Search results for: message passing neural network

Authors: Joonha Park

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This essay examines the Soviet Artist Pavel Korin’s artistic pursuit towards his life-long project, “Requiem/Passing of the Rus,” framing the funeral of Tikhon, the last great defender of the Russian orthodox Church during the Great purge, as the final moment of “Rus,” which is the identity of the Russian people that built up in the 1000 year of history behind Russian Orthodoxy. Korin’s project remains in the form of a series of 29 man-sized portraits and a monumental blank canvas. Born in a family dedicated to iconography, Korin witnessed the historic drama during Stalin’s terror; therefore, he tried to convey the nation’s mourning for the disappearance of “Rus” and disapproval of the Soviet notion of atheism. Yet, due to Korin’s success as a state artist, many believed that the political pressure led Korin to give up his belief and controversy arose over the fact that Korin left the canvas blank. The empty 40-square-meter canvas, which remains untouched in his studio since 1930, supports this theory to an extent. However, resources such as Korin’s notes, primary accounts from his fellow Soviet Artists, and testimonies from his wife suggested that this assumption is incorrect. Moreover, Korin’s uninterrupted relationship with the church and the religious attributes in his commissioned works were brought up as evidence of Korin’s continued belief. The empty canvas not only represents Korin’s discontentment towards the repression and the hardships that the Orthodox Church experienced, but also depicts the identity that coexisted with the Church in order to bequeath this idea to future generations. The faultless canvas surrounded by the striking 29 portraits is a symbol of the highest spirit, similar to that of the iconography paintings placed in every Russian house that unites the Russian people till this day, therefore one can deduce that the legacy of “Requiem” is still relevant to the Russian people even under freedom of religious expression. Consequently, “Requiem” was on display at the Tretyakov Gallery for the first time in public in 2013 even though Korin started creating this piece in 1925, extolling Korin not only as an artist but also as a historian; by recording the turmoil of the Great Oppression, Korin exhibited the social responsibility universal to artists across time and space. In this essay, the legacy Korin left behind, both to his contemporaries and his posterity is reevaluated through the lens of his works, unfinished as they were.

Keywords: Pavel Korin, Art History, Art, Russia, Soviet Union, Requiem, Russian orthodox church, Treytyakov gallery, contemporary art, socialist realism, Maxim Gorky

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Authors: Beatriz Cortés, Andrés Boza, David Pérez, Llanos Cuenca

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The Internet of Things (IoT) field is been applied in industries with different purposes. Sensing Enterprise (SE) is an attribute of an enterprise or a network that allows it to react to business stimuli originating on the internet. These fields have come into focus recently on the enterprises and there is some evidence of the use and implications in supply chain management while finding it as an interesting aspect to work on. This paper presents a revision and proposals of IoT applications in supply chain management.

Keywords: industrial, internet of things, production systems, sensing enterprises, sensor, supply chain management

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Authors: Gabriele Barrocas, Habon Issa

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The amygdala is one of various brain regions that tend to be pathological in individuals with autism spectrum disorder (ASD). ASD is a prevalent and heterogeneous developmental disorder affecting all ethnic and socioeconomic groups and consists of a broad range of severity, etiology, and behavioral symptoms. Common features of ASD include but are not limited to repetitive behaviors, obsessive interests, and anxiety. Neuroscientists view the amygdala as the core of the neural system that regulates behavioral responses to anxiogenic and threatening stimuli. Despite this consensus, many previous studies and literature reviews on the amygdala’s alterations in individuals with ASD have reported inconsistent findings. In this review, we will address these conflicts by highlighting recent studies which reveal that anatomical and related socio-emotional differences detected between individuals with and without ASD are highly age-dependent. We will specifically discuss studies using functional magnetic resonance imaging (fMRI), structural MRI, and diffusion tensor imaging (DTI) to provide insights into the neuroanatomical substrates of ASD across development, with a focus on amygdala volumes, cell densities, and connectivity.

Keywords: autism, amygdala, development, abnormalities

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Authors: Santos Andressa M. N.

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The research brings reflections on the importance of Instagram for the clothing trade, aiming to analyze the use of this social network as a sales tool by small companies in the fashion/clothing sector in Boqueirão-PI. Thus, field research was carried out, with the application of questionnaires, to raise and analyze data related to the topic. Thus, it is believed that Instagram positively influences the dissemination, visibility, reach and profitability of companies in Boqueirão do Piauí. The survey had a low number of companies due to the lack of availability of the owners during the COVID-19 pandemic.

Keywords: Instagram, sales, fashion, marketing

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Authors: Diogo José Morgado Rebelo, Francisco António Carneiro Pacheco de Andrade, Paulo Jorge Freitas de Oliveira Novais

