, colorful and exotic, have become a big tourist draw. Many cultural attractions have been built throughout China to meet the demands of domestic tourists. Sacred cultural heritage sites have been rehabilitated as a major component of ethnic tourism. The purpose of this study is to examine the interconnected consequences of tourism development and tourism-related leisure property development and, and to discuss, in a broader context, issues and considerations that are pertinent to the management and development of ethnic attractions. The role of real estate in tourism development and its sociocultural consequences are explored. An empirical research was conducted in Yiren Ancient Town (literally, "Ancient Town of Yi People") in Chuxiong City, Yunnan Province, China. Multiple research methods, including in-depth interviews, informal discussions, on-site observations, and secondary data review were employed to measure residents and tourism decision-makers’ perceptions of ethnic tourism and to explore the impacts of tourism on local community. Key informants from government officials, tourism developers and local communities were interviewed individually to gather what they think about benefits and costs of tourism, and what their concerns about and hopes for tourism development are. Yiren Ancient Town was constructed in classical Yi architecture style featuring tranquil garden scenery. Commercial streets, entertainment complexes, and accommodation facilities occupied the center of the town, creating culturally distinctive and visually stimulating places for tourists. A variety of activities are presented to visitors, including walking tours of the town, staged dance shows, musical performances, ethnic festivals and ceremonies, tasting minority food and wedding shows. This study reveals that tourism real estate has transformed the town from a traditional neighborhood into diverse real estate landscapes. Ethnic architecture, costumes, festivals and folk culture have been represented, altered and reinvented through the tourist gaze and mechanisms of cultural production. Tourism is now a new economic driver of the community providing opportunities for the creation of small businesses. There was a general appreciation in the community that tourism has created many employment opportunities, especially for self-employment. However, profit-seeking is a primary motivation for the government, developers, businesses, and other actors involved in the tourism development process. As the town has attracted an increasing number of visitors, commercialization and business competition are intense in the town. Many residents complained about elevated land prices, making the town and the surroundings comparatively high-value locales. Local community is also concerned about the decline of traditional ethnic culture and an erosion of the sense of identity and place. A balance is difficult to maintain between protection and development. The preservation of ethnic culture and heritage should be enhanced if long-term sustainable development of tourism is to occur and the loss of ethnic identities is to be avoided.

Keywords: ancient town, ethnic tourism, local community, real estate, China

Procedia PDF Downloads 256

Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, G. Corkery, E. Broderick, J. Walsh

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Farm management and operations will drastically change due to access to real-time data, real-time forecasting, and tracking of physical items in combination with Internet of Things developments to further automate farm operations. Dairy farms have embraced technological innovations and procured vast amounts of permanent data streams during the past decade; however, the integration of this information to improve the whole farm-based management and decision-making does not exist. It is now imperative to develop a system that can collect, integrate, manage, and analyse on-farm and off-farm data in real-time for practical and relevant environmental and economic actions. The developed systems, based on machine learning and artificial intelligence, need to be connected for useful output, a better understanding of the whole farming issue, and environmental impact. Evolutionary computing can be very effective in finding the optimal combination of sets of some objects and, finally, in strategy determination. The system of the future should be able to manage the dairy farm as well as an experienced dairy farm manager with a team of the best agricultural advisors. All these changes should bring resilience and sustainability to dairy farming as well as improving and maintaining good animal welfare and the quality of dairy products. This review aims to provide an insight into the state-of-the-art of big data applications and evolutionary computing in relation to smart dairy farming and identify the most important research and development challenges to be addressed in the future. Smart dairy farming influences every area of management, and its uptake has become a continuing trend.

