Search results for: left ventricular function
2459 Optimization of Gold Adsorption from Aqua-Regia Gold Leachate Using Baggase Nanoparticles
Authors: Oluwasanmi Teniola, Abraham Adeleke, Ademola Ibitoye, Moshood Shitu
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To establish an economical and efficient process for the recovery of gold metal from refractory gold ore obtained from Esperando axis of Osun state Nigeria, the adsorption of gold (III) from aqua reqia leached solution of the ore using bagasse nanoparticles has been studied under various experimental variables using batch technique. The extraction percentage of gold (III) on the prepared bagasse nanoparticles was determined from its distribution coefficients as a function of solution pH, contact time, adsorbent, adsorbate concentrations, and temperature. The rate of adsorption of gold (III) on the prepared bagasse nanoparticles is dependent on pH, metal concentration, amount of adsorbate, stirring rate, and temperature. The adsorption data obtained fit into the Langmuir and Freundlich equations. Three different temperatures were used to determine the thermodynamic parameters of the adsorption of gold (III) on bagasse nanoparticles. The heat of adsorption was measured to be a positive value ΔHo = +51.23kJ/mol, which serves as an indication that the adsorption of gold (III) on bagasse nanoparticles is endothermic. Also, the negative value of ΔGo = -0.6205 kJ/mol at 318K shows the spontaneity of the process. As the temperature was increased, the value of ΔGo becomes more negative, indicating that an increase in temperature favors the adsorption process. With the application of optimal adsorption variables, the adsorption capacity of gold was 0.78 mg/g of the adsorbent, out of which 0.70 mg of gold was desorbed with 0.1 % thiourea solution.Keywords: adsorption, bagasse, extraction, nanoparticles, recovery
Procedia PDF Downloads 1542458 Thermal and Caloric Imperfections Effect on the Supersonic Flow Parameters with Application for Air in Nozzles
Authors: Merouane Salhi, Toufik Zebbiche, Omar Abada
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When the stagnation pressure of perfect gas increases, the specific heat and their ratio do not remain constant anymore and start to vary with this pressure. The gas does not remain perfect. Its state equation change and it becomes a real gas. In this case, the effects of molecular size and inter molecular attraction forces intervene to correct the state equation. The aim of this work is to show and discuss the effect of stagnation pressure on supersonic thermo dynamical, physical and geometrical flow parameters, to find a general case for real gas. With the assumptions that Berthelot’s state equation accounts for molecular size and inter molecular force effects, expressions are developed for analyzing supersonic flow for thermally and calorically imperfect gas lower than the dissociation molecules threshold. The designs parameters for supersonic nozzle like thrust coefficient depend directly on stagnation parameters of the combustion chamber. The application is for air. A computation of error is made in this case to give a limit of perfect gas model compared to real gas model.Keywords: supersonic flow, real gas model, Berthelot’s state equation, Simpson’s method, condensation function, stagnation pressure
Procedia PDF Downloads 5242457 A Technique for Image Segmentation Using K-Means Clustering Classification
Authors: Sadia Basar, Naila Habib, Awais Adnan
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The paper presents the Technique for Image Segmentation Using K-Means Clustering Classification. The presented algorithms were specific, however, missed the neighboring information and required high-speed computerized machines to run the segmentation algorithms. Clustering is the process of partitioning a group of data points into a small number of clusters. The proposed method is content-aware and feature extraction method which is able to run on low-end computerized machines, simple algorithm, required low-quality streaming, efficient and used for security purpose. It has the capability to highlight the boundary and the object. At first, the user enters the data in the representation of the input. Then in the next step, the digital image is converted into groups clusters. Clusters are divided into many regions. The same categories with same features of clusters are assembled within a group and different clusters are placed in other groups. Finally, the clusters are combined with respect to similar features and then represented in the form of segments. The clustered image depicts the clear representation of the digital image in order to highlight the regions and boundaries of the image. At last, the final image is presented in the form of segments. All colors of the image are separated in clusters.Keywords: clustering, image segmentation, K-means function, local and global minimum, region
Procedia PDF Downloads 3762456 High Throughput Virtual Screening against ns3 Helicase of Japanese Encephalitis Virus (JEV)
Authors: Soma Banerjee, Aamen Talukdar, Argha Mandal, Dipankar Chaudhuri