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Not everything in AI-power consumer credit scoring turns out to be a wonder. When using AI in Creditworthiness Assessment (CWA), opacity and unfairness ‘sins’ must be considered to the task be deemed Responsible. AI software is not always 100% accurate, which can lead to misclassification. Discrimination of some groups can be exponentiated. A hetero personalized identity can be imposed on the individual(s) affected. Also, autonomous CWA sometimes lacks transparency when using black box models. However, for this intended purpose, human analysts ‘on-the-loop’ might not be the best remedy consumers are looking for in credit. This study seeks to explore the legality of implementing a Multi-Agent System (MAS) framework in consumer CWA to ensure compliance with the regulation outlined in Article 14(4) of the Proposal for an Artificial Intelligence Act (AIA), dated 21 April 2021 (as per the last corrigendum by the European Parliament on 19 April 2024), Especially with the adoption of Art. 18(8)(9) of the EU Directive 2023/2225, of 18 October, which will go into effect on 20 November 2026, there should be more emphasis on the need for hybrid oversight in AI-driven scoring to ensure fairness and transparency. In fact, the range of EU regulations on AI-based consumer credit will soon impact the AI lending industry locally and globally, as shown by the broad territorial scope of AIA’s Art. 2. Consequently, engineering the law of consumer’s CWA is imperative. Generally, the proposed MAS framework consists of several layers arranged in a specific sequence, as follows: firstly, the Data Layer gathers legitimate predictor sets from traditional sources; then, the Decision Support System Layer, whose Neural Network model is trained using k-fold Cross Validation, provides recommendations based on the feeder data; the eXplainability (XAI) multi-structure comprises Three-Step-Agents; and, lastly, the Oversight Layer has a 'Bottom Stop' for analysts to intervene in a timely manner. From the analysis, one can assure a vital component of this software is the XAY layer. It appears as a transparent curtain covering the AI’s decision-making process, enabling comprehension, reflection, and further feasible oversight. Local Interpretable Model-agnostic Explanations (LIME) might act as a pillar by offering counterfactual insights. SHapley Additive exPlanation (SHAP), another agent in the XAI layer, could address potential discrimination issues, identifying the contribution of each feature to the prediction. Alternatively, for thin or no file consumers, the Suggestion Agent can promote financial inclusion. It uses lawful alternative sources such as the share of wallet, among others, to search for more advantageous solutions to incomplete evaluation appraisals based on genetic programming. Overall, this research aspires to bring the concept of Machine-Centered Anthropocentrism to the table of EU policymaking. It acknowledges that, when put into service, credit analysts no longer exert full control over the data-driven entities programmers have given ‘birth’ to. With similar explanatory agents under supervision, AI itself can become self-accountable, prioritizing human concerns and values. AI decisions should not be vilified inherently. The issue lies in how they are integrated into decision-making and whether they align with non-discrimination principles and transparency rules.

Keywords: creditworthiness assessment, hybrid oversight, machine-centered anthropocentrism, EU policymaking

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Authors: Nizamuddin Zainuddin, Adam Mohd Saifudin, Ahmad Yusni Bahaudin, Mohd Hanizan Zalazilah, Roslan Jamaluddin

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Students’ enhanced experience through simulation is a crucial factor that brings reality to the classroom. The enhanced experience is all about developing, enriching and applications of a generic process flow in the field of logistics and transportations. As educational technology has improved, the effective use of simulations has greatly increased to the point where simulations should be considered a valuable, mainstream pedagogical tool. Additionally, in this era of ongoing (some say never-ending) assessment, simulations offer a rich resource for objective measurement and comparisons. Simulation is not just another in the long line of passing fads (or short-term opportunities) in educational technology. It is rather a real key to helping our students understand the world. It is a way for students to acquire experience about how things and systems in the world behave and react, without actually touching them. In short, it is about interactive pretending. Simulation is all about representing the real world which includes grasping the complex issues and solving intricate problems. Therefore, it is crucial before stimulate the real process of inbound and outbound logistics and transportation a generic process flow shall be developed. The paper will be focusing on the validization of the process flow by looking at the inputs gains from the sample. The sampling of the study focuses on multi-national and local manufacturing companies, third party companies (3PL) and government agency, which are selected in Peninsular Malaysia. A simulation flow chart was proposed in the study that will be the generic flow in logistics and transportation. A qualitative approach was mainly conducted to gather data in the study. It was found out from the study that the systems used in the process of outbound and inbound are System Application Products (SAP) and Material Requirement Planning (MRP). Furthermore there were some companies using Enterprises Resources Planning (ERP) and Electronic Data Interchange (EDI) as part of the Suppliers Own Inventories (SOI) networking as a result of globalized business between one countries to another. Computerized documentations and transactions were all mandatory requirement by the Royal Custom and Excise Department. The generic process flow will be the basis of developing a simulation program that shall be used in the classroom with the objective of further enhanced the students’ learning experience. Thus it will contributes to the body of knowledge on the enrichment of the student’s employability and also shall be one of the way to train new workers in the logistics and transportation filed.

Keywords: enhancement, simulation, process flow, logistics, transportation

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Authors: Abulbasit G. Abdulsayid, Zinab F. Abdulla, Asma A. Omer

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On the ground that the orifice plate is relatively inexpensive, requires very little maintenance and only calibrated during the occasion of plant turnaround, the orifice plate has turned to be in a real prevalent use in gas industry. Inaccuracy of measurement in the fiscal metering stations may highly be accounted to be the most vital factor for mischarges in the natural gas industry in Libya. A very trivial error in measurement can add up a fast escalating financial burden to the custodian transactions. The unaccounted gas quantity transferred annually via orifice plates in Libya, could be estimated in an extent of multi-million dollars. As the oil and gas wealth is the solely source of income to Libya, every effort is now being exerted to improve the accuracy of existing orifice metering facilities. Discharge coefficient has become pivotal in current researches undertaken in this regard. Hence, increasing the knowledge of the flow field in a typical orifice meter is indispensable. Recently and in a drastic pace, the CFD has become the most time and cost efficient versatile tool for in-depth analysis of fluid mechanics, heat and mass transfer of various industrial applications. Getting deeper into the physical phenomena lied beneath and predicting all relevant parameters and variables with high spatial and temporal resolution have been the greatest weighing pros counting for CFD. In this paper, flow phenomena for air passing through an orifice meter were numerically analyzed with CFD code based modeling, giving important information about the effect of orifice plate specifications on the discharge coefficient for three different tappings locations, i.e., flange tappings, D and D/2 tappings compared with vena contracta tappings. Discharge coefficients were paralleled with discharge coefficients estimated by ISO 5167. The influences of orifice plate bore thickness, orifice plate thickness, beveled angle, perpendicularity and buckling of the orifice plate, were all duly investigated. A case of an orifice meter whose pipe diameter of 2 in, beta ratio of 0.5 and Reynolds number of 91100, was taken as a model. The results highlighted that the discharge coefficients were highly responsive to the variation of plate specifications and under all cases, the discharge coefficients for D and D/2 tappings were very close to that of vena contracta tappings which were believed as an ideal arrangement. Also, in general sense, it was appreciated that the standard equation in ISO 5167, by which the discharge coefficient was calculated, cannot capture the variation of the plate specifications and thus further thorough considerations would be still needed.