Keywords: big data, evolutionary computing, cloud, precision technologies

Procedia PDF Downloads 161

Authors: Oliver Ohneiser, Francesca De Crescenzio, Gianluca Di Flumeri, Jan Kraemer, Bruno Berberian, Sara Bagassi, Nicolina Sciaraffa, Pietro Aricò, Gianluca Borghini, Fabio Babiloni

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An increasing degree of automation in air traffic will also change the role of the air traffic controller (ATCO). ATCOs will fulfill significantly more monitoring tasks compared to today. However, this rather passive role may lead to Out-Of-The-Loop (OOTL) effects comprising vigilance decrement and less situation awareness. The project MINIMA (Mitigating Negative Impacts of Monitoring high levels of Automation) has conceived a system to control and mitigate such OOTL phenomena. In order to demonstrate the MINIMA concept, an experimental simulation set-up has been designed. This set-up consists of two parts: 1) a Task Environment (TE) comprising a Terminal Maneuvering Area (TMA) simulator as well as 2) a Vigilance and Attention Controller (VAC) based on neurophysiological data recording such as electroencephalography (EEG) and eye-tracking devices. The current vigilance level and the attention focus of the controller are measured during the ATCO’s active work in front of the human machine interface (HMI). The derived vigilance level and attention trigger adaptive automation functionalities in the TE to avoid OOTL effects. This paper describes the full-scale experimental set-up and the component development work towards it. Hence, it encompasses a pre-test whose results influenced the development of the VAC as well as the functionalities of the final TE and the two VAC’s sub-components.

Keywords: automation, human factors, air traffic controller, MINIMA, OOTL (Out-Of-The-Loop), EEG (Electroencephalography), HMI (Human Machine Interface)

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Authors: Baha-Aldeen S. Algmati, Ahmed R. Ballil

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Multiphase flows occur widely in many engineering and industrial processes as well as in the environment we live in. In particular, bubbly flows are considered to be crucial phenomena in fluid flow applications and can be studied and analyzed experimentally, analytically, and computationally. In the present paper, the dynamic motion of an air bubble rising within a column of liquid is numerically simulated using an open-source CFD modeling tool 'OpenFOAM'. An interface tracking numerical algorithm called MULES algorithm, which is built-in OpenFOAM, is chosen to solve an appropriate mathematical model based on the volume of fluid (VOF) numerical method. The bubbles initially have a spherical shape and starting from rest in the stagnant column of liquid. The algorithm is initially verified against numerical results and is also validated against available experimental data. The comparison revealed that this algorithm provides results that are in a very good agreement with the 2D numerical data of other CFD codes. Also, the results of the bubble shape and terminal velocity obtained from the 3D numerical simulation showed a very good qualitative and quantitative agreement with the experimental data. The simulated rising bubbles yield a very small percentage of error in the bubble terminal velocity compared with the experimental data. The obtained results prove the capability of OpenFOAM as a powerful tool to predict the behavior of rising characteristics of the spherical bubbles in the stagnant column of liquid. This will pave the way for a deeper understanding of the phenomenon of the rise of bubbles in liquids.

Keywords: CFD simulations, multiphase flows, OpenFOAM, rise of bubble, volume of fluid method, VOF

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Authors: Abhimanyu Thakur, Youngjin Lee

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Glioma is a lethal brain cancer whose early diagnosis and prognosis are limited due to the dearth of a suitable technique for its early detection. Current approaches, including magnetic resonance imaging (MRI), computed tomography (CT), and invasive biopsy for the diagnosis of this lethal disease, hold several limitations, demanding an alternative method. Recently, extracellular vesicles (EVs) have been used in numerous biomarker studies, majorly exosomes and microvesicles (MVs), which are found in most of the cells and biofluids, including blood, cerebrospinal fluid (CSF), and urine. Remarkably, glioma cells (GMs) release a high number of EVs, which are found to cross the blood-brain-barrier (BBB) and impersonate the constituents of parent GMs including protein, and lncRNA; however, biophysical properties of EVs have not been explored yet as a biomarker for glioma. We isolated EVs from cell culture conditioned medium of GMs and regular primary culture, blood, and urine of wild-type (WT)- and glioma mouse models, and characterized by nano tracking analyzer, transmission electron microscopy, immunogold-EM, and differential light scanning. Next, we measured the biophysical parameters of GMs-EVs by using atomic force microscopy. Further, the functional constituents of EVs were examined by FTIR and Raman spectroscopy. Exosomes and MVs-derived from GMs, blood, and urine showed distinction biophysical parameters (roughness, adhesion force, and stiffness) and different from that of regular primary glial cells, WT-blood, and -urine, which can be attributed to the characteristic functional constituents. Therefore, biophysical features can be potential diagnostic biomarkers for glioma.

