Search results for: visual media and computer network etc

Authors: Juan Pablo Bertuzzi, Mauro Chiarella

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Employing a communication studies perspective and a socio-technological approach, this paper introduces a theoretical framework for understanding the concept of hybrid world; the avatarization phenomena; and the communicational archetype of co-hybridization. This analysis intends to make a contribution to future design of virtual reality experimental applications. Ultimately, this paper presents an ongoing research project that proposes the study of human-avatar interactions in digital educational environments, as well as an innovative reflection on inner digital communication. The aforementioned project presents the analysis of human-avatar interactions, through the development of an interactive experience in virtual reality. The goal is to generate an innovative communicational dimension that could reinforce the hypotheses presented throughout this paper. Being thought for its initial application in educational environments, the analysis and results of this research are dependent and have been prepared in regard of a meticulous planning of: the conception of a 3D digital platform; the interactive game objects; the AI or computer avatars; the human representation as hybrid avatars; and lastly, the potential of immersion, ergonomics and control diversity that can provide the virtual reality system and the game engine that were chosen. The project is divided in two main axes: The first part is the structural one, as it is mandatory for the construction of an original prototype. The 3D model is inspired by the physical space that belongs to an academic institution. The incorporation of smart objects, avatars, game mechanics, game objects, and a dialogue system will be part of the prototype. These elements have all the objective of gamifying the educational environment. To generate a continuous participation and a large amount of interactions, the digital world will be navigable both, in a conventional device and in a virtual reality system. This decision is made, practically, to facilitate the communication between students and teachers; and strategically, because it will help to a faster population of the digital environment. The second part is concentrated to content production and further data analysis. The challenge is to offer a scenario’s diversity that compels users to interact and to question their digital embodiment. The multipath narrative content that is being applied is focused on the subjects covered in this paper. Furthermore, the experience with virtual reality devices proposes users to experiment in a mixture of a seemingly infinite digital world and a small physical area of movement. This combination will lead the narrative content and it will be crucial in order to restrict user’s interactions. The main point is to stimulate and to grow in the user the need of his hybrid avatar’s help. By building an inner communication between user’s physicality and user’s digital extension, the interactions will serve as a self-guide through the gameworld. This is the first attempt to make explicit the avatarization phenomena and to further analyze the communicational archetype of co-hybridization. The challenge of the upcoming years will be to take advantage from these forms of generalized avatarization, in order to create awareness and establish innovative forms of hybridization.

Keywords: avatar, hybrid worlds, socio-technology, virtual reality

Procedia PDF Downloads 142

Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

Procedia PDF Downloads 64

Authors: Zhongmin Wang, Wudong Fan, Hengshan Zhang, Yimin Zhou

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In data-driven prognostic methods, the prediction accuracy of the estimation for remaining useful life of bearings mainly depends on the performance of health indicators, which are usually fused some statistical features extracted from vibrating signals. However, the existing health indicators have the following two drawbacks: (1) The differnet ranges of the statistical features have the different contributions to construct the health indicators, the expert knowledge is required to extract the features. (2) When convolutional neural networks are utilized to tackle time-frequency features of signals, the time-series of signals are not considered. To overcome these drawbacks, in this study, the method combining convolutional neural network with gated recurrent unit is proposed to extract the time-frequency image features. The extracted features are utilized to construct health indicator and predict remaining useful life of bearings. First, original signals are converted into time-frequency images by using continuous wavelet transform so as to form the original feature sets. Second, with convolutional and pooling layers of convolutional neural networks, the most sensitive features of time-frequency images are selected from the original feature sets. Finally, these selected features are fed into the gated recurrent unit to construct the health indicator. The results state that the proposed method shows the enhance performance than the related studies which have used the same bearing dataset provided by PRONOSTIA.

Keywords: continuous wavelet transform, convolution neural net-work, gated recurrent unit, health indicators, remaining useful life

Procedia PDF Downloads 133

Authors: Cathal Ffrench, Ryan Barrett, Mike Quayle

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It is accepted in social psychology that categorization leads to ingroup favoritism, without further thought given to the processes that may co-occur or even precede categorization. These categorizations move away from the conceptualization of the self as a unique social being toward an increasingly collective identity. Subsequently, many individuals derive much of their self-evaluations from these collective identities. The seminal literature on this topic argues that it is primarily categorization that evokes instances of ingroup favoritism. Apropos to these theories, we argue that categorization acts to enhance and further intergroup processes rather than defining them. More accurately, we propose categorization aids initial ingroup contact and this first contact is predictive of subsequent favoritism on individual and collective levels. This analysis focuses on Virtual Interaction APPLication (VIAPPL) based studies, a software interface that builds on the flaws of the original minimal group studies. The VIAPPL allows the exchange of tokens in an intra and inter-group manner. This token exchange is how we classified the first contact. The study involves binary longitudinal analysis to better understand the subsequent exchanges of individuals based on who they first interacted with. Studies were selected on the criteria of evidence of explicit first interactions and two-group designs. Our findings paint a compelling picture in support of a motivated contact hypothesis, which suggests that an individual’s first motivated contact toward another has strong predictive capabilities for future behavior. This contact can lead to habit formation and specific favoritism towards individuals where contact has been established. This has important implications for understanding how group conflict occurs, and how intra-group individual bias can develop.