Keywords: CFD, discharge coefficients, orifice meter, orifice plate specifications

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Authors: Linda Smail, Zineb Azouz

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Given a Bayesian network relative to a set I of discrete random variables, we are interested in computing the probability distribution P(S) where S is a subset of I. The general idea is to write the expression of P(S) in the form of a product of factors where each factor is easy to compute. More importantly, it will be very useful to give an interpretation of each of the factors in terms of conditional probabilities. This paper considers a semantic interpretation of the factors involved in computing marginal probabilities in Bayesian networks. Establishing such a semantic interpretations is indeed interesting and relevant in the case of large Bayesian networks.

Keywords: Bayesian networks, D-Separation, level two Bayesian networks, factorization of computation

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Authors: Hee Sun (Sunny) Choi, Gerhard Bruyns, Wang Zhang, Sky Cheng, Saijal Sharma

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This research addresses the need for a comprehensive framework that can guide the design and assessment of multi-level public spaces and public realms and their impact on the built environment. The study aims to understand and measure the neural mechanisms involved in this process. By doing so, it can lay the foundation for vertical and volumetric urbanism and ensure consistency and excellence in the field while also supporting scientific research methods for urban design with cognitive neuroscientists. To investigate these aspects, the paper focuses on the neighborhood scale in Hong Kong, specifically examining multi-level public spaces and quasi-public spaces within both commercial and residential complexes. The researchers use predictive Artificial Intelligence (AI) as a methodology to assess and comprehend the applicability of the urban design framework for vertical and volumetric urbanism. The findings aim to identify the factors that contribute to successful public spaces within a vertical living environment, thus introducing a new typology of public spaces.

Keywords: vertical urbanism, scientific research methods, spatial cognition, urban design guideline

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Authors: Mehmood Ali, Attaullah Khan, Md. Abul Kalam

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Petroleum crude oil reserves are going to deplete in future due to the consumption of fossil fuels in transportation and energy generating sector. Thus, increasing the fossil fuel prices and also causing environmental degradation issues such as climate change and global warming due to air pollution. Therefore, to tackle these issues the environmentally friendly fuels are the potential substitute with lower emissions of toxic gases. A non-edible vegetable oilseed crop, Jatropha curcas, from different origins such as Malaysia, Thailand and India were cultivated in Pakistan. The harvested seeds physical, chemical and mechanical properties were measured, having an influence on the post-harvesting machines design parameters for dehulling, storing bins, drying, oil extraction from seeds with a screw expeller and in-situ transesterification reaction to produce biodiesel fuel. The seed variety from Thailand was found better in comparison of its properties with other varieties from Malaysia and India. The seed yield from these three varieties i.e. Malaysia, Thailand and India were 829, 943 and 735 kg/ acre/ year respectively. While the oil extraction yield from Thailand variety seed was found higher (i.e. 32.61 % by wt.) as compared to other two varieties from Malaysia and India were 27.96 and 24.96 % by wt respectively. The physical properties investigated showed the geometric mean diameter of seeds from three varieties Malaysia, Thailand and India were 11.350, 10.505 and 11.324 mm, while the sphericity of seeds were found 0.656, 0.664 and 0.655. The bulk densities of the powdered seeds from three varieties Malaysia, Thailand and India, were found as 0.9697, 0.9932 and 0.9601 g/cm³ and % passing was obtained with sieve test were 78.7, 87.1 and 79.3 respectively. The densities of the extracted oil from three varieties Malaysia, Thailand and India were found 0.902, 0.898 and 0.902 g/ mL with corresponding kinematic viscosities 54.50, 49.18 and 48.16 mm2/sec respectively. The higher heating values (HHV) of extracted oil from Malaysia, Thailand and India seed varieties were measured as 40.29, 36.41 and 34.27 MJ/ kg, while the HHV of de-oiled cake from these varieties were 21.23, 20.78 and 17.31 MJ/kg respectively. The de-oiled cake can be used as compost with nutrients and carbon content to enhance soil fertility to grow future Jatropha curcas oil seed crops and also can be used as a fuel for heating and cooking purpose. Moreover, the mechanical parameter micro Vickers hardness of Malaysia seed was found lowest 16.30 HV measured with seed in a horizontal position to the loading in comparison to other two varieties as 25.2 and 18.7 HV from Thailand and India respectively. The fatty acid composition of three varieties of seed oil showed the presence of C8-C22, required to produce good quality biodiesel fuel. In terms of physicochemical properties of seeds and its extracted oil, the variety from Thailand was found better as compared to the other two varieties.