Keywords: glioma, extracellular vesicles, exosomes, microvesicles, biophysical properties

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Authors: C. Chaillou

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The dominant theoretical approaches in Criminology are interested in the phenomenon of delinquency from the question of the management of the risks incurred by the population. Thus, this research advocate prevention of this phenomenon by a tracking of early disorders in children. Treatments offered to rely on medical research (genetics and biology are cited as a reference) and assuming a high naturalization of delinquent behaviour. Programs that are offered also reduce to a recovery of the deviant behaviour, and rely readily on behavioral guidelines, with an educational grant. Public policy then rely on these programs to prevent unwanted behaviour within a given population and to reduce the risk for the company. This is the case in France, with national institutes making (juvenile) violence a public health problem. We consider that other approaches, issues of sociology, are more relevant to the treatment of offenders. These approaches are moving, not on its prevention, but from its inputs and its outputs. Several modalities of entries and exits of delinquency can find and analyze in terms of process. We assume that there is a dynamic inherent in the individual and it is important to take into account the environment of the offender. These different types of processes can illuminate from the derived work of the Psychoanalytical psychopathology and lead to more effective treatment of delinquent acts. Psychoanalytic concepts have enabled us to offer a new look means to treat delinquency, placing several types of relationship with the other and relating to the clinical structure and the uniqueness of the case, we have been able to enter subjective and unconscious logics at work in delinquent acts. This research has facilitated the reduction of these types of subjective responses and proposed others, opening to a reintegration of offenders in a social link them being more favourable and in a longer term.

Keywords: delinquency, insertion, social link, unconscious

Procedia PDF Downloads 349

Authors: Chong Zhang

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There is widespread debate about the nationalistic top-down approach to citizenship education. Employing the notion of cultural citizenship as a useful theoretical lens, citizenship education research tends to focus on the process of subjectivity construction among students’ citizenship learning process. As the Communist Party of China (CPC) plays a dominant role in cultivating citizens through ideological and political education (IaPE) in Chinese universities, the research problem herein focuses on the dynamics and complexity of how Chinese university students construct their subjectivities regarding citizenship learning through IaPE, mediated by the interaction between the state and university teachers. Drawing on questionnaire data from 212 students and interview data from 25 students in one university in China, this paper examines the ways in which students understand and respond to dominant discourses. Its findings reveal there is a deficit of citizenship learning in IaPE, and that students feel ideologically pressurized. From its analysis of social contexts’ influence, the article suggests Chinese higher education students act as either mild changemakers or active self-motivators to enact complex subjectivities, in that they must involve themselves in IaPE for personal academic and career development, yet adopt covert strategies to realise their self-conscious citizenship learning expectations. These strategies take the form of passive and active freedoms, ranging from obediently completing basic curriculum requirements and distancing themselves by studying abroad, to actively searching for learning opportunities from other courses and social media. This paper contributes to the research on citizenship education by recognizing the complexities of how subjectivities are formed in formal university settings.

