Search results for: passive optical networks (PONs)

Authors: Peng Li, Luan Wang, Haifeng Fei, Renhong Xie, Yibin Rui, Shanhong Guo

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The applications of satellite-based automatic identification system (S-AIS) pave the road for wide-range maritime traffic monitoring and management. But the coverage of satellite’s view includes multiple AIS self-organizing networks, which leads to the collision of AIS signals from different cells. The contribution of this work is to propose an improved multi-channel blind source separation algorithm based on Artificial Bee Colony (ABC) and advanced stochastic optimization to perform separation of the mixed AIS signals. The proposed approach adopts modified ABC algorithm to get an optimized initial separating matrix, which can expedite the initialization bias correction, and utilizes the Adaptive Moment Estimation (Adam) to update the separating matrix by adjusting the learning rate for each parameter dynamically. Simulation results show that the algorithm can speed up convergence and lead to better performance in separation accuracy.

Keywords: satellite-based automatic identification system, blind source separation, artificial bee colony, adaptive moment estimation

Procedia PDF Downloads 183

Authors: Tharntip Tawnie Chutikulrungsee, Oliver Kisalay Burmeister, Maumita Bhattacharya, Dragana Calic

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Sharing on social network sites (SNSs) has rapidly emerged as a new social norm and has become a global phenomenon. Billions of users reveal not only their own information (self disclosure) but also information about others (other-generated disclosure), resulting in a risk and a serious threat to either personal or informational privacy. Self-disclosure (SD) has been extensively researched in the literature, particularly regarding control of individual and existing privacy management. However, far too little attention has been paid to other-generated disclosure (OGD), especially by insiders. OGD has a strong influence on self-presentation, self-image, and electronic word of mouth (eWOM). Moreover, OGD is more credible and less likely manipulated than SD, but lacks privacy control and legal protection to some extent. This article examines OGD in depth, ranging from motivation to both online and offline impacts, based upon lived experiences from both ‘the disclosed’ and ‘the discloser’. Using purposive sampling, this phenomenological study involves an online survey and in-depth interviews. The findings report the influence of peer disclosure as well as users’ strategies to mitigate privacy issues. This article also calls attention to the challenge of OGD privacy and inadequacies in the law related to privacy protection in the digital domain.

Keywords: facebook, online privacy, other-generated disclosure, social networks sites (SNSs)

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Authors: Vanaja Rao

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In the recent times, the need for the integration of Renewable Energy Sources (RES) in a Smart Grid is on the rise. As a result of this, associated energy storage systems are known to play important roles in sustaining the efficient operation of such RES like wind power and solar power. This paper investigates the importance of location selection of Energy Storage Systems (ESSs) in a Smart Grid. Three scenarios of ESS location is studied and analyzed in a Smart Grid, which are – 1. Near the generation/source, 2. In the middle of the Grid and, 3. Near the demand/consumption. This is explained with the aim of assisting any Distribution Network Operator (DNO) in deploying the ESSs in a power network, which will significantly help reduce the costs and time of planning and avoid any damages incurred as a result of installing them at an incorrect location of a Smart Grid. To do this, the outlined scenarios mentioned above are modelled and analyzed with the National Grid’s datasets of energy generation and consumption in the UK power network. As a result, the outcome of this analysis aims to provide a better overview for the location selection of the ESSs in a Smart Grid. This ensures power system stability and security along with the optimum usage of the ESSs.

Keywords: distribution networks, energy storage system, energy security, location planning, power stability, smart grid

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Authors: Jigar Shaileshumar Halpati, Aravind Kumar Chandiran

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Vacancy ordered double perovskites (VOPs) have been significantly attracting researchers due to their chemical structure diversity and interesting optoelectronic properties. Some VOPs have been recently reported to be suitable photoelectrodes for photoelectrochemical water-splitting reactions due to their high stability and panchromatic absorption. In this work, we systematically synthesized mixed tetravalent VOPs based on Cs₂RuₘPt₁-ₘX₆ (X = Cl-, Br-) and reported their structural, optical, electrochemical and photoelectrochemical properties. The structural characterization confirms that the mixed tetravalent site intermediates formed their own phases. The parent materials, as well as their intermediates, were found to be stable in ambient conditions for over 1 year and also showed incredible stability in harsh pH media ranging from pH 1 to pH 11. Moreover, these materials showed panchromatic absorption with onset up to 1000 nm depending upon the mixture stoichiometry. The extraordinary stability and excellent absorption properties make them suitable materials for photoelectrochemical water-splitting applications. PEC studies of these series of materials showed a high water oxidation photocurrent of 0.56 mA cm-² for Cs₂Ru₀.₅Pt₀.₅Cl₆. Fundamental investigation from photoelectrochemical reactions revealed that the intrinsic ruthenium-based VOP showed enhanced hole transfer to the electrolyte, while the intrinsic platinum-based VOP showed higher photovoltage. The mix of these end members at the tetravalent site showed a synergic effect of reduced charge transfer resistance from the material to the electrolyte and increased photovoltage, which led to increased PEC performance of the intermediate materials.