Keywords: biodiesel, Jatropha curcas, mechanical property, physico-chemical properties

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Authors: Desmond Young

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In building services electrical design, a key element of any project will be assessing the electrical load requirements. This needs to be done early in the design process to allow the selection of infrastructure that would be required to meet the electrical needs of the type of building. The type of building will define the type of assessment made, and the values applied in defining the maximum demand for the building, and ultimately the size of supply or infrastructure required, and the application that needs to be made to the distribution network operator, or alternatively to an independent network operator. The fact that this assessment needs to be undertaken early in the design process provides limits on the type of assessment that can be used, as different methods require different types of information, and sometimes this information is not available until the latter stages of a project. A common method applied in the earlier design stages of a project, typically during stages 1,2 & 3, is the use of benchmarks. It is a possibility that some of the benchmarks applied are excessive in relation to the current loads that exist in a modern installation. This lack of accuracy is based on information which does not correspond to the actual equipment loads that are used. This includes lighting and small power loads, where the use of more efficient equipment and lighting has reduced the maximum demand required. The electrical load can be used as part of the process to assess the heat generated from the equipment, with the heat gains from other sources, this feeds into the sizing of the infrastructure required to cool the building. Any overestimation of the loads would contribute to the increase in the design load for the heating and ventilation systems. Finally, with the new policies driving the industry to decarbonise buildings, a prime example being the recently introduced London Plan, loads are potentially going to increase. In addition, with the advent of the pandemic and changes to working practices, and the adoption of electric heating and vehicles, a better understanding of the loads that should be applied will aid in ensuring that infrastructure is not oversized, as a cost to the client, or undersized to the detriment of the building. In addition, more accurate benchmarks and methods will allow assessments to be made for the incorporation of energy storage and renewable technologies as these technologies become more common in buildings new or refurbished.

Keywords: energy, ADMD, electrical load assessment, energy benchmarks

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Authors: R. M. López-Gutiérrez, L. Cardoza-Avendaño, H. Cervantes-de Ávila, J. A. Michel-Macarty, C. Cruz-Hernández, A. Arellano-Delgado, R. Carmona-Rodríguez

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In this paper, synchronization of multiple chaotic semiconductor lasers is achieved by appealing to complex system theory. In particular, we consider dynamical networks composed by semiconductor laser, as interconnected nodes, where the interaction in the networks are defined by coupling the first state of each node. An interesting case is synchronized with master-slave configuration in star topology. Nodes of these networks are modeled for the laser and simulated by Matlab. These results are applicable to private communication.

Keywords: chaotic laser, network, star topology, synchronization

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Authors: Sonia Boscenco, Zihan Wang, Euclides José de Mendoça Filho, João Paulo Hoppe, Irina Pokhvisneva, Geoffrey B.C. Hall, Michael J. Meaney, Patricia Pelufo Silveira

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Entropy can be described as a measure of the number of states of a system, and when used in the context of physiological time-based signals, it serves as a measure of complexity. In functional connectivity data, entropy can account for the moment-to-moment variability that is neglected in traditional functional magnetic resonance imaging (fMRI) analyses. While brain fMRI resting state entropy has been associated with some pathological conditions like schizophrenia, no investigations have explored the association between brain entropy measures and individual differences in child behavior in healthy children. We describe a novel exploratory approach to evaluate brain fMRI resting state data in two child cohorts, and MAVAN (N=54, 4.5 years, 48% males) and GUSTO (N = 206, 4.5 years, 48% males) and its associations to child behavior, that can be used in future research in the context of child exposures and long-term health. Following rs-fMRI data pre-processing and Shannon entropy calculation across 32 network regions of interest to acquire 496 unique functional connections, partial correlation coefficient analysis adjusted for sex was performed to identify associations between entropy data and Strengths and Difficulties questionnaire in MAVAN and Child Behavior Checklist domains in GUSTO. Significance was set at p < 0.01, and we found eight significant associations in GUSTO. Negative associations were found between two frontoparietal regions and cerebellar posterior and oppositional defiant problems, (r = -0.212, p = 0.006) and (r = -0.200, p = 0.009). Positive associations were identified between somatic complaints and four default mode connections: salience insula (r = 0.202, p < 0.01), dorsal attention intraparietal sulcus (r = 0.231, p = 0.003), language inferior frontal gyrus (r = 0.207, p = 0.008) and language posterior superior temporal gyrus (r = 0.210, p = 0.008). Positive associations were also found between insula and frontoparietal connection and attention deficit / hyperactivity problems (r = 0.200, p < 0.01), and insula – default mode connection and pervasive developmental problems (r = 0.210, p = 0.007). In MAVAN, ten significant associations were identified. Two positive associations were found = with prosocial scores: the salience prefrontal cortex and dorsal attention connection (r = 0.474, p = 0.005) and the salience supramarginal gyrus and dorsal attention intraparietal sulcus (r = 0.447, p = 0.008). The insula and prefrontal connection were negatively associated with peer problems (r = -0.437, p < 0.01). Conduct problems were negatively associated with six separate connections, the left salience insula and right salience insula (r = -0.449, p = 0.008), left salience insula and right salience supramarginal gyrus (r = -0.512, p = 0.002), the default mode and visual network (r = -0.444, p = 0.009), dorsal attention and language network (r = -0.490, p = 0.003), and default mode and posterior parietal cortex (r = -0.546, p = 0.001). Entropy measures of resting state functional connectivity can be used to identify individual differences in brain function that are correlated with variation in behavioral problems in healthy children. Further studies applying this marker into the context of environmental exposures are warranted.

Keywords: child behaviour, functional connectivity, imaging, Shannon entropy

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Authors: Imdad Ullah Khan, Yongseok Yoon, Kyeung Uk Choi, Kwang Rae Jo, Namyul Kim, Eunbee Lee, Wan Hee Kim, Oh-Kyeong Kweon