Keywords: university students, citizenship learning, cultural citizenship, subjectivity, Chinese higher education

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Authors: Saeed Vahedikamal, Ian Hepburn

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Microwave Kinetic Inductance Detectors (MKIDs) are considered as one of the most promising photon detectors of the future in many Astronomical applications such as exoplanet detections. The MKID advantages stem from their single photon sensitivity (ranging from UV to optical and near infrared), photon energy resolution and high temporal capability (~microseconds). There has been substantial progress in the development of these detectors and MKIDs with Megapixel arrays is now possible. The unique capability of recording an incident photon and its energy (or wavelength) while also registering its time of arrival to within a microsecond enables an array of MKIDs to produce a four-dimensional data block of x, y, z and t comprising x, y spatial, z axis per pixel spectral and t axis per pixel which is temporal. This offers the possibility that the spectrum and brightness variation for any detected piece of space debris as a function of time might offer a unique identifier or fingerprint. Such a fingerprint signal from any object identified in multiple detections by different observers has the potential to determine the orbital features of the object and be used for their tracking. Modelling performed so far shows that with a 20 cm telescope located at an Astronomical observatory (e.g. La Palma, Canary Islands) we could detect sub cm objects at GEO. By considering a Lambertian sphere with a 10 % reflectivity (albedo of the Moon) we anticipate the following for a GEO object: 10 cm object imaged in a 1 second image capture; 1.2 cm object for a 70 second image integration or 0.65 cm object for a 4 minute image integration. We present details of our modelling and the potential instrument for a dedicated GEO surveillance system.

Keywords: space debris, orbital debris, detection system, observation, microwave kinetic inductance detectors, MKID

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Authors: Hosam A. Shawky, Amr A. Abdel Fatah, Moustafa M. S. Abo ElFad, Abdel Hameed M. El-Aassar

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Water desalination projects based on reverse osmosis technology are being introduced in Egypt to combat drinking water shortage in remote areas. Reverse osmosis (RO) desalination is a pressure driven process. This paper focuses on the design of an integrated brackish water and seawater RO desalination and solar Photovoltaic (PV) technology. A small Mobile PV driven RO desalination plant prototype without batteries is designed and tested. Solar-driven reverse osmosis desalination can potentially break the dependence of conventional desalination on fossil fuels, reduce operational costs, and improve environmental sustainability. Moreover, the innovative features incorporated in the newly designed PV-RO plant prototype are focusing on improving the cost effectiveness of producing drinkable water in remote areas. This is achieved by maximizing energy yield through an integrated automatic single axis PV tracking system with programmed tilting angle adjustment. An autonomous cleaning system for PV modules is adopted for maximizing energy generation efficiency. RO plant components are selected so as to produce 4-5 m3/day of potable water. A basic criterion in the design of this PV-RO prototype is to produce a minimum amount of fresh water by running the plant during peak sun hours. Mobility of the system will provide potable water to isolated villages and population as well as ability to provide good drinking water to different number of people from any source that is not drinkable.

Keywords: design, reverse osmosis, photovoltaic, energy, desalination, Egypt

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Authors: Linnan Zhang

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Linguists, as well as psychologists, have shown great interests in implicit causality in reference processing. However, most frequently-used approaches to this issue are psychological experiments (such as eye tracking or self-paced reading, etc.). This research is a corpus-based one and is assisted with statistical tool – software R. The main focus of the present study is about the competition between verb-based implicit causality and theme structure’s influence on anaphora bias in Mandarin Chinese sentences. In Accessibility Theory, it is believed that salience, which is also known as accessibility, and relevance are two important factors in reference processing. Theme structure, which is a special syntactic structure in Chinese, determines the salience of an antecedent on the syntactic level while verb-based implicit causality is a key factor to the relevance between antecedent and anaphora. Therefore, it is a study about anaphora, combining psychology with linguistics. With analysis of the sentences from corpus as well as the statistical analysis of Multinomial Logistic Regression, major findings of the present study are as follows: 1. When the sentence is stated in a ‘cause-effect’ structure, the theme structure will always be the antecedent no matter forward biased verbs or backward biased verbs co-occur; in non-theme structure, the anaphora bias will tend to be the opposite of the verb bias; 2. When the sentence is stated in a ‘effect-cause’ structure, theme structure will not always be the antecedent and the influence of verb-based implicit causality will outweigh that of theme structure; moreover, the anaphora bias will be the same with the bias of verbs. All the results indicate that implicit causality functions conditionally and the noun in theme structure will not be the high-salience antecedent under any circumstances.