Keywords: categorization, group dynamics, initial contact, minimal social networks, momentary contact

Procedia PDF Downloads 148

Authors: Jin Hwan Cheong, Mina Hwang, Myung Hoon Han, Je Il Ryu, Young ha Oh, Seong Ho Koh, Wu Duck Won, Byung Jin Ha

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Leucine-rich repeat-containing G-protein coupled receptor 5 (LGR5) has been reported to play critical roles in the proliferation of various cancer cells. However, the roles of LGR5 in brain tumors and the specific intracellular signaling proteins directly associated with it remain unknown. Expression of LGR5 was first measured in normal brain tissue, meningioma, and pituitary adenoma of humans. To identify the downstream signaling pathways of LGR5, siRNA-mediated knockdown of LGR5 was performed in SH-SY5Y neuroblastoma cells followed by proteomics analysis with 2-dimensional polyacrylamide gel electrophoresis (2D-PAGE). In addition, the expression of LGR5-associated proteins was evaluated in LGR5-inꠓhibited neuroblastoma cells and in human normal brain, meningioma, and pituitary adenoma tissue. Proteomics analysis showed 12 protein spots were significantly different in expression level (more than two-fold change) and subsequently identified by peptide mass fingerprinting. A protein association network was constructed from the 12 identified proteins altered by LGR5 knockdown. Direct and indirect interactions were identified among the 12 proteins. HSP 90-beta was one of the proteins whose expression was altered by LGR5 knockdown. Likewise, we observed decreased expression of proteins in the hnRNP subfamily following LGR5 knockdown. In addition, we have for the first time identified significantly higher hnRNP family expression in meningioma and pituitary adenoma compared to normal brain tissue. Taken together, LGR5 and its downstream sigꠓnaling play critical roles in neuroblastoma and brain tumors such as meningioma and pituitary adenoma.

Keywords: LGR5, neuroblastoma, meningioma, pituitary adenoma, hnRNP

Procedia PDF Downloads 56

Authors: Sanjay Adhikesaven

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Workplace accidents are a critical problem that causes many deaths, injuries, and financial losses. Climate change has a severe impact on industrial workers, partially caused by global warming. To reduce such casualties, it is important to proactively find unsafe environments where injuries could occur by detecting the use of personal protective equipment (PPE) and identifying unsafe activities. Thus, we propose an industrial workplace alerting and monitoring platform to detect PPE use and classify unsafe activity in group settings involving multiple humans and objects over a long period of time. Our proposed method is the first to analyze prolonged actions involving multiple people or objects. It benefits from combining pose estimation with PPE detection in one platform. Additionally, we propose the first open-source annotated data set with video data from industrial workplaces annotated with the action classifications and detected PPE. The proposed system can be implemented within the surveillance cameras already present in industrial settings, making it a practical and effective solution.

Keywords: computer vision, deep learning, workplace safety, automation

Procedia PDF Downloads 103

Authors: Jonas Hamann, Siavash Saki, Tobias Hagen

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Discretization of urban areas is a crucial aspect in many spatial analyses. The process of discretization of space into subspaces without overlaps and gaps is called tessellation. It helps understanding spatial space and provides a framework for analyzing geospatial data. Tessellation methods can be divided into two groups: regular tessellations and irregular tessellations. While regular tessellation methods, like squares-grids or hexagons-grids, are suitable for addressing pure geometry problems, they cannot take the unique characteristics of different subareas into account. However, irregular tessellation methods allow the border between the subareas to be defined more realistically based on urban features like a road network or Points of Interest (POI). Even though Python is one of the most used programming languages when it comes to spatial analysis, there is currently no library that combines different tessellation methods to enable users and researchers to compare different techniques. To close this gap, we are proposing TessPy, an open-source Python package, which combines all above-mentioned tessellation methods and makes them easily accessible to everyone. The core functions of TessPy represent the five different tessellation methods: squares, hexagons, adaptive squares, Voronoi polygons, and city blocks. By using regular methods, users can set the resolution of the tessellation which defines the finesse of the discretization and the desired number of tiles. Irregular tessellation methods allow users to define which spatial data to consider (e.g., amenity, building, office) and how fine the tessellation should be. The spatial data used is open-source and provided by OpenStreetMap. This data can be easily extracted and used for further analyses. Besides the methodology of the different techniques, the state-of-the-art, including examples and future work, will be discussed. All dependencies can be installed using conda or pip; however, the former is more recommended.

Keywords: geospatial data science, geospatial data analysis, tessellations, urban studies

Procedia PDF Downloads 128

Authors: Alicia Regodon Puyalto, Alfonso Garcia-Santos

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This article presents a method to analyze the use of indoor spaces based on data analytics obtained from inbuilt digital devices. The study uses the data generated by the in-place devices, such as smart locks, Wi-Fi routers, and electrical sensors, to gain additional insights on space occupancy, user behaviour, and comfort. Those devices, originally installed to facilitate remote operations, report data through the internet that the research uses to analyze information on human real-time use of spaces. Using an in-place Internet of Things (IoT) network enables a faster, more affordable, seamless, and scalable solution to analyze building interior spaces without incorporating external data collection systems such as sensors. The methodology is applied to a real case study of coliving, a residential building of 3000m², 7 floors, and 80 users in the centre of Madrid. The case study applies the method to classify IoT devices, assess, clean, and analyze collected data based on the analysis framework. The information is collected remotely, through the different platforms devices' platforms; the first step is to curate the data, understand what insights can be provided from each device according to the objectives of the study, this generates an analysis framework to be escalated for future building assessment even beyond the residential sector. The method will adjust the parameters to be analyzed tailored to the dataset available in the IoT of each building. The research demonstrates how human-centered data analytics can improve the future spatial design of indoor spaces.