Keywords: solar water splitting, photo electrochemistry, photo absorbers, material characterization, device characterization, green hydrogen

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Authors: Yosra Mefteh Rekik, Younes Boujelbene

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We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

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Authors: P. Viduthalai, A. K. Divakar, V. Natarajan

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Media is one of the powerful tools that manipulate the world in numerous aspects especially in the form of a communication process. For instance, the concept of the public sphere, which was earlier represented by landlords and elites has now transformed into a virtual public sphere, which is also represented by marginalized people. Unfortunately, this acquisition is still paradoxical. Though the media proliferation and its effects are humongous, still it has not been the same throughout the world. Inequality in access to media has created a technological divide among people. Finally, globalization and approach by the government towards using media for development communication has significantly changed the way in which the media reaches every nook and corner. Monarchy, oligarchy, republic and democracy together form the basis of most governments of the world. Of which, democracy is the one with the highest involvement and participation of the people. Ideally, the participation of the people is what, that keeps the democracy running. A healthy democracy is possible only when people are able to access information that makes citizens responsible and serves to check the functioning of their elected representatives. On one side the media consumption of people plays a crucial role in the formation of the public sphere, and on the other side, big media conglomerates are a serious threat to community participation, which is a goal that the media should strive for in a country like India. How different people consume these different media, differs greatly from length and breadth of the country. Another aspect of this media consumption is that it isn’t passive. People usage and consumption of media are related with the gratification that they derive from the particular media. This aspect varies from person to person and from society to society according to both internal and external factors. This article sets out from the most underlying belief that Malayali Tribes have adopted television and becomes a part of daily life and a day never passes without it especially after the introduction of Free Television Scheme by the past state government. Though they are living in hilly and socially isolated places, they too have started accessing media for understanding about the people of the plains and their culture, dictated by their interest. Many of these interests appear to have a social and psychological origin. The present research attempts to study how gratification of these needs lead Malayali Tribes to form such a virtual public sphere where they could communicate with people of the plains. Data was collected through survey method, from 300 respondents on “Exposure towards Television and their perception”. Conventional anthropological methods like unstructured interviews were also used to supplement the data collection efforts in the three taluks namely Yercaud, Pethanayankkanpalayam and Panamaraththuppatty in Salem district of TamilNadu. The results highlight the role of Television in gratifying needs of the Malayali Tribes.

Keywords: democracy, gratification, Malayali Tribes and television, virtual public sphere

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Authors: Yin Yuanling

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A Deep Feedback Recurrent Neural Network (DFRNN) and Bidirectional Long Short-Term Memory (BiLSTM) are designed to address the problem of low accuracy of traditional relationship extraction models. This method combines a deep feedback-based recurrent neural network (DFRNN) with a bi-directional long short-term memory (BiLSTM) approach. The method combines DFRNN, which extracts local features of text based on deep feedback recurrent mechanism, BiLSTM, which better extracts global features of text, and Self-Attention, which extracts semantic information. Experiments show that the method achieves an F1 value of 76.69% on the CEC dataset, which is 0.0652 better than the BiLSTM+Self-ATT model, thus optimizing the performance of the deep learning method in the event relationship extraction task.

Keywords: event relations, deep learning, DFRNN models, bi-directional long and short-term memory networks

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Authors: Nasir Haruna Soba

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In addition to sustaining poverty and inequality, the issue of out-of-school children impedes efforts to accomplish the sustainable development goals (SDGs), especially Goal 4, which is to guarantee inclusive, egalitarian, and high-quality education for everyone. However, a number of social, cultural, and infrastructure barriers mean that millions of children in Nigeria are denied this privilege. This paper presents the findings of a case study conducted in Nigeria. The findings of this study revealed that out of school children in Nigeria are the most common causes of poverty; inadequate school facilities, long distances to schools, and poor road networks make it difficult for children, especially in rural areas, to access education. Social Disparities: Social inequality is sustained by differences in education, especially when it comes to financing, governance, and coordination amongst stakeholders. These differences are especially pronounced along gender and socioeconomic lines. The study recommended that policymakers and stakeholders should consider addressing the root causes, enhancing existing interventions, and implementing targeted policy measures. Nigeria can make significant strides towards ensuring inclusive and quality education for all children, thereby fostering sustainable development and reducing poverty.