Keywords: accessibility theory, anaphora, theme strcture, verb-based implicit causality

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Authors: Thohaku Abdul Hadi, Hadyan Perdana Putra, Nugroho Wicaksono, Adhika Prajna Nandiwardhana, Onang Surya Nugroho, Heri Suryoatmojo, Soedibjo

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Access to electricity is now a basic requirement of mankind. Unfortunately, there are still many places around the world which have no access to electricity, such as small islands, where there could potentially be a factory, a plantation, a residential area, or resorts. Many of these places might have substantial potential for energy generation such us Photovoltaic (PV) and Wind turbine (WT), which can be used to generate electricity independently for themselves. Solar energy and wind power are renewable energy sources which are mostly found in nature and also kinds of alternative energy that are still developing in a rapid speed to help and meet the demand of electricity. PV and Wind has a characteristic of power depend on solar irradiation and wind speed based on geographical these areas. This paper presented a control methodology of hybrid small scale PV/Wind energy system that use a fuzzy logic controller (FLC) to extract the maximum power point tracking (MPPT) in different solar irradiation and wind speed. This paper discusses simulation and analysis of the generation process of hybrid resources in MPP and power conditioning unit (PCU) of Photovoltaic (PV) and Wind Turbine (WT) that is connected to the three-phase low voltage electricity grid system (380V) without battery storage. The capacity of the sources used is 2.2 kWp PV and 2.5 kW PMSG (Permanent Magnet Synchronous Generator) -WT power rating. The Modeling of hybrid PV/Wind, as well as integrated power electronics components in grid connected system, are simulated using MATLAB/Simulink.

Keywords: fuzzy MPPT, grid connected inverter, photovoltaic (PV), PMSG wind turbine

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Authors: Ilze Pelece, Imants Ziemelis, Henriks Putans

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Traditionally the solar energy has been used in southern countries, but it has been used also in northern ones. Most popular kind of use of solar energy in Latvia is solar collector for water heating. Traditionally flat-plate solar collectors are used because of simplicity of manufacturing. However, some peculiarities in use of solar energy in northern countries must be taken into account. In northern countries, there is lower irradiance, but longer day and longer path of the sun during summer. Therefore traditional flat-plate solar collectors are not appropriate enough in northern countries, but new forms must be developed. There are two forms of solar collectors - cylindrical and semi-spherical – proposed in this work. Such collectors can be made both for water or air heating. Theoretical calculations and measurements of energy gain from those two collectors have been done. Results show that daily energy sum received by the semi-spherical collector from the sun at the middle of summer is 1.43 times more than that of the flat one, but for the cylindrical collector, it is 1.74 times more than that of the flat one or equal to that of the tracking to sun flat-plate collector. The resulting difference in energy gain from collector will be not so large because of the difference in heat loses. Heat can be decreased by switching off the water circulation pump when the sun is covered by clouds. For this purpose solar batteries, powered pump can be used instead of complicated and expensive automatics. Even more important than overall energy gain is the fact that semi-spherical and cylindrical collectors work all day (17 hours in the middle of summer at 57 northern latitudes), while flat-plate collector only about 11 hours. Yearly energy sum received by the collector from the sun is 1.5 and 1.9 times larger for the semi-spherical and cylindrical collector respectively as for the flat one. The cylindrical solar collector is easier to manufacture, but semi-spherical one is more aesthetical and durable against the impact of the wind. Although solar collectors for water and air heating are studied in this article, main ideas are applicable also for solar batteries.