Keywords: in-place devices, IoT, human-centred data-analytics, spatial design

Procedia PDF Downloads 197

Authors: Armend Kelmendi, Adnan Ahmeti

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The purpose of our study was to assess the impact of soccer in the overall wealth fare (education, health, and economic prosperity) of youth in Kosovo (age: 7-18). The research conducted measured a number of parameters (training methodologies, conditions, community leadership impact) in a sample consisting of 6 different football clubs’ academies across the country. Fifty (50) male and female football youngsters volunteered in this study. To generate more reliable results, the analysis was conducted with the help of a set of effective project management tools and techniques (Gantt chart, Logic Network, PERT chart, Work Breakdown Structure, and Budgeting Analysis). The interviewees were interviewed under a specific lens of categories (impact in education, health, and economic prosperity). A set of questions were asked i.e. what has football provided to you and the community you live in?; Did football increase your confidence and shaped your life for better?; What was the main reason you started training in football? The results generated explain how a single sport, namely that of football in Kosovo can make a huge social change, improving key social factors in a society. There was a considerable difference between the youth clubs as far as training conditions are concerned. The study found out that despite financial constraints, two out of six clubs managed to produce twice as more talented players that were introduced to professional primary league teams in Kosovo and Albania, including other soccer teams in the region, Europe, and Asia. The study indicates that better sports policy must be formulated and associated with important financial investments in soccer for it to be considered fruitful and beneficial for players of 18 plus years of age, namely professionals.

Keywords: youth, prosperity, conditions, investments, growth, free movement

Procedia PDF Downloads 242

Authors: Jana Soler Libran

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The primary aim of this paper is to analyze the relationship between power and knowledge suggested in Michel Foucault's theory. Taking into consideration the role of power in knowledge production, the goal is to evaluate to what extent genealogy can be presented as a practical method for epistemic resistance. To do so, the methodology used consists of a revision of Foucault’s literature concerning the topic discussed. In this sense, conceptual analysis is applied in order to understand the effect of the double dimension of power on knowledge production. In its negative dimension, power is conceived as an organ of repression, vetoing certain instances of knowledge considered deceitful. In opposition, in its positive dimension, power works as an organ of the production of truth by means of institutionalized discourses. This double declination of power leads to the first main findings of the present analysis: no truth or knowledge can lie outside power’s action, and power is constituted through accepted forms of knowledge. To second these statements, Foucaultian discourse formations are evaluated, presenting external exclusion procedures as paradigmatic practices to demonstrate how power creates and shapes the validity of certain epistemes. Thus, taking into consideration power’s mechanisms to produce and reproduce institutionalized truths, this paper accounts for the Foucaultian praxis of genealogy as a method to reveal power’s intention, instruments, and effects in the production of knowledge. In this sense, it is suggested to consider genealogy as a practice which, firstly, reveals what instances of knowledge are subjugated to power and, secondly, promotes aforementioned peripherical discourses as a form of epistemic resistance. In order to counterbalance these main theses, objections to Foucault’s work from Nancy Fraser, Linda Nicholson, Charles Taylor, Richard Rorty, Alvin Goldman, or Karen Barad are discussed. In essence, the understanding of the Foucaultian relationship between power and knowledge is essential to analyze how contemporary discourses are produced by both traditional institutions and new forms of institutionalized power, such as mass media or social networks. Therefore, Michel Foucault's practice of genealogy is relevant, not only for its philosophical contribution as a method to uncover the effects of power in knowledge production but also because it constitutes a valuable theoretical framework for political theory and sociological studies concerning the formation of societies and individuals in the contemporary world.

Keywords: epistemic resistance, Foucault’s genealogy, knowledge, power, truth

Procedia PDF Downloads 124

Authors: Francis Nanda Prakash Monteiro, Shyna Quadras, Tanush Shetty

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The association between human physique and morbidity and mortality resulting from coronary artery disease has been studied extensively over several decades. Multiple studies have also been done on the correlation between grade of atherosclerosis, coronary artery diseases and anthropometrical measurements. However, the number of autopsy-based studies drastically reduces this number. It has been suggested that while in living subjects, it would be expensive, difficult, and even harmful to subject them to imaging modalities like CT scans and procedures involving contrast media to study mild atherosclerosis, no such harm is encountered in study of autopsy cases. This autopsy-based study was aimed to correlate the anthropometric measurements and indices of obesity, such as waist circumference (WC), hip circumference (HC), body mass index (BMI) and waist hip ratio (WHR) with the degree of atherosclerosis in the right coronary artery (RCA), main branch of the left coronary artery (LCA) and the left anterior descending artery (LADA) in 95 South Indian origin victims of both the genders between the age of 18 years and 75 years. The grading of atherosclerosis was done according to criteria suggested by the American Heart Association. The study also analysed the correlation of the anthropometric measurements and indices of obesity with the number of coronaries affected with atherosclerosis in an individual. All the anthropometric measurements and the derived indices were found to be significantly correlated to each other in both the genders except for the age, which is found to have a significant correlation only with the WHR. In both the genders severe degree of atherosclerosis was commonly observed in LADA, followed by LCA and RCA. Grade of atherosclerosis in RCA is significantly related to the WHR in males. Grade of atherosclerosis in LCA and LADA is significantly related to the WHR in females. Significant relation was observed between grade of atherosclerosis in RCA and WC, and WHR, and between grade of atherosclerosis in LADA and HC in males. Significant relation was observed between grade of atherosclerosis in RCA and WC, and WHR, and between grade of atherosclerosis in LADA and HC in females. Anthropometric measurements/indices of obesity can be an effective means to identify high risk cases of atherosclerosis at an early stage that can be effective in reducing the associated cardiac morbidity and mortality. A person with anthropometric measurements suggestive of mild atherosclerosis can be advised to modify his lifestyle, along with decreasing his exposure to the other risk factors. Those with measurements suggestive of higher degree of atherosclerosis can be subjected to confirmatory procedures to start effective treatment.