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Japanese Encephalitis is a major infectious disease with nearly half the world’s population living in areas where it is prevalent. Currently, treatment for it involves only supportive care and symptom management through vaccination. Due to the lack of antiviral drugs against Japanese Encephalitis Virus (JEV), the quest for such agents remains a priority. For these reasons, simulation studies of drug targets against JEV are important. Towards this purpose, docking experiments of the kinase inhibitors were done against the chosen target NS3 helicase as it is a nucleoside binding protein. Previous efforts regarding computational drug design against JEV revealed some lead molecules by virtual screening using public domain software. To be more specific and accurate regarding finding leads, in this study a proprietary software Schrödinger-GLIDE has been used. Druggability of the pockets in the NS3 helicase crystal structure was first calculated by SITEMAP. Then the sites were screened according to compatibility with ATP. The site which is most compatible with ATP was selected as target. Virtual screening was performed by acquiring ligands from databases: KinaseSARfari, KinaseKnowledgebase and Published inhibitor Set using GLIDE. The 25 ligands with best docking scores from each database were re-docked in XP mode. Protein structure alignment of NS3 was performed using VAST against MMDB, and similar human proteins were docked to all the best scoring ligands. The low scoring ligands were chosen for further studies and the high scoring ligands were screened. Seventy-three ligands were listed as the best scoring ones after performing HTVS. Protein structure alignment of NS3 revealed 3 human proteins with RMSD values lesser than 2Å. Docking results with these three proteins revealed the inhibitors that can interfere and inhibit human proteins. Those inhibitors were screened. Among the ones left, those with docking scores worse than a threshold value were also removed to get the final hits. Analysis of the docked complexes through 2D interaction diagrams revealed the amino acid residues that are essential for ligand binding within the active site. Interaction analysis will help to find a strongly interacting scaffold among the hits. This experiment yielded 21 hits with the best docking scores which could be investigated further for their drug like properties. Aside from getting suitable leads, specific NS3 helicase-inhibitor interactions were identified. Selection of Target modification strategies complementing docking methodologies which can result in choosing better lead compounds are in progress. Those enhanced leads can lead to better in vitro testing.Keywords: antivirals, docking, glide, high-throughput virtual screening, Japanese encephalitis, ns3 helicase
Procedia PDF Downloads 2302455 Designing a Patient Monitoring System Using Cloud and Semantic Web Technologies
Authors: Chryssa Thermolia, Ekaterini S. Bei, Stelios Sotiriadis, Kostas Stravoskoufos, Euripides G. M. Petrakis
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Moving into a new era of healthcare, new tools and devices are developed to extend and improve health services, such as remote patient monitoring and risk prevention. In this concept, Internet of Things (IoT) and Cloud Computing present great advantages by providing remote and efficient services, as well as cooperation between patients, clinicians, researchers and other health professionals. This paper focuses on patients suffering from bipolar disorder, a brain disorder that belongs to a group of conditions called effective disorders, which is characterized by great mood swings.We exploit the advantages of Semantic Web and Cloud Technologies to develop a patient monitoring system to support clinicians. Based on intelligently filtering of evidence-knowledge and individual-specific information we aim to provide treatment notifications and recommended function tests at appropriate times or concluding into alerts for serious mood changes and patient’s non-response to treatment. We propose an architecture, as the back-end part of a cloud platform for IoT, intertwining intelligence devices with patients’ daily routine and clinicians’ support.Keywords: bipolar disorder, intelligent systems patient monitoring, semantic web technologies, healthcare
Procedia PDF Downloads 5092454 Modified Plastic-Damage Model for FRP-Confined Repaired Concrete Columns
Authors: I. A Tijani, Y. F Wu, C.W. Lim
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Concrete Damaged Plasticity Model (CDPM) is capable of modeling the stress-strain behavior of confined concrete. Nevertheless, the accuracy of the model largely depends on its parameters. To date, most research works mainly focus on the identification and modification of the parameters for fiber reinforced polymer (FRP) confined concrete prior to damage. And, it has been established that the FRP-strengthened concrete behaves differently to FRP-repaired concrete. This paper presents a modified plastic damage model within the context of the CDPM in ABAQUS for modelling of a uniformly FRP-confined repaired concrete under monotonic loading. The proposed model includes infliction damage, elastic stiffness, yield criterion and strain hardening rule. The distinct feature of damaged concrete is elastic stiffness reduction; this is included in the model. Meanwhile, the test results were obtained from a physical testing of repaired concrete. The dilation model is expressed as a function of the lateral stiffness of the FRP-jacket. The finite element predictions are shown to be in close agreement with the obtained test results of the repaired concrete. It was observed from the study that with necessary modifications, finite element method is capable of modeling FRP-repaired concrete structures.Keywords: Concrete, FRP, Damage, Repairing, Plasticity, and Finite element method