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The primary spinal cord injury (SCI) causes mechanical damage to the neurons and blood vessels. It leads to secondary SCI, which activates multiple pathological pathways, which expand neuronal damage at the injury site. It is characterized by vascular disruption, ischemia, excitotoxicity, oxidation, inflammation, and apoptotic cell death. It causes nerve demyelination and disruption of axons, which perpetuate a loss of impulse conduction through the injured spinal cord. It also leads to the production of myelin inhibitory molecules, which with a concomitant formation of an astroglial scar, impede axonal regeneration. The pivotal role regarding the neuronal necrosis is played by oxidation and inflammation. During an early stage of spinal cord injury, there occurs an abundant expression of reactive oxygen species (ROS) due to defective mitochondrial metabolism and abundant migration of phagocytes (macrophages, neutrophils). ROS cause lipid peroxidation of the cell membrane, and cell death. Abundant migration of neutrophils, macrophages, and lymphocytes collectively produce pro-inflammatory cytokines such as tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), interleukin-1beta (IL-1β), matrix metalloproteinase, superoxide dismutase, and myeloperoxidases which synergize neuronal apoptosis. Therefore, it is crucial to control inflammation and oxidation injury to minimize the nerve cell death during secondary spinal cord injury. Therefore, in response to oxidation and inflammation, heme oxygenase-1 (HO-1) is induced by the resident cells to ameliorate the milieu. In the meanwhile, neurotrophic factors are induced to promote neuroregeneration. However, it seems that anti-stress enzyme (HO-1) and neurotrophic factor (BDNF) do not significantly combat the pathological events during secondary spinal cord injury. Therefore, optimum healing can be induced if anti-inflammatory and neurotrophic factors are administered in a higher amount through an exogenous source. During the first experiment, the inflammation and neuroregeneration were selectively targeted. HO-1 expressing MSCs (HO-1 MSCs) and BDNF expressing MSCs (BDNF MSC) were co-transplanted in one group (combination group) of dogs with subacute spinal cord injury to selectively control the expression of inflammatory cytokines by HO-1 and induce neuroregeneration by BDNF. We compared the combination group with the HO-1 MSCs group, BDNF MSCs group, and GFP MSCs group. We found that the combination group showed significant improvement in functional recovery. It showed increased expression of neural markers and growth-associated proteins (GAP-43) than in other groups, which depicts enhanced neuroregeneration/neural sparing due to reduced expression of pro-inflammatory cytokines such as TNF-alpha, IL-6 and COX-2; and increased expression of anti-inflammatory markers such as IL-10 and HO-1. Histopathological study revealed reduced intra-parenchymal fibrosis in the injured spinal cord segment in the combination group than in other groups. Thus it was concluded that selectively targeting the inflammation and neuronal growth with the combined use of HO-1 MSCs and BDNF MSCs more favorably promote healing of the SCI. HO-1 MSCs play a role in controlling the inflammation, which favors the BDNF induced neuroregeneration at the injured spinal cord segment of dogs.

Keywords: HO-1 MSCs, BDNF MSCs, neuroregeneration, inflammation, anti-inflammation, spinal cord injury, dogs

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Authors: Marina Vicario, Amadeo Argüelles, Pilar Gómez, Carlos Hernández

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In this paper, the Computer Research Network of the National Polytechnic Institute of Mexico proposes a paradigmatic model for the inference of cognitive patterns in digital learning systems. This model leads to metadata architecture useful for analysis and prediction in online learning systems; especially on MOOc's architectures. The model is in the design phase and expects to be tested through an institutional of courses project which is going to develop for the MOOc.

Keywords: cognitive footprints, learning analytics, predictive learning, digital learning, educational computing, educational informatics

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Authors: Güzi̇n Ti̇rkeş, Özge Teki̇n, Kerem Kurtuluş, Y. Yekta Yurtseven, Murat Baran

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A scanning electron microscope (SEM) is a type of electron microscope mainly used in nanoscience and nanotechnology areas. Automatic image recognition and classification are among the general areas of application concerning SEM. In line with these usages, the present paper proposes a deep learning algorithm that classifies SEM images into nine categories by means of an online application to simplify the process. The NFFA-EUROPE - 100% SEM data set, containing approximately 21,000 images, was used to train and test the algorithm at 80% and 20%, respectively. Validation was carried out using a separate data set obtained from the Middle East Technical University (METU) in Turkey. To increase the accuracy in the results, the Inception ResNet-V2 model was used in view of the Fine-Tuning approach. By using a confusion matrix, it was observed that the coated-surface category has a negative effect on the accuracy of the results since it contains other categories in the data set, thereby confusing the model when detecting category-specific patterns. For this reason, the coated-surface category was removed from the train data set, hence increasing accuracy by up to 96.5%.

Keywords: convolutional neural networks, deep learning, image classification, scanning electron microscope

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Authors: Wen-Bin Chiou, Hsiao-Chiao Weng

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Social networking sites (SNS) such as Facebook and Twitter are low-cost tools that can promote the creation of social connections by providing a convenient platform that can be accessed at any time. In the current research, a laboratory experiment was conducted test the hypothesis that reminders of losing SNS would alter the impact of social events, especially those involving social exclusion. Specifically, this study explored whether losing SNS would intensify perceived social distress induced by exclusionary bogus feedback. Eighty-eight Facebook users (46 females, 42 males; mean age = 22.6 years, SD = 3.1 years) were recruited via campus posters and flyers at a national university in southern Taiwan. After participants provided consent, they were randomly assigned to a 2 (SNS non-use vs. neutral) between-subjects experiment. Participants completed an ostensible survey about online social networking in which we included an item about the time spent on SNS per day. The last question was used to manipulate thoughts about losing SNS access. Participants under the non-use condition were asked to record three conditions that would render them unable to use SNS (e.g., a network adaptor problem, malfunctioning cable modem, or problems with Internet service providers); participants under the neutral condition recorded three conditions that would render them unable to log onto the college website (e.g., server maintenance, local network or firewall problems). Later, this experiment employed a bogus-feedback paradigm to induce social exclusion. Participants then rated their social distress on a four-item scale, identical to that of Experiment 1 (α = .84). The results showed that thoughts of losing SNS intensified distress caused by social exclusion, suggesting that the loss of SNS has a similar effect to the loss of a primary source for social reconnections. Moreover, the priming effects of SNS on perceived distress were more prominent for heavy users. The demonstrated link between the idea of losing SNS use and increased pain of social exclusion manifests the importance of SNS as a crucial gateway for acquiring and rebuilding social connections. Use of online social networking appears to be a two-edged sword for coping with social exclusion in human lives in the e-society.