Keywords: atherosclerosis, coronary artery disease, indices, obesity

Procedia PDF Downloads 66

Authors: Soumita Banerjee

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The State of West Bengal is mostly watered by innumerable rivers, and they are different in nature in both the northern and the southern part of the state. The southern part of West Bengal is mainly drained with the river Bhagirathi-Hooghly, and its major distributaries and tributaries have divided this major river basin into many subparts like the Ichamati-Bidyadhari, Pagla-Bansloi, Mayurakshi-Babla, Ajay, Damodar, Kangsabati Sub-basin to name a few. These rivers basically drain the Districts of Bankura, Burdwan, Hooghly, Nadia and Purulia, Birbhum, Midnapore, Murshidabad, North 24-Parganas, Kolkata, Howrah and South 24-Parganas. West Bengal has a huge number of flood-prone blocks in the southern part of the state of West Bengal, the responsible factors for flood situation are the shape and size of the catchment area, its steep gradient starting from plateau to flat terrain, the river bank erosion and its siltation, tidal condition especially in the lower Ganga Basin and very low maintenance of the embankments which are mostly used as communication links. Along with these factors, DVC (Damodar Valley Corporation) plays an important role in the generation (with the release of water) and controlling the flood situation. This year the whole Gangetic West Bengal is being flooded due to high intensity and long duration rainfall, and the release of water from the Durgapur Barrage As most of the rivers are interstate in nature at times floods also take place with release of water from the dams of the neighbouring states like Jharkhand. Other than Embankments, there is no such structural measures for combatting flood in West Bengal. This paper tries to analyse the reasons behind the flood situation this year especially with the help of climatic data collected from the Indian Metrological Department, flood related data from the Irrigation and Waterways Department, West Bengal and GPM (General Precipitation Measurement) data for rainfall analysis. Based on the threshold value derived from the calculation of the past available flood data, it is possible to predict the flood events which may occur in the near future and with the help of social media it can be spread out within a very short span of time to aware the mass. On a larger or a governmental scale, heightening the settlements situated on the either banks of the river can yield a better result than building up embankments.

Keywords: dam failure, embankments, flood, rainfall

Procedia PDF Downloads 225

Authors: Migael van Zyl, Stefanie Visser, Awelani Phaswana

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The electricity landscape in South Africa is characterized by frequent occurrences of loadshedding, a measure implemented by Eskom to manage electricity generation shortages by curtailing demand. Loadshedding, classified into stages ranging from 1 to 8 based on severity, involves the systematic rotation of power cuts across municipalities according to predefined schedules. However, this practice introduces distortions in recorded electricity demand, posing challenges to accurate forecasting essential for budgeting, network planning, and generation scheduling. Addressing this challenge requires the development of a methodology to quantify the impact of loadshedding and integrate it back into metered electricity demand data. Fortunately, comprehensive records of loadshedding impacts are maintained in a database, enabling the alignment of Loadshedding effects with hourly demand data. This adjustment ensures that forecasts accurately reflect true demand patterns, independent of loadshedding's influence, thereby enhancing the reliability of electricity supply management in South Africa. This paper presents a methodology for determining the hourly impact of load scheduling and subsequently adjusting historical demand data to account for it. Furthermore, two forecasting models are developed: one utilizing the original dataset and the other using the adjusted data. A comparative analysis is conducted to evaluate forecast accuracy improvements resulting from the adjustment process. By implementing this methodology, stakeholders can make more informed decisions regarding electricity infrastructure investments, resource allocation, and operational planning, contributing to the overall stability and efficiency of South Africa's electricity supply system.

Keywords: electricity demand forecasting, load shedding, demand side management, data science

Procedia PDF Downloads 61

Authors: Carolina S. Monteiro, Eugénia Pinto, Miguel A. Faria, Sara C. Cunha

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Rice (Oryza sativa) production plays a vital role in reducing hunger and poverty and assumes particular importance in low-income and developing countries. Rice is a sensitive plant, and production occurs strictly where suitable temperature and water conditions are found. Climatic changes are likely to affect worldwide, and some models have predicted increased temperatures, variations in atmospheric CO₂ concentrations and modification in precipitation patterns. Therefore, the ongoing climatic changes threaten rice production by increasing biotic and abiotic stress factors, and crops will grow in different environmental conditions in the following years. Around the world, the effects will be regional and can be detrimental or advantageous depending on the region. Mediterranean zones have been identified as possible hot spots, where dramatic temperature changes, modifications of CO₂ levels, and rainfall patterns are predicted. The actual estimated atmospheric CO₂ concentration is around 400 ppm, and it is predicted that it can reach up to 1000–1200 ppm, which can lead to a temperature increase of 2–4 °C. Alongside, rainfall patterns are also expected to change, with more extreme wet/dry episodes taking place. As a result, it could increase the migration of pathogens, and a shift in the occurrence of mycotoxins, concerning their types and concentrations, is expected. Mycotoxigenic spoilage fungi can colonize the crops and be present in all rice food chain supplies, especially Penicillium species, mainly resulting in ochratoxin A (OTA) contamination. In this scenario, the objectives of the present study are evaluating the effect of temperature (20 vs. 25 °C), CO₂ (400 vs. 1000 ppm), and water stress (0.93 vs 0.95 water activity) on growth and OTA production by a Penicillium nordicum strain in vitro on rice-based media and when colonizing layers of raw rice. Results demonstrate the effect of temperature, CO₂ and drought on the OTA production in a rice-based environment, thus contributing to the development of mycotoxins predictive models in climate change scenarios. As a result, improving mycotoxins' surveillance and monitoring systems, whose occurrence can be more frequent due to climatic changes, seems relevant and necessary. The development of prediction models for hazard contaminants presents in foods highly sensitive to climatic changes, such as mycotoxins, in the highly probable new agricultural scenarios is of paramount importance.