Procedia PDF Downloads 1372453 Climate Change, Women's Labour Markets and Domestic Work in Mexico
Authors: Luis Enrique Escalante Ochoa
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This paper attempts to assess the impacts of Climate change (CC) on inequalities in the labour market. CC will have the most serious effects on some vulnerable economic sectors, such as agriculture, livestock or tourism, but also on the most vulnerable population groups. The objective of this research is to evaluate the impact of CC on the labour market and particularly on Mexican women. Influential documents such as the synthesis reports produced by the Intergovernmental Panel on Climate Change (IPCC) in 2007 and 2014 revived a global effort to counteract the effects of CC, called for an analysis of the impacts on vulnerable socio-economic groups and on economic activities, and for the development of decision-making tools to enable policy and other decisions based on the complexity of the world in relation to climate change, taking into account socio-economic attributes. We follow up this suggestion and determine the impact of CC on vulnerable populations in the Mexican labour market, taking into account two attributes (gender and level of qualification of workers). Most studies have focused on the effects of CC on the agricultural sector, as it is considered a highly vulnerable economic sector to the effects of climate variability. This research seeks to contribute to the existing literature taking into account, in addition to the agricultural sector, other sectors such as tourism, water availability, and energy that are of vital importance to the Mexican economy. Likewise, the effects of climate change will be extended to the labour market and specifically to women who in some cases have been left out. The studies are sceptical about the impact of CC on the female labour market because of the perverse effects on women's domestic work, which are too often omitted from analyses. This work will contribute to the literature by integrating domestic work, which in the case of Mexico is much higher among women than among men (80.9% vs. 19.1%), according to the 2009 time use survey. This study is relevant since it will allow us to analyse impacts of climate change not only in the labour market of the formal economy, but also in the non-market sphere. Likewise, we consider that including the gender dimension is valid for the Mexican economy as it is a country with high degrees of gender inequality in the labour market. In the OECD economic study for Mexico (2017), the low labour participation of Mexican women is highlighted. Although participation has increased substantially in recent years (from 36% in 1990 to 47% in 2017), it remains low compared to the OECD average where women participate around 70% of the labour market. According to Mexico's 2009 time use survey, domestic work represents about 13% of the total time available. Understanding the interdependence between the market and non-market spheres, and the gender division of labour within them is the necessary premise for any economic analysis aimed at promoting gender equality and inclusive growth.Keywords: climate change, labour market, domestic work, rural sector
Procedia PDF Downloads 1312452 Autophagy Suppresses Tumorigenesis through Upregulation of MiR-449a in Colorectal Cancer
Authors: Sheng-Hui Lan, Shan-Ying Wu, Shu-Ching Lin, Wei-Chen Wang, Hsiao-Sheng Liu
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Autophagy is an essential mechanism to maintain cellular homeostasis through its degradation function, and the autophagy deficiency is related various diseases including tumorigenesis in several cancers. MicroRNAs (miRNAs) are small none coding RNAs, which regulate gene expression through degradation of mRNA or inhibition of translation. However, the relationship between autophagy deficiency and dysregulated miRNAs is still unclear. We revealed a mechanism that autophagy up-regulates miR-449a expression at the transcriptional level through activation of forkhead transcription factor family member FoxO1 and then suppresses tumorigenesis in CRC. Our data showed that the autophagic activity and miR-449a expression were lower in colorectal cancer (CRC) and has a positive correlation. We further reveal that autophagy degrades p300 expression and then suppresses acetylation of FoxO1. Under autophagic induction conditions, FoxO1 is transported from the cytoplasm to the nucleus and binds to the miR-449a promoter and then promotes miR-449a expression. In addition, either miR-449a overexpression or amiodarone-induced autophagy inhibits cell cycle progression, proliferation, colony formation migration, invasion, and tumor formation of SW480 cells. Our findings indicate that autophagy inducers may have the potential to be used for prevention and treatment of CRC through upregulation of miR-449a expression.Keywords: autophagy, MiR-449a, FoxO1, colorectal cancer