Keywords: online social networking, perceived distress, social exclusion, SNS

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Authors: Allmin Susaiyah, Aki Härmä, Milan Petković

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Automatic generation of insights from data using insight mining systems (IMS) is useful in many applications, such as personal health tracking, patient monitoring, and business process management. Existing IMS face challenges in controlling insight extraction, scaling to large databases, and generalising to unseen domains. In this work, we propose a hybrid approach consisting of rule-based and neural components for generating insights from data while overcoming the aforementioned challenges. Firstly, a rule-based data 2CNL component is used to extract statistically significant insights from data and represent them in a controlled natural language (CNL). Secondly, a BERTSum-based CNL2NL component is used to convert these CNLs into natural language texts. We improve the model using task-specific and domain-specific fine-tuning. Our approach has been evaluated using statistical techniques and standard evaluation metrics. We overcame the aforementioned challenges and observed significant improvement with domain-specific fine-tuning.

Keywords: data mining, insight mining, natural language generation, pre-trained language models

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Authors: Ashiq Hussain, Mahwash Hussain, Zeenat Parveen

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Now a days the demand for broadband service has increased. Due to which the researchers are trying to find a solution to provide a large amount of service. There is a shortage of bandwidth because of the use of downloading video, voice and data. One of the solutions to overcome this shortage of bandwidth is to provide the communication system with passive optical components. We have increased the data rate in this system. From experimental results we have concluded that the quality factor has increased by adding passive optical networks.

Keywords: WDM-PON, optical fiber, BER, Q-factor, eye diagram

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Authors: Xabier Olaz Moratinos

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Drone navigation is critical, particularly during the initial phases, such as the initial ascension, where pilots may fail due to strong external interferences that could potentially lead to a crash. In this ongoing work, a drone has been successfully trained to perform an ascent of up to 6 meters at speeds with external disturbances pushing it up to 24 mph, with the DQN algorithm managing external forces affecting the system. It has been demonstrated that the system can control its height, position, and stability in all three axes (roll, pitch, and yaw) throughout the process. The learning process is carried out in the Gazebo simulator, which emulates interferences, while ROS is used to communicate with the agent.

Keywords: machine learning, DQN, Gazebo, navigation

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Authors: Catia S. A. Sima, K. Bousson

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Congestion in the Terminal Maneuvering Areas (TMAs) of larger airports impacts all aspects of air traffic flow, not only at national level but may also induce arrival delays at international level. Hence, there is a need to monitor appropriately the air traffic flow in TMAs so that efficient decisions may be taken to manage their occupancy rates. It would be desirable to physically increase the existing airspace to accommodate all existing demands, but this question is entirely utopian and, given this possibility, several studies and analyses have been developed over the past decades to meet the challenges that have arisen due to the dizzying expansion of the aeronautical industry. The main objective of the present paper is to propose concepts to manage and reduce the degree of uncertainty in the air traffic operations, maximizing the interest of all involved, ensuring a balance between demand and supply, and developing and/or adapting resources that enable a rapid and effective adaptation of measures to the current context and the consequent changes perceived in the aeronautical industry. A central task is to emphasize the increase in air traffic flow management capacity to the present day, taking into account not only a wide range of methodologies but also equipment and/or tools already available in the aeronautical industry. The efficient use of these resources is crucial as the human capacity for work is limited and the actors involved in all processes related to air traffic flow management are increasingly overloaded and, as a result, operational safety could be compromised. The methodology used to answer and/or develop the issues listed above is based on the advantages promoted by the application of Markov Chain principles that enable the construction of a simplified model of a dynamic network that describes the air traffic flow behavior anticipating their changes and eventual measures that could better address the impact of increased demand. Through this model, the proposed concepts are shown to have potentials to optimize the air traffic flow management combined with the operation of the existing resources at each moment and the circumstances found in each TMA, using historical data from the air traffic operations and specificities found in the aeronautical industry, namely in the Portuguese context.

Keywords: air traffic flow, terminal maneuvering area, TMA, air traffic management, ATM, Markov chains

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Authors: M. K. Benhaoua, A. K. Singh, A. E. H. Benyamina

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In this paper, we propose heuristic for dynamic communications mapping that considers the placement of communications in order to optimize the overall performance. The mapping technique uses a newly proposed Algorithm to place communications between the tasks. The placement we propose of the communications leads to a better optimization of several performance metrics (time and energy consumption). Experimental results show that the proposed mapping approach provides significant performance improvements when compared to those using static routing.

Keywords: Multi-Processor Systems-on-Chip (MPSoCs), Network-on-Chip (NoC), heterogeneous architectures, dynamic mapping heuristics

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Authors: Vikram Kalekar

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Modern Internet Protocol (IP) networks deploy traditional and modern Quality of Service (QoS) management methods to ensure the smooth flow of network packets during regular operations. SDN (Software-defined networking) networks have also made headway into better service delivery by means of novel QoS methodologies. While many of these techniques are experimental, some of them have been tested extensively in controlled environments, and few of them have the potential to be deployed widely in the industry. With this survey, we plan to analyze the approaches to QoS and resource allocation in SDN, and we will try to comment on the possible improvements to QoS management in the context of SDN.