Keywords: climate changes, ochratoxin A, penicillium, rice

Procedia PDF Downloads 69

Authors: Carla Silva

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Recent development of information and communication technology enables us to acquire, collect, analyse data in various fields of socioeconomic – technological systems. Along with the increase of economic globalization and the evolution of information technology, data mining has become an important approach for economic data analysis. As a result, there has been a critical need for automated approaches to effective and efficient usage of massive amount of educational data, in order to support institutions to a strategic planning and investment decision-making. In this article, we will address data from several different perspectives and define the applied data to sciences. Many believe that 'big data' will transform business, government, and other aspects of the economy. We discuss how new data may impact educational policy and educational research. Large scale administrative data sets and proprietary private sector data can greatly improve the way we measure, track, and describe educational activity and educational impact. We also consider whether the big data predictive modeling tools that have emerged in statistics and computer science may prove useful in educational and furthermore in economics. Finally, we highlight a number of challenges and opportunities for future research.

Keywords: data mining, research analysis, investment decision-making, educational research

Procedia PDF Downloads 358

Authors: Mohamed Zellagui, Heba Ahmed Hassan

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This paper proposes a new approach for the calculation of short-circuit parameters in the presence of Pulse Width Modulated based Series Compensator (PWMSC). PWMSC is a newly Flexible Alternating Current Transmission System (FACTS) device that can modulate the impedance of a transmission line through applying a variation to the duty cycle (D) of a train of pulses with fixed frequency. This results in an improvement of the system performance as it provides virtual compensation of distribution line impedance by injecting controllable apparent reactance in series with the distribution line. This controllable reactance can operate in both capacitive and inductive modes and this makes PWMSC highly effective in controlling the power flow and increasing system stability in the system. The purpose of this work is to study the impact of fault resistance (RF) which varies between 0 to 30 Ω on the fault current calculations in case of a ground fault and a fixed fault location. The case study is for a medium voltage (MV) Algerian distribution line which is compensated by PWMSC in the 30 kV Algerian distribution power network. The analysis is based on symmetrical components method which involves the calculations of symmetrical components of currents and voltages, without and with PWMSC in both cases of maximum and minimum duty cycle value for capacitive and inductive modes. The paper presents simulation results which are verified by the theoretical analysis.

Keywords: pulse width modulated series compensator (pwmsc), duty cycle, distribution line, short-circuit calculations, ground fault, symmetrical components method

Procedia PDF Downloads 500

Authors: A. F. Alves, L. Schmidt, J. Ferrao

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Portugal is one of the more vulnerable European countries to the impacts of climate change. These include: temperature increase; coastal sea level rise; desertification and drought in the countryside; and frequent and intense extreme weather events. Hence, adaptation strategies to climate change are of great importance. This is what was addressed by ClimAdaPT.Local. This policy-oriented project had the main goal of developing 26 Municipal Adaptation Strategies for Climate Change, through the identification of local specific present and future vulnerabilities, the training of municipal officials, and the engagement of local communities. It is intended to be replicated throughout the whole territory and to stimulate the creation of a national network of local adaptation in Portugal. Supported by methodologies and tools specifically developed for this project, our paper is based on the surveys, training and stakeholder engagement workshops implemented at municipal level. In an 'adaptation-as-learning' process, these tools functioned as a social-learning platform and an exercise in knowledge and policy co-production. The results allowed us to explore the nature of local vulnerabilities and the exposure of gaps in the context of reappraisal of both future climate change adaptation opportunities and possible dysfunctionalities in the governance arrangements of municipal Portugal. Development issues are highlighted when we address the sectors and social groups that are both more sensitive and more vulnerable to the impacts of climate change. We argue that a pluralistic dialogue and a common framing can be established between them, with great potential for transformational adaptation. Observed climate change, present-day climate variability and future expectations of change are great societal challenges which should be understood in the context of the sustainable development agenda.

Keywords: adaptation, ClimAdaPT.Local, climate change, Portugal, sustainable development

Procedia PDF Downloads 196

Authors: Damou Mehdi, Nouri Keltoum, Feham Mohammed, Khazini Mohammed, Bouazza Tayb Habibi Chawki

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The Half mode SIW filter is treated by two softwares (HFSS (High Frequency Structure Simulator) and CST (Computer Simulation Technology)). The filter HMSIW has a very simple structure and a very compact size. The simulated results by CST are presented and compared with the results simulated by a high-frequency structure simulator. Good agreement between the simulated CST and simulated results by HFSS is observed. By cascading two of them according to design requirement, a X-band bandpass filter is designed and simulated to meet compact size, low insertion loss, good return loss as well as second harmonic suppression. As an example, we designed the proposed HMSIW filter at X band by HFSS. The filter has a pass-band from 7.3 GHz to 9.8 GHz, and its relative operating fraction bandwidth is 29.5 %. There are one transmission zeros are located at 14.4 GHz.