Keywords: poverty, inequality, funding, education, development

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Authors: Musaab Salman Sultan

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The surface and bulk magnetization behavior of template released isolated ferromagnetic Ni₆₀Fe₄₀ nanowires of relatively thick diameters (~200 nm), deposited from a dilute suspension onto pre-patterned insulating chips have been investigated experimentally, using a highly sensitive Magneto-Optical Ker Effect (MOKE) magnetometry and Magneto-Resistance (MR) measurements, respectively. The MR data were consistent with the theoretical predictions of the anisotropic magneto-resistance (AMR) effect. The MR measurements, in all the angles of investigations, showed large features and a series of nonmonotonic "continuous small features" in the resistance profiles. The extracted switching fields from these features and from MOKE loops were compared with each other and with the switching fields reported in the literature that adopted the same analytical techniques on the similar compositions and dimensions of nanowires. A large difference between MOKE and MR measurments was noticed. The disparate between MOKE and MR results is attributed to the variance in the micro-magnetic structure of the surface and the bulk of such ferromagnetic nanowires. This result was ascertained using micro-magnetic simulations on an individual: cylindrical and rectangular cross sections NiFe nanowires, with the same diameter/thickness of the experimental wires, using the Object Oriented Micro-magnetic Framework (OOMMF) package where the simulated loops showed different switching events, indicating that such wires have different magnetic states in the reversal process and the micro-magnetic spin structures during switching behavior was complicated. These results further supported the difference between surface and bulk magnetization behavior in these nanowires. This work suggests that a combination of MOKE and MR measurements is required to fully understand the magnetization behavior of such relatively thick isolated cylindrical ferromagnetic nanowires.

Keywords: MOKE magnetometry, MR measurements, OOMMF package, micromagnetic simulations, ferromagnetic nanowires, surface magnetic properties

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Authors: Mustafa Sahin, İlkay Yavrucuk

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This paper presents a wind turbine envelope protection control algorithm that protects Variable Speed Variable Pitch (VSVP) wind turbines from damage during operation throughout their below and above rated regions, i.e. from cut-in to cut-out wind speed. The proposed approach uses a neural network that can adapt to turbines and their operating points. An algorithm monitors instantaneous wind and turbine states, predicts a wind speed that would push the turbine to a pre-defined envelope limit and, when necessary, realizes an avoidance action. Simulations are realized using the MS Bladed Wind Turbine Simulation Model for the NREL 5 MW wind turbine equipped with baseline controllers. In all simulations, through the proposed algorithm, it is observed that the turbine operates safely within the allowable limit throughout the below and above rated regions. Two example cases, adaptations to turbine operating points for the below and above rated regions and protections are investigated in simulations to show the capability of the proposed envelope protection system (EPS) algorithm, which reduces excessive wind turbine loads and expectedly increases the turbine service life.

Keywords: adaptive envelope protection control, limit detection and avoidance, neural networks, ultimate load reduction, wind turbine power control

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Authors: Adithya Jaikumar, Sudarsan Jayasingh

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The dramatic technology led changes that continue to take place at the market place has led to the emergence and implication of online brand pages on social media networks. The Facebook brand page has become extremely popular among different brands. The primary aim of this study was to identify the impact of post formats and content type on customer engagement in Facebook brand pages. Methodology used for this study was to analyze and categorize 9037 content messages posted by 20 automobile brands in India during April 2014 to March 2015 and the customer activity it generated in return. The data was obtained from Fanpage karma- an online tool used for social media analytics. The statistical technique used to analyze the count data was negative binomial regression. The study indicates that there is a statistically significant relationship between the type of post and the customer engagement. The study shows that photos are the most posted format and highest engagement is found to be related to videos. The finding also reveals that social events and entertainment related content increases engagement with the message.

Keywords: content analysis, customer engagement, digital engagement, facebook brand pages, social media

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Authors: Tahani Amutairi, Paul May, Neil Allan