Keywords: cylindric, semi-spherical, solar collector, solar energy, water heating

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Authors: Alexandros Lioulemes, Michail Theofanidis, Varun Kanal, Konstantinos Tsiakas, Maher Abujelala, Chris Collander, William B. Townsend, Angie Boisselle, Fillia Makedon

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This paper presents a home-based robot-rehabilitation instrument, called ”MAGNI Dynamics”, that utilized a vision-based kinematic/dynamic module and an adaptive haptic feedback controller. The system is expected to provide personalized rehabilitation by adjusting its resistive and supportive behavior according to a fuzzy intelligence controller that acts as an inference system, which correlates the user’s performance to different stiffness factors. The vision module uses the Kinect’s skeletal tracking to monitor the user’s effort in an unobtrusive and safe way, by estimating the torque that affects the user’s arm. The system’s torque estimations are justified by capturing electromyographic data from primitive hand motions (Shoulder Abduction and Shoulder Forward Flexion). Moreover, we present and analyze how the Barrett WAM generates a force-field with a haptic controller to support or challenge the users. Experiments show that by shifting the proportional value, that corresponds to different stiffness factors of the haptic path, can potentially help the user to improve his/her motor skills. Finally, potential areas for future research are discussed, that address how a rehabilitation robotic framework may include multisensing data, to improve the user’s recovery process.

Keywords: human-robot interaction, kinect, kinematics, dynamics, haptic control, rehabilitation robotics, artificial intelligence

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Authors: Mansa Radhakrishnan, Anwar Ali, Muhammad Rizwan Mughal

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Many universities around the world are working on modular and low budget architecture of small spacecraft to reduce the development cost of the overall system. This paper focuses on the design of a modular solar power harvesting system for a hexagonal-shaped small satellite. The designed solar power harvesting systems are composed of solar panels and power converter subsystems. The solar panel is composed of solar cells mounted on the external face of the printed circuit board (PCB), while the electronic components of power conversion are mounted on the interior side of the same PCB. The solar panel with dimensions 16.5cm × 99cm is composed of 36 solar cells (each solar cell is 4cm × 7cm) divided into four parallel banks where each bank consists of 9 solar cells. The output voltage of a single solar cell is 2.14V, and the combined output voltage of 9 series connected solar cells is around 19.3V. The output voltage of the solar panel is boosted to the satellite power distribution bus voltage level (28V) by a boost converter working on a constant voltage maximum power point tracking (MPPT) technique. The solar panel module is an eight-layer PCB having embedded coil in 4 internal layers. This coil is used to control the attitude of the spacecraft, which consumes power to generate a magnetic field and rotate the spacecraft. As power converter and distribution subsystem components are mounted on the PCB internal layer, therefore it is mandatory to do thermal analysis in order to ensure that the overall module temperature is within thermal safety limits. The main focus of the overall design is on compactness, miniaturization, and efficiency enhancement.

Keywords: small satellites, power subsystem, efficiency, MPPT

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Authors: E. Rama Devi Jothilingam

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Diabetes mellitus is now one of the most common non communicable diseases globally. India leads the world with largest number of diabetic subjects earning the title "diabetes capital of the world". In order to reduce the mortality rate, a fuzzy expert system is designed to predict the severity of cardiac and renal problems of diabetic patients using fuzzy logic. Since uncertainty is inherent in medicine, fuzzy logic is used in this research work to remove the inherent fuzziness of linguistic concepts and uncertain status in diabetes mellitus which is the prime cause for the cardiac arrest and renal failure. In this work, the controllable risk factors "blood sugar, insulin, ketones, lipids, obesity, blood pressure and protein/creatinine ratio" are considered as input parameters and the "the stages of cardiac" (SOC)" and the stages of renal" (SORD) are considered as the output parameters. The triangular membership functions are used to model the input and output parameters. The rule base is constructed for the proposed expert system based on the knowledge from the medical experts. Mamdani inference engine is used to infer the information based on the rule base to take major decision in diagnosis. Mean of maximum is used to get a non fuzzy control action that best represent possibility distribution of an inferred fuzzy control action. The proposed system also classifies the patients with high risk and low risk using fuzzy c means clustering techniques so that the patients with high risk are treated immediately. The system is validated with Matlab and is used as a tracking system with accuracy and robustness.