Procedia PDF Downloads 3202451 Deep Learning Based on Image Decomposition for Restoration of Intrinsic Representation
Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong
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Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation
Procedia PDF Downloads 1902450 Understanding Everyday Insecurities Emerging from Fragmented Territorial Control in Post-Accord Colombia
Authors: Clara Voyvodic
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Transitions from conflict to peace are by no means smooth nor linear, particularly from the perspective of those living through them. Over the last few decades, the changing focus in peacebuilding studies has come to appreciate the everyday experience of communities and how that provides a lens through which the relative success or efficacy of these transitions can be understood. In particular, the demobilization of a significant conflict actor is not without consequences, not just for the macro-view of state stabilization and peace, but for the communities who find themselves without a clear authority of territorial control. In Colombia, the demobilization and disarmament of the FARC guerilla group provided a brief respite to the conflict and a major political win for President Manuel Santos. However, this victory has proven short-lived. Drawing from extensive field research in Colombia within the last year, including interviews with local communities and actors operating in these regions, field observations, and other primary resources, this paper examines the post-accord transitions in Colombia and the everyday security experiences of local communities in regions formerly controlled by the FARC. In order to do so, the research focused on a semi-ethnographic approach in the northern region of the department of Antioquia and the coastal area of the border department of Nariño that documented how individuals within these marginalized communities have come to understand and negotiate their security in the years following the accord and the demobilization of the FARC. This presentation will argue that the removal of the FARC as an informal governance actor opened a space for multiple actors to attempt to control the same territory, including the state. This shift has had a clear impact on the everyday security experiences of the local communities. With an exploration of the dynamics of local governance and its impact on lived security experiences, this research seeks to demonstrate how distinct patterns of armed group behavior are emerging not only from a vacuum of control left by the FARC but from an increase in state presence that nonetheless remains inconsistent and unpersuasive as a monopoly of force in the region. The increased multiplicity of actors, particularly the state, has meant that the normal (informal) rules for communities to navigate these territories are no longer in play as the identities, actions, and intentions of different competing groups have become frustratingly opaque. This research provides a prescient analysis on how the shifting dynamics of territorial control in a post-peace accord landscape produce uncertain realities that affect the daily lives of the local communities and endanger the long-term prospect of human-centered security.Keywords: armed actors, conflict transitions, informal governance, post-accord, security experiences
Procedia PDF Downloads 1322449 Tracking Performance Evaluation of Robust Back-Stepping Control Design for a Nonlinear Electro-Hydraulic Servo System
Authors: Maria Ahmadnezhad, Mohammad Reza Soltanpour
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Electrohydraulic servo systems have been used in industry in a wide number of applications. Its dynamics are highly nonlinear and also have large extent of model uncertainties and external disturbances. In this thesis, a robust back-stepping control (RBSC) scheme is proposed to overcome the problem of disturbances and system uncertainties effectively and to improve the tracking performance of EHS systems. In order to implement the proposed control scheme, the system uncertainties in EHS systems are considered as total leakage coefficient and effective oil volume. In addition, in order to obtain the virtual controls for stabilizing system, the update rule for the system uncertainty term is induced by the Lyapunov control function (LCF). To verify the performance and robustness of the proposed control system, computer simulation of the proposed control system using Matlab/Simulink Software is executed. From the computer simulation, it was found that the RBSC system produces the desired tracking performance and has robustness to the disturbances and system uncertainties of EHS systems.Keywords: electro hydraulic servo system, back-stepping control, robust back-stepping control, Lyapunov redesign
Procedia PDF Downloads 2962448 Video Analytics on Pedagogy Using Big Data
Authors: Jamuna Loganath