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Many properties of semiconductor materials (mechanical, electronic, magnetic, and optical) can be significantly modified by introducing a point defect. Diamond offers extraordinary properties as a semiconductor, and doping seems to be a viable method of solving the problem associated with the fabrication of diamond-based electronic devices in order to exploit those properties. The dopants are believed to play a significant role in reducing the energy barrier to conduction and controlling the mobility of the carriers and the resistivity of the film. Although it has been proven that the n-type diamond semiconductor can be obtained with phosphorus doping, the resulting ionisation energy and mobility are still inadequate for practical application. Theoretical studies have revealed that this is partly because the effects of the many phosphorus atoms incorporated in the diamond lattice are compensated by acceptor states. Using spin-polarised hybrid density functional theory and a supercell approach, we explored the effects of bonding one N atom to a P in adjacent substitutional sites in diamond. A range of hybrid functional, including HSE06, B3LYP, PBE0, PBEsol0, and PBE0-13, were used to calculate the formation, binding, and ionisation energies, in order to explore the solubility and stability of the point defect. The equilibrium geometry and the magnetic and electronic structures were analysed and presented in detail. The defect introduces a unique reconstruction in a diamond where one of the C atoms coordinated with the N atom involved in the elongated C-N bond and creates a new bond with the P atom. The simulated infrared spectra of phosphorus-nitrogen defects were investigated with different supercell sizes and found to contain two sharp peaks at the edges of the spectrum, one at a high frequency 1,379 cm⁻¹ and the second appearing at the end range, 234 cm⁻¹, as obtained with the largest supercell (216).

Keywords: DFT, HSE06, B3LYP, PBE0, PBEsol0, PBE0-13

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Authors: Joseph Uzuazomaro Oju

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The ease at which manipulated media can be created, and the increasing difficulty in identifying fake media makes it a great threat. Most of the applications used for the creation of these high-quality fake videos and images are built with deep learning. Hence, the use of deep learning in creating a detection mechanism cannot be overemphasized. Any successful fake media that is being detected before it reached the populace will save people from the self-doubt of either a content is genuine or fake and will ensure the credibility of videos and images. The methodology introduced in this paper approaches the manipulated media detection challenge using a combo of VGG-19 and a deep capsule network. In the case of videos, they are converted into frames, which, in turn, are resized and cropped to the face region. These preprocessed images/videos are fed to the VGG-19 network to extract the latent features. The extracted latent features are inputted into a deep capsule network enhanced with a 3D -convolution dynamic routing agreement. The 3D –convolution dynamic routing agreement algorithm helps to reduce the linkages between capsules networks. Thereby limiting the poor learning shortcoming of multiple capsule network layers. The resultant output from the deep capsule network will indicate a media to be either genuine or fake.

Keywords: deep capsule network, dynamic routing, fake media detection, manipulated media

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Authors: Burak Köken, Hatice D. Arslan, Bilgehan Y. Çakmak

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Analyzing the relation networks between the hospital buildings which have complex structure and distinctive spatial relationships is quite difficult. The hospital buildings which require specialty in spatial relationship solutions during design and self-innovation through the developing technology should survive and keep giving service even after the disasters such as earthquakes. In this study, a hospital building where the load-bearing system was strengthened because of the insufficient earthquake performance and the construction of an additional building was required to meet the increasing need for space was discussed and a comparative spatial evaluation of the hospital building was made with regard to its status before the change and after the change. For this reason, spatial organizations of the building before change and after the change were analyzed by means of Space Syntax method and the effects of the change on space organization parameters were searched by applying an analytical procedure. Using Depthmap UCL software, connectivity, visual mean depth, beta and visual integration analyses were conducted. Based on the data obtained after the analyses, it was seen that the relationships between spaces of the building increased after the change and the building has become more explicit and understandable for the occupants. Furthermore, it was determined according to findings of the analysis that the increase in depth causes difficulty in perceiving the spaces and the changes considering this problem generally ease spatial use.

Keywords: architecture, hospital building, space syntax, strengthening

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Authors: Jung-Hun Cho, Tae-Heon Moon, Jin-Hak Lee

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Land price contains the comprehensive characteristics of urban space, representing the social and economic features of the city. Accordingly, land price can be utilized as an indicator, which can identify the changes of spatial structure and socioeconomic variations caused by urban development. This study attempted to explore the changes in land price by a new road construction. Methodologically, it adopted Space Syntax, which can interpret urban spatial structure comprehensively, to identify the relationship between the forms of road networks and land price. The result of the regression analysis showed the ‘integration index’ of Space Syntax is statistically significant and has a strong correlation with land price. If the integration value is high, land price increases proportionally. Subsequently, using regression equation, it tried to predict the land price changes of each of the lots surrounding the roads that are newly opened. The research methods or study results have the advantage of predicting the changes in land price in an easy way. In addition, it will contribute to planners and project managers to establish relevant polices and smoothing urban regeneration projects through enhancing residents’ understanding by providing possible results and advantages in their land price before the execution of urban regeneration and development projects.