Keywords: substrate integrated waveguide, filter, HMSIW, defected ground structures (DGS), simulation BPF

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Authors: Atefeh Omidkhah, Mohammadreza Bemanian

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The issue of way-finding earmarks a wide range of literature in architecture and despite the 50 year background of way-finding studies, it still lacks a comprehensive theory for indoor settings. Way-finding has a notable role in emergency evacuation as well. People in the panic situation of a fire emergency need to find the safe egress route correctly and in as minimum time as possible. In this regard the parameters of an appropriate way-finding are mentioned in the evacuation related researches albeit scattered. This study reviews the fire safety related literature to extract a way-finding related framework for architectural purposes of the design of a safe evacuation route. In this regard a research trend review in addition with applied methodological approaches review is conducted. Then by analyzing eight original researches related to way-finding parameters in fire evacuation, main parameters that affect way-finding in emergency situation of a fire incident are extracted and a framework was developed based on them. Results show that the issues related to exit route and emergency evacuation can be chased in task oriented studies of way-finding. This research trend aims to access a high-level framework and in the best condition a theory that has an explanatory capability to define differences in way-finding in indoor/outdoor settings, complex/simple buildings and different building types or transitional spaces. The methodological advances demonstrate the evacuation way-finding researches in line with three approaches that the latter one is the most up-to-date and precise method to research this subject: real actors and hypothetical stimuli as in evacuation experiments, hypothetical actors and stimuli as in agent-based simulations and real actors and semi-real stimuli as in virtual reality environment by adding multi-sensory simulation. Findings on data-mining of 8 sample of original researches in way-finding in evacuation indicate that emergency way-finding design of a building should consider two level of space cognition problems in the time of emergency and performance consequences of them in the built environment. So four major classes of problems in way-finding which are visual information deficiency, confusing layout configuration, improper navigating signage and demographic issues had been defined and discussed as the main parameters that should be provided with solutions in design and interior of a building. In the design phase of complex buildings, which face more reported problem in way-finding, it is important to consider the interior components regarding to the building type of occupancy and behavior of its occupants and determine components that tend to become landmarks and set the architectural features of egress route in line with the directions that they navigate people. Research on topological cognition of environmental and its effect on way-finding task in emergency evacuation is proposed for future.

Keywords: architectural design, egress route, way-finding, fire safety, evacuation

Procedia PDF Downloads 174

Authors: Zhanna Yermekova, Sergey Roslyakov

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Solution combustion synthesis (SCS) is the unique method which multiple times has proved itself as an effective and efficient approach for the versatile synthesis of a variety of materials. It has significant advantages such as relatively simple handling process, high rates of product synthesis, mixing of the precursors on a molecular level, and fabrication of the nanoproducts as a result. Nowadays, an overwhelming majority of solution combustion investigations performed through the volume combustion synthesis (VCS) where the entire liquid precursor is heated until the combustion self-initiates throughout the volume. Less amount of the experiments devoted to the steady-state self-propagating mode of SCS. Under the beforementioned regime, the precursor solution is dried until the gel-like media, and later on, the gel substance is locally ignited. In such a case, a combustion wave propagates in a self-sustaining mode as in conventional solid combustion synthesis. Even less attention is given to the impregnated active layer (IAL) mode of solution combustion. An IAL approach to the synthesis is implying that the solution combustion of the precursors should be initiated on the surface of the third chemical or inside the third substance. This work is aiming to emphasize an underestimated role of the impregnated active layer mode of the solution combustion synthesis for the fundamental studies of the combustion mechanisms. It also serves the purpose of popularizing the technical terms and clarifying the difference between them. In order to do so, the solution combustion synthesis of γ-FeNi (PDF#47-1417) alloy has been accomplished within short (seconds) one-step reaction of metal precursors with hexamethylenetetramine (HTMA) fuel. An idea of the special role of the Ni in a process of alloy formation was suggested and confirmed with the particularly organized set of experiments. The first set of experiments were conducted in a conventional steady-state self-propagating mode of SCS. An alloy was synthesized as a single monophasic product. In two other experiments, the synthesis was divided into two independent processes which are possible under the IAL mode of solution combustion. The sequence of the process was changed according to the equations which are describing an Experiment A and B below: Experiment A: Step 1. Fe(NO₃)₃*9H₂O + HMTA = FeO + gas products; Step 2. FeO + Ni(NO₃)₂*6H₂O + HMTA = Ni + FeO + gas products; Experiment B: Step 1. Ni(NO₃)₂*6H₂O + HMTA = Ni + gas products; Step 2. Ni + Fe(NO₃)₃*9H₂O + HMTA = Fe₃Ni₂+ traces (Ni + FeO). Based on the IAL experiment results, one can see that combustion of the Fe(NO₃)₃9H₂O on the surface of the Ni is leading to the alloy formation while presence of the already formed FeO does not affect the Ni(NO₃)₂*6H₂O + HMTA reaction in any way and Ni is the main product of the synthesis.

Keywords: alloy, hexamethylenetetramine, impregnated active layer mode, mechanism, solution combustion synthesis

Procedia PDF Downloads 135

Authors: Bhat Geetalaxmi Jairam, D. V. Ashoka

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Wireless Sensor Networks are used in many applications to collect sensed data from different sources. Sensed data has to be delivered through sensors wireless interface using multi-hop communication towards the sink. The data collection in wireless sensor networks consumes energy. Energy consumption is the major constraints in WSN .Reducing the energy consumption while increasing the amount of generated data is a great challenge. In this paper, we have implemented two data gathering protocols with multiple mobile sinks/elements to collect data from sensor nodes. First, is Energy-Efficient Data Gathering with Tour Length-Constrained Mobile Elements in Wireless Sensor Networks (EEDG), in which mobile sinks uses vehicle routing protocol to collect data. Second is An Intelligent Agent-based Routing Structure for Mobile Sinks in WSNs (IAR), in which mobile sinks uses prim’s algorithm to collect data. Authors have implemented concepts which are common to both protocols like deployment of mobile sinks, generating visiting schedule, collecting data from the cluster member. Authors have compared the performance of both protocols by taking statistics based on performance parameters like Delay, Packet Drop, Packet Delivery Ratio, Energy Available, Control Overhead. Authors have concluded this paper by proving EEDG is more efficient than IAR protocol but with few limitations which include unaddressed issues likes Redundancy removal, Idle listening, Mobile Sink’s pause/wait state at the node. In future work, we plan to concentrate more on these limitations to avail a new energy efficient protocol which will help in improving the life time of the WSN.