Keywords: Diabetes mellitus, fuzzy expert system, Mamdani, MATLAB

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Authors: Teodora Vukovic, Christoph Hottiger, Noah Bubenhofer

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The development of VIAN-DH aims at bridging two linguistic approaches: conversation analysis/interactional linguistics (IL), so far a dominantly qualitative field, and computational/corpus linguistics and its quantitative and automated methods. Contemporary IL investigates the systematic organization of conversations and interactions composed of speech, gaze, gestures, and body positioning, among others. These highly integrated multimodal behaviour is analysed based on video data aimed at uncovering so called “multimodal gestalts”, patterns of linguistic and embodied conduct that reoccur in specific sequential positions employed for specific purposes. Multimodal analyses (and other disciplines using videos) are so far dependent on time and resource intensive processes of manual transcription of each component from video materials. Automating these tasks requires advanced programming skills, which is often not in the scope of IL. Moreover, the use of different tools makes the integration and analysis of different formats challenging. Consequently, IL research often deals with relatively small samples of annotated data which are suitable for qualitative analysis but not enough for making generalized empirical claims derived quantitatively. VIAN-DH aims to create a workspace where many annotation layers required for the multimodal analysis of videos can be created, processed, and correlated in one platform. VIAN-DH will provide a graphical interface that operates state-of-the-art tools for automating parts of the data processing. The integration of tools that already exist in computational linguistics and computer vision, facilitates data processing for researchers lacking programming skills, speeds up the overall research process, and enables the processing of large amounts of data. The main features to be introduced are automatic speech recognition for the transcription of language, automatic image recognition for extraction of gestures and other visual cues, as well as grammatical annotation for adding morphological and syntactic information to the verbal content. In the ongoing instance of VIAN-DH, we focus on gesture extraction (pointing gestures, in particular), making use of existing models created for sign language and adapting them for this specific purpose. In order to view and search the data, VIAN-DH will provide a unified format and enable the import of the main existing formats of annotated video data and the export to other formats used in the field, while integrating different data source formats in a way that they can be combined in research. VIAN-DH will adapt querying methods from corpus linguistics to enable parallel search of many annotation levels, combining token-level and chronological search for various types of data. VIAN-DH strives to bring crucial and potentially revolutionary innovation to the field of IL, (that can also extend to other fields using video materials). It will allow the processing of large amounts of data automatically and, the implementation of quantitative analyses, combining it with the qualitative approach. It will facilitate the investigation of correlations between linguistic patterns (lexical or grammatical) with conversational aspects (turn-taking or gestures). Users will be able to automatically transcribe and annotate visual, spoken and grammatical information from videos, and to correlate those different levels and perform queries and analyses.

Keywords: multimodal analysis, corpus linguistics, computational linguistics, image recognition, speech recognition

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Authors: Mara F. Müller, Simon C. Griffith, Tara L. Crewe, Mirjam Kaestli, Sydney J. Collett, Ian J. Radford, Hamish A. Campbell

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The intensity and frequency of heat waves have been progressively increasing because of climate change. Passerines that inhabit very hot regions are already close to their physiological thermal limit and are thus considered highly susceptible to increased ambient temperatures. However, the extent by which passerines behaviorally compensate for extreme heat in their natural habitat has rarely been assessed due to monitoring challenges. To address this knowledge gap, coded VHF-nano transmitters were attached to a tropical passerine (Gouldian finch, Chloebia gouldiae). Fine-scale activity and movement were monitored throughout the hottest and driest period of the year using an array of static VHF-receivers. The finches were found to typically show a peak activity for a few hours at sunrise and remained relatively quiescent for the rest of the day. However, on extremely hot days (max temperature >38ºC), finches showed higher activity levels earlier in the morning and presented a second peak in the afternoon. Gouldian finches are physiologically challenged when ambient temperatures exceed 38ºC, suggesting the shift in movement activity reflects a behavioral mitigation strategy to extreme heat. These tropical finches already exist on an energetic knife-edge during this time of the year due to resource scarcity. Hence, the increased energetic expenditure to mitigate thermal stress may be detrimental. The study demonstrates the value of VHF-telemetry technology in monitoring the impact of global change on the biology of small-bodied mobile species.