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Education is the key to the development of any individual’s personality. Today’s students will be tomorrow’s citizens of the global society. The education of the student is the edifice on which his/her future will be built. Schools therefore should provide an all-round development of students so as to foster a healthy society. The behaviors and the attitude of the students in school play an essential role for the success of the education process. Frequent reports of misbehaviors such as clowning, harassing classmates, verbal insults are becoming common in schools today. If this issue is left unattended, it may develop a negative attitude and increase the delinquent behavior. So, the need of the hour is to find a solution to this problem. To solve this issue, it is important to monitor the students’ behaviors in school and give necessary feedback and mentor them to develop a positive attitude and help them to become a successful grownup. Nevertheless, measuring students’ behavior and attitude is extremely challenging. None of the present technology has proven to be effective in this measurement process because actions, reactions, interactions, response of the students are rarely used in the course of the data due to complexity. The purpose of this proposal is to recommend an effective supervising system after carrying out a feasibility study by measuring the behavior of the Students. This can be achieved by equipping schools with CCTV cameras. These CCTV cameras installed in various schools of the world capture the facial expressions and interactions of the students inside and outside their classroom. The real time raw videos captured from the CCTV can be uploaded to the cloud with the help of a network. The video feeds get scooped into various nodes in the same rack or on the different racks in the same cluster in Hadoop HDFS. The video feeds are converted into small frames and analyzed using various Pattern recognition algorithms and MapReduce algorithm. Then, the video frames are compared with the bench marking database (good behavior). When misbehavior is detected, an alert message can be sent to the counseling department which helps them in mentoring the students. This will help in improving the effectiveness of the education process. As Video feeds come from multiple geographical areas (schools from different parts of the world), BIG DATA helps in real time analysis as it analyzes computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. It also analyzes data that can’t be analyzed by traditional software applications such as RDBMS, OODBMS. It has also proven successful in handling human reactions with ease. Therefore, BIG DATA could certainly play a vital role in handling this issue. Thus, effectiveness of the education process can be enhanced with the help of video analytics using the latest BIG DATA technology.Keywords: big data, cloud, CCTV, education process
Procedia PDF Downloads 2402447 Growth Curves Genetic Analysis of Native South Caspian Sea Poultry Using Bayesian Statistics
Authors: Jamal Fayazi, Farhad Anoosheh, Mohammad R. Ghorbani, Ali R. Paydar
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In this study, to determine the best non-linear regression model describing the growth curve of native poultry, 9657 chicks of generations 18, 19, and 20 raised in Mazandaran breeding center were used. Fowls and roosters of this center distributed in south of Caspian Sea region. To estimate the genetic variability of none linear regression parameter of growth traits, a Gibbs sampling of Bayesian analysis was used. The average body weight traits in the first day (BW1), eighth week (BW8) and twelfth week (BW12) were respectively estimated as 36.05, 763.03, and 1194.98 grams. Based on the coefficient of determination, mean squares of error and Akaike information criteria, Gompertz model was selected as the best growth descriptive function. In Gompertz model, the estimated values for the parameters of maturity weight (A), integration constant (B) and maturity rate (K) were estimated to be 1734.4, 3.986, and 0.282, respectively. The direct heritability of BW1, BW8 and BW12 were respectively reported to be as 0.378, 0.3709, 0.316, 0.389, 0.43, 0.09 and 0.07. With regard to estimated parameters, the results of this study indicated that there is a possibility to improve some property of growth curve using appropriate selection programs.Keywords: direct heritability, Gompertz, growth traits, maturity weight, native poultry
Procedia PDF Downloads 2642446 A Disappearing Radiolucency of the Mandible Caused by Inadvertent Trauma Following IMF Screw Placement
Authors: Anna Ghosh, Dominic Shields, Ceri McIntosh, Stephen Crank