Keywords: aggregation, consumption, data gathering, efficiency

Procedia PDF Downloads 497

Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The problem of Dyslexia and Dysgraphia, two learning disabilities that affect reading and writing abilities, respectively, is a major concern for the educational system. Due to the complexity and uniqueness of the Sinhala language, these conditions are especially difficult for children who speak it. The traditional risk detection methods for Dyslexia and Dysgraphia frequently rely on subjective assessments, making it difficult to cover a wide range of risk detection and time-consuming. As a result, diagnoses may be delayed and opportunities for early intervention may be lost. The project was approached by developing a hybrid model that utilized various deep learning techniques for detecting risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16 and YOLOv8 were integrated to detect the handwriting issues, and their outputs were fed into an MLP model along with several other input data. The hyperparameters of the MLP model were fine-tuned using Grid Search CV, which allowed for the optimal values to be identified for the model. This approach proved to be effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention of these conditions. The Resnet50 model achieved an accuracy of 0.9804 on the training data and 0.9653 on the validation data. The VGG16 model achieved an accuracy of 0.9991 on the training data and 0.9891 on the validation data. The MLP model achieved an impressive training accuracy of 0.99918 and a testing accuracy of 0.99223, with a loss of 0.01371. These results demonstrate that the proposed hybrid model achieved a high level of accuracy in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, Dyslexia, Dysgraphia, deep learning, learning disabilities, data science

Procedia PDF Downloads 114

Authors: Dengyu You, Alireza Kashani

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This study explores the potential of 3D concrete printing in manufacturing prefabricated staircases. The applications of 3D concrete printing in large-scale construction could enhance the industry’s implementation of the Industry 4.0 concept. In addition, the current global challenge is to achieve Net Zero Emissions by 2050. Innovation in the construction industry could potentially speed up achieving this target. The 3D printing technology offers a possible solution that reduces cement usage, minimises framework wastes, and is capable of manufacturing complex structures. The performance of the 3D concrete printed lightweight staircase needs to be evaluated. In this study, the staircase is designed using computer-aided technologies, fabricated by 3D concrete printing technologies, and tested with Australian Standard (AS 1657-2018 Fixed platforms, walkways, stairways, and ladders – design, construction, and installation) under a laboratory environment. The experiment results will be further compared with the FEM analysis. The results indicate that 3D concrete printing is capable of fast production, reducing material usage, and is highly automotive, which meets the industry’s future development goal.

Keywords: concrete 3D printing, staircase, sustainability, automation

Procedia PDF Downloads 105

Authors: K. Adu Michael, K. Alese Boniface

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Developing a reliable and sustainable software products is today a big challenge among up–coming software developers in Nigeria. The inability to develop a comprehensive problem statement needed to execute proper requirements engineering process is missing. The need to describe the ‘what’ of a system in one document, written in a natural language is a major step in the overall process of Software Engineering. Requirements Engineering is a process use to discover, analyze and validate system requirements. This process is needed in reducing software errors at the early stage of the development of software. The importance of each of the steps in Requirements Engineering is clearly explained in the context of using detailed problem statement from client/customer to get an overview of an existing system along with expectations from the new system. This paper elicits inadequate Requirements Engineering principle as the major cause of poor software development in developing nations using a case study of final year computer science students of a tertiary-education institution in Nigeria.

Keywords: client/customer, problem statement, requirements engineering, software developers

Procedia PDF Downloads 406

Authors: Umar Albalawi, Sang C. Suh, Jinoh Kim

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As internet continues to expand its usage with an enormous number of applications, cyber-threats have significantly increased accordingly. Thus, accurate detection of malicious traffic in a timely manner is a critical concern in today’s Internet for security. One approach for intrusion detection is to use Machine Learning (ML) techniques. Several methods based on ML algorithms have been introduced over the past years, but they are largely limited in terms of detection accuracy and/or time and space complexity to run. In this work, we present a novel method for intrusion detection that incorporates a set of supervised learning algorithms. The proposed technique provides high accuracy and outperforms existing techniques that simply utilizes a single learning method. In addition, our technique relies on partial flow information (rather than full information) for detection, and thus, it is light-weight and desirable for online operations with the property of early identification. With the mid-Atlantic CCDC intrusion dataset publicly available, we show that our proposed technique yields a high degree of detection rate over 99% with a very low false alarm rate (0.4%).

Keywords: intrusion detection, supervised learning, traffic classification, computer networks

Procedia PDF Downloads 350

Authors: Alec Wells, Aminu Bello Usman, Justin McKeown

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The growing usage of smart speakers raises many privacy and trust concerns compared to other technologies such as smart phones and computers. In this study, a proxy measure of trust is used to gauge users’ opinions on three different technologies based on an empirical study, and to understand which technology most people are most likely to trust. The collected data were analysed using the Kruskal-Wallis H test to determine the statistical differences between the users’ trust level of the three technologies: smart speaker, computer and smart phone. The findings of the study revealed that despite the wide acceptance, ease of use and reputation of smart speakers, people find it difficult to trust smart speakers with their sensitive information via the Direct Voice Input (DVI) and would prefer to use a keyboard or touchscreen offered by computers and smart phones. Findings from this study can inform future work on users’ trust in technology based on perceived ease of use, reputation, perceived credibility and risk of using technologies via DVI.