Keywords: space syntax, urban regeneration, spatial structure, official land price

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Authors: Nishank Raisinghani

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Efficiently predicting drug response remains a challenge in the realm of drug discovery. To address this issue, we propose four model architectures that combine graphical representation with varying positions of multiheaded self-attention mechanisms. By leveraging two types of multi-omics data, transcriptomics and genomics, we create a comprehensive representation of target cells and enable drug response prediction in precision medicine. A majority of our architectures utilize multiple transformer models, one with a graph attention mechanism and the other with a multiheaded self-attention mechanism, to generate latent representations of both drug and omics data, respectively. Our model architectures apply an attention mechanism to both drug and multiomics data, with the goal of procuring more comprehensive latent representations. The latent representations are then concatenated and input into a fully connected network to predict the IC-50 score, a measure of cell drug response. We experiment with all four of these architectures and extract results from all of them. Our study greatly contributes to the future of drug discovery and precision medicine by looking to optimize the time and accuracy of drug response prediction.

Keywords: drug discovery, transformers, graph neural networks, multiomics

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Authors: Colette Faucher

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In modern asymmetric conflicts, the Armed Forces generally have to intervene in countries where the internal peace is in danger. They must make the local population an ally in order to be able to deploy the necessary military actions with its support. For this purpose, psychological operations (PSYOPs) are used to shape people’s behaviors and emotions by the modification of their attitudes in acting on their perceptions. PSYOPs aim at elaborating and spreading a message that must be read, listened to and/or looked at, then understood by the info-targets in order to get from them the desired behavior. A message can generate in the info-targets, reasoned thoughts, spontaneous emotions or reflex behaviors, this effect partly depending on the means of conveyance used to spread this message. In this paper, we focus on psychological operations that generate emotions. We present a method based on the Intergroup Emotion Theory, that determines, from the characteristics of the conveyed message and of the people from the population directly reached by the means of conveyance (direct info-targets), the emotion likely to be triggered in them and we simulate the propagation of the effects of such a message on indirect info-targets that are connected to them through the social networks that structure the population.

Keywords: military psychological operations, social identity, social network, emotion propagation

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Authors: Sheikh, R. Author, Bhardwaj S. Author, Jr.

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The emphasis of this paper is to investigate the identity shifts experienced within the Indian community and among Muslim refugee women in Sydney. Using Goffman’s paradigm of everyday interactions, attention is paid to how migrants navigate and perform their multiple identities in their daily life. By focusing on narratives of the migrant- migration is understood as processual instead of a one time decision of re-location. The paper aims to highlight how individuals choose and re-adapt their cultural and social practices within the context of Australia. Migrant narratives are rooted in specific socio-cultural settings of one’s own community as well as the nature of migration to a specific country. Differences and similarities will be observed within the Indian community, and among Muslim refugee women in terms of how identity is negotiated, social networks are re-established in Australia. Some attention will also be paid to difficulties that are being faced by migrants-especially in terms of Muslim identity for Refugee women, particularly in terms of assimilation, building on Ghassan Hage’s use of appraisal theory and how a diversity of language and religion is accommodated within the Indian community. By using two diverse groups, it would be able to identify and contrast migrant experiences.

Keywords: identity, migrant, refugee, women, assimilation, narratives

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Authors: Giselda Cristina Ferreira, Carlos Alberto Kamienski, Ana Lígia Scott

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The COVID-19 pandemic has enhanced the anti-vaccination movement in Brazil, supported by unscientific theories and false news and the possibility of wide communication through social networks such as Twitter, Facebook, and YouTube. The World Health Organization (WHO) classified the large volume of information on the subject against COVID-19 as an Infodemic. In this paper, we present a protocol to identify polarizing users (called polarizers) and study the profiles of Brazilian polarizers on Twitter (renamed to X some weeks ago). We analyzed polarizing interactions on Twitter (in Portuguese) to identify the main polarizers and how the conflicts they caused influenced the COVID-19 vaccination rate throughout the pandemic. This protocol uses data from this social network, graph theory, Java, and R-studio scripts to model and analyze the data. The information about the vaccination rate was obtained in a public database for the government called OpenDataSus. The results present the profiles of Twitter’s Polarizer (political position, gender, professional activity, immunization opinions). We observed that social and political events influenced the participation of these different profiles in conflicts and the vaccination rate.