Keywords: QoS, policy, congestion, flow management, latency, delay index terms-SDN, delay

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Authors: Madeleine Elder, Aye Htun

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Background: Myiasis is the parasitic infestation of body tissues by fly larvae. It predominantly occurs in poor socioeconomic regions of tropical and subtropical countries where it is associated with poor hygiene and sanitation. Cutaneous and wound myiasis are the most common presentations whereas urogenital myiasis is rare, with few reported cases. Case: a 26-year-old primiparous woman with a low-risk pregnancy presented to the emergency department at 37+3-weeks’ gestation after passing a 2cm black larva during micturition, with 2 weeks of mild vulvar pruritus and dysuria. She had travelled to India 9-months prior. Examination of the external genitalia showed small white larvae over the vulva and anus and a mildly inflamed introitus. Speculum examination showed infiltration into the vagina and heavy white discharge. High vaginal swab reported Candida albicans. Urine microscopy reported bacteriuria with Enterobacter cloacae. Urine parasite examination showed myiasis caused by Clogmia albipunctata species of fly larvae from the family Psychodidae. Renal tract ultrasound and inflammatory markers were normal. Infectious diseases, urology and paediatric teams were consulted. The woman received treatment for her urinary tract infection (which was likely precipitated by bladder irritation from local parasite infestation) and vaginal candidiasis. She underwent daily physical removal of parasites with cleaning, speculum examination and removal, and hydration to promote bladder emptying. Due to the risk of neonatal exposure, aspiration pneumonitis and facial infestation, the woman was steroid covered and proceeded to have an elective caesarean section at 38+3-weeks’ gestation, with delivery of a healthy infant. She then proceeded to have a rigid cystoscopy and washout, which was unremarkable. Placenta histopathology revealed focal eosinophilia in keeping with the history of maternal parasites. Conclusion: Urogenital myiasis is very rare, especially in the developed world where it is seen in returned travellers. Treatment may include systemic therapy with ivermectin and physical removal of parasites. During pregnancy, physical removal is considered the safest treatment option, and discussion around the timing and mode of delivery should consider the risk of harm to the foetus.

Keywords: urogenital myiasis, parasitic infection, infection in pregnancy, returned traveller

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Authors: Ioana Simina Frincu

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As institutional initiatives often fail to provide good practices when it comes to heritage management or to adapt to the changing environment in which they function and to the audiences they address, private actions represent viable strategies for sustainable knowledge acquisition. Information dissemination to future generations is one of the key aspects in preserving cultural heritage and is successfully feasible even in the absence of original artifacts. Combined with the (re)discovery of natural landscape, open-air exploratory approaches (archeoparks) versus an enclosed monodisciplinary rigid framework (traditional museums) are more likely to 'speak the language' of a larger number of people, belonging to a variety of categories, ages, and professions. Interactive sites are efficient ways of stimulating heritage awareness and increasing the number of visitors of non-interactive/static cultural institutions owning original pieces of history, delivering specialized information, and making continuous efforts to preserve historical evidence (relics, manuscripts, etc.). It is high time entrepreneurs took over the role of promoting cultural heritage, bet it under a more commercial yet more attractive form (business). Inclusive, participatory type of activities conceived by experts from different domains/fields (history, anthropology, tourism, sociology, business management, integrative sustainability, etc.) have better chances to ensure long term cultural benefits for both adults and children, especially when and where the educational discourse fails. These unique self-experience leisure activities, which offer everyone the opportunity to recreate history by him-/her-self, to relive the ancestors’ way of living, surviving and exploring should be regarded not as pseudo-scientific approaches but as important pre-steps to museum experiences. In order to support this theory, focus will be laid on two different examples: one dynamic, in the outdoors (the Boario Terme Archeopark from Italy) and one experimental, held indoor (the reconstruction of the Neolithic sanctuary of Parta, Romania as part of a transdisciplinary academic course) and their impact on young generations. The conclusion of this study shows that the increasingly lower engagement of youth (students) in discovering and understanding history, archaeology, and heritage can be revived by entrepreneurial projects.

Keywords: archeopark, educational tourism, open air museum, Parta sanctuary, prehistory

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Authors: H. M. Alfrihidi, H.A. Albarakaty

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Flattening filter-free (FFF) photon beam radiotherapy has increased in the last decade, which is enabled by advancements in treatment planning systems and radiation delivery techniques like multi-leave collimators. FFF beams have higher dose rates, which reduces treatment time. On the other hand, FFF beams have a higher surface dose, which is due to the loss of beam hardening effect caused by the presence of the flatting filter (FF). The possibility of improving FFF beam quality using filters from low-z materials such as steel and aluminium (Al) was investigated using Monte Carlo (MC) simulations. The attenuation coefficient of low-z materials for low-energy photons is higher than that of high-energy photons, which leads to the hardening of the FFF beam and, consequently, a reduction in the surface dose. BEAMnrc user code, based on Electron Gamma Shower (EGSnrc) MC code, is used to simulate the beam of a 6 MV True-Beam linac. A phase-space (phosphor) file provided by Varian Medical Systems was used as a radiation source in the simulation. This phosphor file was scored just above the jaws at 27.88 cm from the target. The linac from the jaw downward was constructed, and radiation passing was simulated and scored at 100 cm from the target. To study the effect of low-z filters, steel and Al filters with a thickness of 1 cm were added below the jaws, and the phosphor file was scored at 100 cm from the target. For comparison, the FF beam was simulated using a similar setup. (BEAM Data Processor (BEAMdp) is used to analyse the energy spectrum in the phosphorus files. Then, the dose distribution resulting from these beams was simulated in a homogeneous water phantom using DOSXYZnrc. The dose profile was evaluated according to the surface dose, the lateral dose distribution, and the percentage depth dose (PDD). The energy spectra of the beams show that the FFF beam is softer than the FF beam. The energy peaks for the FFF and FF beams are 0.525 MeV and 1.52 MeV, respectively. The FFF beam's energy peak becomes 1.1 MeV using a steel filter, while the Al filter does not affect the peak position. Steel and Al's filters reduced the surface dose by 5% and 1.7%, respectively. The dose at a depth of 10 cm (D10) rises by around 2% and 0.5% due to using a steel and Al filter, respectively. On the other hand, steel and Al filters reduce the dose rate of the FFF beam by 34% and 14%, respectively. However, their effect on the dose rate is less than that of the tungsten FF, which reduces the dose rate by about 60%. In conclusion, filters from low-z material decrease the surface dose and increase the D10 dose, allowing for a high-dose delivery to deep tumors with a low skin dose. Although using these filters affects the dose rate, this effect is much lower than the effect of the FF.