Keywords: direct voice input, risk, security, technology, trust

Procedia PDF Downloads 191

Authors: Zouhair Haddi, Stephane Delliaux, Jean-Francois Pons, Ismail Kechaf, Jean-Claude De Haro, Mustapha Ouladsine

Abstract:

Atrial fibrillation (AF) has been considered as the most common cardiac arrhythmia, and a major public health burden associated with significant morbidity and mortality. Nowadays, telemedical approaches targeting cardiac outpatients situate AF among the most challenged medical issues. The automatic, early, and fast AF detection is still a major concern for the healthcare professional. Several algorithms based on univariate analysis have been developed to detect atrial fibrillation. However, the published results do not show satisfactory classification accuracy. This work was aimed at resolving this shortcoming by proposing multivariate data analysis methods for automatic AF detection. Four publicly-accessible sets of clinical data (AF Termination Challenge Database, MIT-BIH AF, Normal Sinus Rhythm RR Interval Database, and MIT-BIH Normal Sinus Rhythm Databases) were used for assessment. All time series were segmented in 1 min RR intervals window and then four specific features were calculated. Two pattern recognition methods, i.e., Principal Component Analysis (PCA) and Learning Vector Quantization (LVQ) neural network were used to develop classification models. PCA, as a feature reduction method, was employed to find important features to discriminate between AF and Normal Sinus Rhythm. Despite its very simple structure, the results show that the LVQ model performs better on the analyzed databases than do existing algorithms, with high sensitivity and specificity (99.19% and 99.39%, respectively). The proposed AF detection holds several interesting properties, and can be implemented with just a few arithmetical operations which make it a suitable choice for telecare applications.

Keywords: atrial fibrillation, multivariate data analysis, automatic detection, telemedicine

Procedia PDF Downloads 268

Authors: N. D. Iswarya, M. A. Maluk Mohamed, N. Vijaya

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Grid is infrastructure that allows the deployment of distributed data in large size from multiple locations to reach a common goal. Scheduling data intensive applications becomes challenging as the size of data sets are very huge in size. Only two solutions exist in order to tackle this challenging issue. First, computation which requires huge data sets to be processed can be transferred to the data site. Second, the required data sets can be transferred to the computation site. In the former scenario, the computation cannot be transferred since the servers are storage/data servers with little or no computational capability. Hence, the second scenario can be considered for further exploration. During scheduling, transferring huge data sets from one site to another site requires more network bandwidth. In order to mitigate this issue, this work focuses on incorporating cognitive science in scheduling. Cognitive Science is the study of human brain and its related activities. Current researches are mainly focused on to incorporate cognitive science in various computational modeling techniques. In this work, the problem solving approach of human brain is studied and incorporated during the data intensive scheduling in grid environments. Here, a cognitive engine is designed and deployed in various grid sites. The intelligent agents present in CE will help in analyzing the request and creating the knowledge base. Depending upon the link capacity, decision will be taken whether to transfer data sets or to partition the data sets. Prediction of next request is made by the agents to serve the requesting site with data sets in advance. This will reduce the data availability time and data transfer time. Replica catalog and Meta data catalog created by the agents assist in decision making process.

Keywords: data grid, grid workflow scheduling, cognitive artificial intelligence

Procedia PDF Downloads 394

Authors: Bambang Novianto, Rizal Aditya Herdianto, Raphael Bianco Huwae, Afifah, Alfonso Brolin Sihite, Rudi Lumanto

Abstract:

The mobile banking application is a type of mobile application that is growing rapidly. This is caused by the ease of service and time savings in making transactions. On the other hand, this certainly provides a challenge in security issues. The use of mobile banking can not be separated from cyberattacks that may occur which can result the theft of sensitive information or financial loss. The financial loss and the theft of sensitive information is the most avoided thing because besides harming the user, it can also cause a loss of customer trust in a bank. Cyberattacks that are often carried out against mobile applications are phishing, hacking, theft, misuse of data, etc. Cyberattack can occur when a vulnerability is successfully exploited. OWASP mobile Top 10 has recorded as many as 10 vulnerabilities that are most commonly found in mobile applications. In the others, android permissions also have the potential to cause vulnerabilities. Therefore, an overview of the profile of the mobile banking application becomes an urgency that needs to be known. So that it is expected to be a consideration of the parties involved for improving security. In this study, an experiment has been conducted to capture the profile of the mobile banking applications in Indonesia based on android permission and OWASP mobile top 10 2016. The results show that there are six basic vulnerabilities based on OWASP Mobile Top 10 that are most commonly found in mobile banking applications in Indonesia, i.e. M1:Improper Platform Usage, M2:Insecure Data Storage, M3:Insecure Communication, M5:Insufficient Cryptography, M7:Client Code Quality, and M9:Reverse Engineering. The most permitted android permissions are the internet, status network access, and telephone read status.

Keywords: mobile banking application, OWASP mobile top 10 2016, android permission, sensitive information, financial loss

Procedia PDF Downloads 141

Authors: Brian Kozak, Ryan Ferguson, Evan Hockeridge

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Aerospace engineering and aeronautical engineering students studying propulsion often learn about propellers and their importance in aviation propulsion. In order to reinforce concepts introduced in the classroom, laboratory projects are used. However, to test a full scale propeller, an engine mounted on a test stand must be used. This engine needs to be enclosed in a test cell for appropriated safety requirements, is expensive to operate, and requires a significant amount of time to change propellers. In order to decrease costs and time requirements, the authors designed and built an electric motor powered desktop Arduino controlled test stand. This test stand is used to enhance student understanding of propeller size and pitch on thrust. The test stand can accommodate propellers up to 25 centimeters in diameter. The code computer allowed for the motor speed to be increased or decreased by 1% per second. Outputs that are measured are thrust, motor rpm, amperes, voltage, and motor temperature. These data are exported as a .CVS file and can be imported into a graphing program for data analysis.

Keywords: Arduino, Laboratory Project, Test stand, Propeller

Procedia PDF Downloads 219