Keywords: Twitter, polarization, vaccine, Brazil

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Authors: Tsu-Hsu Yen

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The interfacial gas adsorption presents a frequent challenge and opportunity for micro-/nano-fluidic operation. In this study, we investigate the wettability, gas accumulation, and nanobubble formation on various homogeneous surface conditions by using MD simulation, including a series of 3D and quasi-2D argon-water-solid systems simulation. To precisely determine the wettability on various substrates, several indicators were calculated. Among these wettability indicators, the water PMF (potential of mean force) has the most correlation tendency with interfacial water molecular orientation than depletion layer width and droplet contact angle. The results reveal that the aggregation of argon molecules on substrates not only depending on the level of hydrophobicity but also determined by the competition between gas-solid and water-solid interaction as well as water molecular structure near the surface. In addition, the surface nanobubble is always observed coexisted with the gas enrichment layer. The water structure adjacent to water-gas and water-solid interfaces also plays an important factor in gas out-flux and gas aggregation, respectively. The quasi-2D simulation shows that only a slight difference in the curved argon-water interface from the plane interface which suggests no noticeable obstructing effect on gas outflux from the gas-water interfacial water networks.

Keywords: gas aggregation, interfacial nanobubble, molecular dynamics simulation, wettability

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Authors: Yassamina Berkane, Leila Kloul, Yoann Demoli

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Quality of life, environmental impact, congestion of mobility means, and infrastructures remain significant challenges for urban mobility. Solutions like car sharing, spatial redesign, eCommerce, and autonomous vehicles will likely increase the unit veh-km and the density of cars in urban traffic, thus reducing congestion. However, the impact of such solutions is not clear for researchers. Congestion arises from growing populations that must travel greater distances to arrive at similar locations (e.g., workplaces, schools) during the same time frame (e.g., rush hours). This paper first reviews the research and application cases of urban congestion methods through recent years. Rethinking the question of time, it then investigates people’s willingness and flexibility to adapt their arrival and departure times from workplaces. We use neural networks and methods of supervised learning to apply a new methodology for predicting peoples' intentions from their responses in a questionnaire. We created and distributed a questionnaire to more than 50 companies in the Paris suburb. Obtained results illustrate that our methodology can predict peoples' intentions to reschedule their activities (work, study, commerce, etc.).

Keywords: urban mobility, decongestion, machine learning, neural network

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Authors: P. S. Jagadeesh Kumar, Yang Yung, Mingmin Pan, Xianpei Li, Wenli Hu

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Glaucoma is impelled by optic nerve mutilation habitually represented as cupping and visual field injury frequently with an arcuate pattern of mid-peripheral loss, subordinate to retinal ganglion cell damage and death. Glaucoma is the second foremost cause of blindness and the chief cause of permanent blindness worldwide. Consequently, all-embracing study into the analysis and empathy of glaucoma is happening to escort deep learning based neural network intrusions to deliberate this substantial optic neuropathy. This paper advances an ophthalmic hashing based supervision of glaucoma and corneal disorders preeminent on deep graphical model. Ophthalmic hashing is a newly proposed method extending the efficacy of visual hash-coding to predict glaucoma corneal disorder matching, which is the faster than the existing methods. Deep graphical model is proficient of learning interior explications of corneal disorders in satisfactory time to solve hard combinatoric incongruities using deep Boltzmann machines.

Keywords: corneal disorders, deep Boltzmann machines, deep graphical model, glaucoma, neural networks, ophthalmic hashing

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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Gliomas are most challenging and aggressive type of tumors which appear in different sizes, locations, and scattered boundaries. CNN is most efficient deep learning approach with outstanding capability of solving image analysis problems. A fully automatic deep learning based 2D-CNN model for brain tumor segmentation is presented in this paper. We used small convolution filters (3 x 3) to make architecture deeper. We increased convolutional layers for efficient learning of complex features from large dataset. We achieved better results by pushing convolutional layers up to 16 layers for HGG model. We achieved reliable and accurate results through fine-tuning among dataset and hyper-parameters. Pre-processing of this model includes generation of brain pipeline, intensity normalization, bias correction and data augmentation. We used the BRATS-2015, and Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.81 for complete, 0.79 for core, 0.80 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, HGG

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Authors: Najib Al-Fadhali, Huda Majid

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In this article, a substrate integrated waveguide cavity slot antenna was designed using a computer simulation technology software tool to address the specific design challenges for millimeter-wave communications posed by future satellite communications. Due to the symmetrical structure, a high-order mode is generated in SIW, which yields high gain and high efficiency with a compact feed structure. The antenna has dimensions of 20 mm x 20 mm x 1.34 mm. The proposed antenna bandwidth ranges from 45 GHz to 50 GHz, covering a Q-band application such as satellite communication. Antenna efficiency is above 80% over the operational frequency range. The gain of the antenna is above 9 dB with a peak value of 9.4 dB at 47.5 GHz. The proposed antenna is suitable for various millimeter-wave applications such as sensing, body imaging, indoor scenarios, new generations of wireless networks, and future satellite communications. The simulated results show that the SIW antenna resonates throughout the bands of 45 to 50 GHz, making this new antenna cover all applications within this range. The reflection coefficients are below 10 dB in most ranges from 45 to 50 GHz. The compactness, integrity, reliability, and performance at various operating frequencies make the proposed antenna a good candidate for future satellite communications.