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A 29-year-old male was a referral to the maxillofacial unit following a referral from his general dental practitioner via a routine pathway regarding a large periapical lesion on the LR4 with root resorption. The patient was asymptomatic, the LR4 vital and unrestored, and this was an incidental finding at a routine check-up. The patient's past medical history was unremarkable. Examination revealed no extra or intra-oral pathology and non-mobile teeth. No focal neurology was detected. An orthopantogram demonstrated a well-defined unilocular corticated radiolucency associated with the LR4. The root appeared shortened with the radiolucency between the root and a radio-opacity, possibly representing the displacement of the apical tip of the tooth. It was recommended that the referring general practitioner should proceed with orthograde root canal therapy, after which time exploration, enucleation, and retrograde root filling of the LR4 would be carried out by a maxillofacial unit. The patient was reviewed six months later where, due to the COVID-19 pandemic, the patient had been unable to access general dental services for the root canal treatment. He was still entirely asymptomatic. A one-year review was planned in the hope this would allow time for the orthograde root canal therapy to be completed. At this review, the orthograde root canal therapy had still not been completed. Interestingly, a repeat orthopantogram revealed a significant reduction in size with good bony infill and a significant reduction in the size of the lesion. Due to the ongoing delays with primary care dental therapy, the patient was subsequently internally referred to the restorative dentistry department for care. The patient was seen again by oral and maxillo-facial surgery in mid-2022 where he still reports this tooth as asymptomatic with no focal neurology. The patient's history was fully reviewed, and noted that 15 years previously, the patient underwent open reduction and internal fixation of a left angle of mandible fracture. Temporary IMF involving IMF screws and fixation wires were employed to maintain occlusion during plating and subsequently removed post-operatively. It is proposed that the radiolucency was, as a result of the IMF screw placement, penetrating the LR4 root resulting in resorption of the tooth root and development of a radiolucency. This case highlights the importance of careful screw size and physical site location, and placement of IMF screws, as there can be permeant damage to a patient’s dentition.Keywords: facial trauma, inter-maxillary fixation, mandibular radiolucency, oral and maxillo-facial surgery
Procedia PDF Downloads 1362445 Exploring the Challenges of Post-conflict Peacebuilding in the Border Districts of Eastern Zone of Tigray Region
Authors: Gebreselassie Sebhatleab
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According to the Global Peace Index report (GPI, 2023), global peacefulness has deteriorated by more than 0.42%. Old and new conflicts, COVID-19, and political and cultural polarization are the main drivers of conflicts in the world. The 2022 was the deadliest year for armed conflict in the history of the GPI. In Ethiopia, over half a million people died in the Tigray war, which was the largest conflict death event since the 1994 Rwandan genocide. In total, 84 countries recorded an improvement, while 79 countries recorded a deterioration in peacefulness across the globe. The Russia-Ukraine war and its consequences were the main drivers of the deterioration in peacefulness globally. Both Russia and Ukraine are now ranked amongst the ten least peaceful countries, and Ukraine had the largest deterioration of any country in the 2023 GPI. In the same year, the global impact of violence on the economy was 17 percent, which was equivalent to 10.9% of global GDP. Besides, the brutal conflict in Tigray started in November. 2020 claimed more than half a million lives lost and displaced nearly 3 million people, along with widespread human rights violations and sexual violence has left deep damage on the population. The displaced people are still unable to return home because the western, southern and Eastern parts of Tigray are occupied by Eritrean and Amhara forces, despite the Pretoria Agreement. Currently, armed conflicts in Amhara in the Oromya regions are intensified, and human rights violations are being reported in both regions. Meanwhile, protests have been held by war-injured TDF members, IDPs and teachers in the Tigray region. Hence, the general objective of this project is to explore the challenges of peace-building processes in the border woredas of the Eastern Zone of the Tigray Region. Methodologically, the project will employ exploratory qualitative research designs to gather and analyze qualitative data. A purposive sampling technique will be applied to gather pertinent information from the key stakeholders. Open-ended interview questions will be prepared to gather relevant information about the challenges and perceptions of peacebuilding in the study area. Data will be analyzed using qualitative methods such as content analysis, narrative analysis and phenomenological analysis to deeply investigate the challenges of peace-building in the study woredas. Findings of this research project will be employed for program intervention to promote sustainable peace in the study area.Keywords: peace building, conflcit and violence, political instability, insecurity
Procedia PDF Downloads 392444 The Impact of Solution-Focused Brief Therapy on the Improvement of the Psychological Wellbeing of Family Supervisor Women
Authors: Kaveh Qaderi Bagajan, Osman Khanahmadi, Ziba Mamaghani Chaharborj, Majid Chenaparchi