Keywords: animal tracking, biotelemetry, climate change, extreme heat, movement activity, radiotelemetry, VHF-telemetry

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Authors: Fatemeh Babaeian, Nemai Chandra Karmakar

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Chipless RFID system is a wireless system for tracking and identification which use passive tags for encoding data. The advantage of using chipless RFID tag is having a planar tag which is printable on different low-cost materials like paper and plastic. The printed tag can be attached to different items in the labelling level. Since the price of chipless RFID tag can be as low as a fraction of a cent, this technology has the potential to compete with the conventional optical barcode labels. However, due to the passive structure of the tag, data processing of the reflection signal is a crucial challenge. The captured reflected signal from a tag attached to an item consists of different components which are the reflection from the reader antenna, the reflection from the item, the tag structural mode RCS component and the antenna mode RCS of the tag. All these components are summed up in both time and frequency domains. The effect of reflection from the item and the structural mode RCS component can distort/saturate the frequency domain signal and cause difficulties in extracting the desired component which is the antenna mode RCS. Therefore, it is required to study the reflection of the tag in both time and frequency domains to have a better understanding of the nature of the captured chipless RFID signal. The other benefits of this study can be to find an optimised encoding technique in tag design level and to find the best processing algorithm the chipless RFID signal in decoding level. In this paper, the reflection from a typical backscattered chipless RFID tag with six resonances is analysed, and different components of the signal are separated in both time and frequency domains. Moreover, the time domain signal corresponding to each resonator of the tag is studied. The data for this processing was captured from simulation in CST Microwave Studio 2017. The outcome of this study is understanding different components of a measured signal in a chipless RFID system and a discovering a research gap which is a need to find an optimum detection algorithm for tag ID extraction.

Keywords: antenna mode RCS, chipless RFID tag, resonance, structural mode RCS

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Authors: Nneka Augustina Akwu, Yougasphree Naidoo

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Molecular advancement in technology has created a means whereby the atoms and molecules (solid forms) of certain materials such as plants, can now be reduced to a range of 1-100 nanometres. Green synthesis of silver nanoparticles (AgNPs) was carried out at room temperature (RT) 25 ± 2°C and 80°C, using the metabolites in the aqueous extracts of the leaves and stem bark of Grewia lasiocarpa as reductants and stabilizing agents. The biosynthesized AgNPs were characterized by UV-Vis spectrophotometry, attenuated total reflectance - Fourier transforms infrared (ATR-FTIR) spectroscopy, nanoparticle tracking analysis (NTA), Energy Dispersive X-ray fluorescence scanning electron microscope (SEM-EDXRF) and high-resolution transmission electron microscopy (HRTEM). The AgNPs were biologically evaluated for antioxidant, antibacterial and cytotoxicity activities. The phytochemical and FTIR analyses revealed the presence of metabolites that act as reducing and capping agents, while the UV-Vis spectroscopy of the biosynthesized NPs showed absorption between 380-460 nm, confirming AgNP synthesis. The Zeta potential values were between -9.1 and -20.6 mV with a hydrodynamics diameter ranging from 38.3 to 46.7 nm. SEM and HRTEM analyses revealed that AgNPs were predominately spherical with an average particle size of 2- 31 nm for the leaves and 5-27 nm for the stem bark. The cytotoxicity IC50 values of the AgNPs against HeLa, Caco-2 and MCF-7 were >1 mg/mL. The AgNPs were sensitive to all strains of bacteria used, with methicillin-resistant Staphylococcus aureus (MRSA), Staphylococcus aureus (ATCC 25923) and Escherichia coli (ATCC 25922) being more sensitive to the AgNPs. Our findings propose that antibacterial and anticancer agents could be derived from these AgNPs of G. lasiocarpa, and warrant their further investigation.

Keywords: antioxidant, cytotoxicity, Grewia lasiocarpa, silver nanoparticles, Zeta potentials

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