Keywords: ultra-wideband, Q-band, SIW, mm-wave, satellite communications

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Authors: Albert Alexander Stonier

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Due to the fossil fuel exhaustion and environmental pollution, renewable energy sources especially solar photovoltaic system plays a predominant role in providing energy to the consumers. It has been estimated that by 2050 the renewable energy sources will satisfy 50% of the total energy requirement of the world. In this context, the faults in the conversion process require a special attention which is considered as a major problem. A fault which remains even for a few seconds will cause undesirable effects to the system. The presentation comprises of the analysis, causes, effects and mitigation methods of various faults occurring in the entire solar photovoltaic energy conversion process. In order to overcome the faults in the system, an intelligent based artificial neural networks and fuzzy logic are proposed which can significantly mitigate the faults. Hence the presentation intends to find the problem in renewable energy and provides the possible solution to overcome it with simulation and experimental results. The work performed in a 3kWp solar photovoltaic plant whose results cites the improvement in reliability, availability, power quality and fault tolerant ability.

Keywords: solar photovoltaic, power electronics, power quality, PWM

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Authors: Ming-Hsiang Shih, Wen-Pei Sung, Shih-Heng Tung

Abstract:

Semi-active control system for structure under excitation of earthquake provides with the characteristics of being adaptable and requiring low energy. DSHD (Displacement Semi-Active Hydraulic Damper) was developed by our research team. Shake table test results of this DSHD installed in full scale test structure demonstrated that this device brought its energy-dissipating performance into full play for test structure under excitation of earthquake. The objective of this research is to develop a new AIC (Active Interaction Control Device) and apply shake table test to perform its dissipation of energy capability. This new proposed AIC is converting an improved DSHD (Displacement Semi-Active Hydraulic Damper) to AIC with the addition of an accumulator. The main concept of this energy-dissipating AIC is to apply the interaction function of affiliated structure (sub-structure) and protected structure (main structure) to transfer the input seismic force into sub-structure to reduce the structural deformation of main structure. This concept is tested using full-scale multi-degree of freedoms test structure, installed with this proposed AIC subjected to external forces of various magnitudes, for examining the shock absorption influence of predictive control, stiffness of sub-structure, synchronous control, non-synchronous control and insufficient control position. The test results confirm: (1) this developed device is capable of diminishing the structural displacement and acceleration response effectively; (2) the shock absorption of low precision of semi-active control method did twice as much seismic proof efficacy as that of passive control method; (3) active control method may not exert a negative influence of amplifying acceleration response of structure; (4) this AIC comes into being time-delay problem. It is the same problem of ordinary active control method. The proposed predictive control method can overcome this defect; (5) condition switch is an important characteristics of control type. The test results show that synchronism control is very easy to control and avoid stirring high frequency response. This laboratory results confirm that the device developed in this research is capable of applying the mutual interaction between the subordinate structure and the main structure to be protected is capable of transforming the quake energy applied to the main structure to the subordinate structure so that the objective of minimizing the deformation of main structural can be achieved.

Keywords: DSHD (Displacement Semi-Active Hydraulic Damper), AIC (Active Interaction Control Device), shake table test, full scale structure test, sub-structure, main-structure

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Authors: Krishan Kumar, Mohit Mittal, Pramod Kumar

Abstract:

Wireless sensor network is one of the most promising communication networks for monitoring remote environmental areas. In this network, all the sensor nodes are communicated with each other via radio signals. The sensor nodes have capability of sensing, data storage and processing. The sensor nodes collect the information through neighboring nodes to particular node. The data collection and processing is done by data aggregation techniques. For the data aggregation in sensor network, clustering technique is implemented in the sensor network by implementing self-organizing feature map (SOFM) neural network. Some of the sensor nodes are selected as cluster head nodes. The information aggregated to cluster head nodes from non-cluster head nodes and then this information is transferred to base station (or sink nodes). The aim of this paper is to manage the huge amount of data with the help of SOM neural network. Clustered data is selected to transfer to base station instead of whole information aggregated at cluster head nodes. This reduces the battery consumption over the huge data management. The network lifetime is enhanced at a greater extent.