Keywords: flattening filter free, monte carlo, radiotherapy, surface dose

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Authors: Gorkem Algan, Ilkay Ulusoy, Saban Gonul, Banu Turgut, Berker Bakbak

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Computer vision systems recently made a big leap thanks to deep neural networks. However, these systems require correctly labeled large datasets in order to be trained properly, which is very difficult to obtain for medical applications. Two main reasons for label noise in medical applications are the high complexity of the data and conflicting opinions of experts. Moreover, medical imaging datasets are commonly tiny, which makes each data very important in learning. As a result, if not handled properly, label noise significantly degrades the performance. Therefore, a label-noise-robust learning algorithm that makes use of the meta-learning paradigm is proposed in this article. The proposed solution is tested on retinopathy of prematurity (ROP) dataset with a very high label noise of 68%. Results show that the proposed algorithm significantly improves the classification algorithm's performance in the presence of noisy labels.

Keywords: deep learning, label noise, robust learning, meta-learning, retinopathy of prematurity

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Authors: Swarna Pundir, Prabuddha Hans

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As AI has already stepped into the daily life of human society, one cannot be ignorant about the data it collects and used it to provide a quality of services depending up on the individuals’ choices. It also helps in giving option for making decision Vs choice selection with a calculation based on the history of our search criteria. Over the past decade or so, the way Artificial Intelligence (AI) has impacted society is undoubtedly large.AI has changed the way we shop, the way we entertain and challenge ourselves, the way information is handled, and has automated some sections of our life. We have answered as to what AI is, but not why one may see it as useful. AI is useful because it is capable of learning and predicting outcomes, using Machine Learning (ML) and Deep Learning (DL) with the help of Artificial Neural Networks (ANN). AI can also be a system that can act like humans. One of the major impacts be Joblessness through automation via AI which is seen mostly in manufacturing sectors, especially in the routine manual and blue-collar occupations and those without a college degree. It raises some serious concerns about AI in regards of less employment, ethics in making moral decisions, Individuals privacy, human judgement’s, natural emotions, biased decisions, discrimination. So, the question is if an error occurs who will be responsible, or it will be just waved off as a “Machine Error”, with no one taking the responsibility of any wrongdoing, it is essential to form some rules for using the AI where both machines and humans are involved.

Keywords: AI, ML, DL, ANN

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Authors: Matthias Haenisch, Marc Godau, Julia Barreiro, Dominik Maxelon

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In times of ubiquitous digitalization and the increasing entanglement of humans and technologies in musical practices in the 21st century, it is to be asked, how popular musicians learn in the (post)digital Age. Against the backdrop of the increasing interest in transferring informal learning practices into formal settings of music education the interdisciplinary research association »MusCoDA – Musical Communities in the (Post)Digital Age« (University of Erfurt/University of Applied Sciences Clara Hoffbauer Potsdam, funded by the German Ministry of Education and Research, pursues the goal to derive an empirical model of collective songwriting practices from the study of informal lelearningf songwriters and bands that can be translated into pedagogical concepts for music education in schools. Drawing on concepts from Community of Musical Practice and Actor Network Theory, lelearnings considered not only as social practice and as participation in online and offline communities, but also as an effect of heterogeneous networks composed of human and non-human actors. Learning is not seen as an individual, cognitive process, but as the formation and transformation of actor networks, i.e., as a practice of assembling and mediating humans and technologies. Based on video stimulated recall interviews and videography of online and offline activities, songwriting practices are followed from the initial idea to different forms of performance and distribution. The data evaluation combines coding and mapping methods of Grounded Theory Methodology and Situational Analysis. This results in network maps in which both the temporality of creative practices and the material and spatial relations of human and technological actors are reconstructed. In addition, positional analyses document the power relations between the participants that structure the learning process of the field. In the area of online informal lelearninginitial key research findings reveal a transformation of the learning subject through the specific technological affordances of TikTok and Instagram and the accompanying changes in the learning practices of the corresponding online communities. Learning is explicitly shaped by the material agency of online tools and features and the social practices entangled with these technologies. Thus, any human online community member can be invited to directly intervene in creative decisions that contribute to the further compositional and structural development of songs. At the same time, participants can provide each other with intimate insights into songwriting processes in progress and have the opportunity to perform together with strangers and idols. Online Lelearnings characterized by an increase in social proximity, distribution of creative agency and informational exchange between participants. While it seems obvious that traditional notions not only of lelearningut also of the learning subject cannot be maintained, the question arises, how exactly the observed informal learning practices and the subject that emerges from the use of social media as online learning technologies can be transferred into contexts of formal learning

Keywords: informal learning, postdigitality, songwriting, actor-network theory, community of musical practice, social media, TikTok, Instagram, apps

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Authors: Azfar Adib

Abstract:

Like many other countries of the world, mobile internet has been playing a key role in the growth of internet subscriber base in Bangladesh. This study has attempted to identify particular behavioral or usage patterns of 2G mobile internet subscribers who were using the service of the topmost internet service provider (as well as the top mobile operator) of Bangladesh prior to the launching of 3G services (when 2G was fully dominant). It contains some comprehensive analysis carried on different info regarding 2G mobile internet subscribers, obtained from the operator’s own network insights.This is accompanied by the results of a survey conducted among 40 high-frequency users of this service.

Keywords: mobile internet, Symbian, Android, iPhone

Procedia PDF Downloads 442