Keywords: artificial neural network, data clustering, self organization feature map, wireless sensor network

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Authors: S. S. Sree Sanker, K. N. Madhusoodanan

Abstract:

Optical biosensors are dominant alternative for traditional analytical methods, because of their small size, simple design and high sensitivity. Photonic sensing method is one of the recent advancing technology for biosensors. It measures the change in refractive index which is induced by the difference in molecular interactions due to the change in concentration of the analyte. Glucose is an aldosic monosaccharide, which is a metabolic source in many of the organisms. The terahertz waves occupies the space between infrared and microwaves in the electromagnetic spectrum. Terahertz waves are expected to be applied to various types of sensors for detecting harmful substances in blood, cancer cells in skin and micro bacteria in vegetables. We have designed glucose sensors using silicon based 1D and 2D photonic crystal pillar arrays in terahertz frequency range. 1D photonic crystal has rectangular pillars with height 100 µm, length 1600 µm and width 50 µm. The array period of the crystal is 500 µm. 2D photonic crystal has 5×5 cylindrical pillar array with an array period of 75 µm. Height and diameter of the pillar array are 160 µm and 100 µm respectively. Two samples considered in the work are blood and glucose solution, which are labelled as sample 1 and sample 2 respectively. The proposed sensor detects the concentration of glucose in the samples from 0 to 100 mg/dL. For this, the crystal was irradiated with 0.3 to 3 THz waves. By analyzing the obtained S parameter, the refractive index of the crystal corresponding to the particular concentration of glucose was measured using the parameter retrieval method. Refractive indices of the two crystals decreased gradually with the increase in concentration of glucose in the sample. For 1D photonic crystals, a gradual decrease in refractive index was observed at 1 THz. 2D photonic crystal showed this behavior at 2 THz. The proposed sensor was simulated using CST Microwave studio. This will enable us to develop a model which can be used to characterize a glucose sensor. The present study is expected to contribute to blood glucose monitoring.

Keywords: CST microwave studio, glucose sensor, photonic crystal, terahertz waves

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Authors: Emineh Tsegahun Gedif

Abstract:

Zinc oxide nanoparticles (ZnO NPs) have garnered significant attention due to their diverse applications encompassing catalytic, optical, photonic, and antibacterial properties. In this study, we successfully synthesized zinc oxide nanoparticles using a rapid, environmentally benign, and cost-effective method. Neem (Azadirachta indica) leaf extract served as the reducing agent for Zn (NO₃)₂.6H2O solution under optimized conditions (pH = 9). Qualitative screening techniques and FT-IR Spectroscopy confirmed the presence of active biomolecules such as flavonoids, phenolic groups, alkaloids, terpenoids, and tannins within the Neem leaf extract, both before and after reduction. The formation of ZnO NPs was visually evident through a distinct color change from colorless to light yellow. The biosynthesized nanoparticles underwent comprehensive characterization through UV-visible, FT-IR, and XRD spectroscopies. The reduction process proved to be straightforward and user-friendly, with UV-visible spectroscopy demonstrating a surface plasmon resonance (SPR) at 321 nm, unequivocally confirming the ZnO NP formation. X-ray diffraction analysis elucidated the crystal structure, revealing an average particle size of approximately 20 nm using Scherrer's equation based on the line width of the plane. Furthermore, the synthesized zinc oxide nanoparticles were evaluated for their antimicrobial properties against both Gram-positive and Gram-negative bacteria. The results showcased significant inhibitory activity, with the highest zone of inhibition observed against Escherichia coli (15 mm) and comparatively lower activity against Staphylococcus aureus. This research underscores the potential of Neem leaf extract-mediated synthesis of ZnO NPs as an eco-friendly and effective approach for various applications, including antibacterial agents.

Keywords: zinc oxide nanoparticles (ZnO NPs), bioreducing agent, green synthesis, antibacterial activity

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Authors: Min Jin Kwon, Seung Won Kim, Eui Yeon Kim, Haeyoung Lee

Abstract:

Numerous anonymous chat apps that help people to connect with random strangers have been released in South Korea. However, they become a serious problem for young people since young people often use them for channels of prostitution or sexual violence. Although ISPs in South Korea are responsible for making inappropriate content inaccessible on their networks, they do not block traffic of random chat apps since 1) the use of random chat apps is entirely legal. 2) it is reported that they use HTTP proxy blocking so that non-HTTP traffic cannot be blocked. In this paper, we propose a service model that can block random chat apps at home routers. A service provider manages a blacklist that contains blocked apps’ information. Home routers that subscribe the service filter the traffic of the apps out using deep packet inspection. We have implemented a prototype of the proposed model, including a centralized server providing the blacklist, a Raspberry Pi-based home router that can filter traffic of the apps out, and an Android app used by the router’s administrator to locally customize the blacklist.

Keywords: deep packet inspection, internet filtering, juvenile protection, technical blocking

Procedia PDF Downloads 345