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The purpose of this study is to investigate the efficacy of the solution-focused brief therapy on improving the psychological wellbeing of family supervisor woman. This study has been carried out by semi-experimental method and in the form of pre-test, post-test performance on two groups (experimental and control), so that one sample group of 30 individuals was randomly achieved and were randomly divided in two groups of experimental (n=15) and control (n=15). To collect data, Ryff scale psychological wellbeing was used. After conducting pre-test (RSPWB) for two experimental and control groups, Solution-focused brief therapy interference was conducted on the experimental group during five two-hour sessions. Finally, Ryff scale psychological wellbeing was reused for the two groups as post-test and achieved outcomes that were analyzed using covariance. The results indicated that the significant increase of average marks of the experimental group in psychological wellbeing had better function than that of the control group. Finally, solution-focused brief therapy for improving psychological well-being of family supervisor women has a suitable capability and could be used in this way.Keywords: solution-focused brief therapy, short-term therapy, family supervisor women, psychological well-being
Procedia PDF Downloads 3102443 Effect of Changing Iron Content and Excitation Frequency on Magnetic Particle Imaging Signal: A Comparative Study of Synomag® Nanoparticles
Authors: Kalthoum Riahi, Max T. Rietberg, Javier Perez y Perez, Corné Dijkstra, Bennie ten Haken, Lejla Alic
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Magnetic nanoparticles (MNPs) are widely used to facilitate magnetic particle imaging (MPI) which has the potential to become the leading diagnostic instrument for biomedical imaging. This comparative study assesses the effects of changing iron content and excitation frequency on point-spread function (PSF) representing the effect of magnetization reversal. PSF is quantified by features of interest for MPI: i.e., drive field amplitude and full-width-at-half-maximum (FWHM). A superparamagnetic quantifier (SPaQ) is used to assess differential magnetic susceptibility of two commercially available MNPs: Synomag®-D50 and Synomag®-D70. For both MNPs, the signal output depends on increase in drive field frequency and amount of iron-oxide, which might be hampering the sensitivity of MPI systems that perform on higher frequencies. Nevertheless, there is a clear potential of Synomag®-D for a stable MPI resolution, especially in case of 70 nm version, that is independent of either drive field frequency or amount of iron-oxide.Keywords: magnetic nanoparticles, MNPs, differential magnetic susceptibility, DMS, magnetic particle imaging, MPI, magnetic relaxation, Synomag®-D
Procedia PDF Downloads 1402442 Analysis of Efficacy and Safety of Abatacept for Rheumatoid Arthritis: A Systematic Review and Meta Analysis
Authors: Hamida Memon
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Rheumatoid arthritis (RA) is a persistent inflammation of the joints caused by an aggressive immune reaction leading to pain, stiffness, and limited function. Abatacept, a selective co-modulator, is a promising option for treatment and may have better safety profiles compared to other interventions. This meta-analysis aims at assessing the effectiveness and safety of abatacept in contrast to various RA treatments such as placebos, biological DMARDs and conventional DMARDs. The analysis assesses how abatacept influences disease activity, pain intensity and overall patient functionality. It weighs the risk factor of abatacept with other drugs such as tocilizumab, with the numbers being lower for abatacept. This meta-analysis aims at assessing the effectiveness and safety of abatacept in contrast to various RA treatments such as placebos, biological DMARDs and conventional DMARDs. The analysis assesses how abatacept influences disease activity, pain intensity and overall patient functionality. It weighs the risk factor of abatacept with other drugs such as tocilizumab, with the numbers being lower for abatacept.Keywords: Rheumatoid arthritis, abatacept, control group, bone disease
Procedia PDF Downloads 232441 Optimal Design of Composite Cylindrical Shell Based on Nonlinear Finite Element Analysis
Authors: Haider M. Alsaeq
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The present research is an attempt to figure out the best configuration of composite cylindrical shells of the sandwich type, i.e. the lightest design of such shells required to sustain a certain load over a certain area. The optimization is based on elastic-plastic geometrically nonlinear incremental-iterative finite element analysis. The nine-node degenerated curved shell element is used in which five degrees of freedom are specified at each nodal point, with a layered model. The formulation of the geometrical nonlinearity problem is carried out using the well-known total Lagrangian principle. For the structural optimization problem, which is dealt with as a constrained nonlinear optimization, the so-called Modified Hooke and Jeeves method is employed by considering the weight of the shell as the objective function with stress and geometrical constraints. It was concluded that the optimum design of composite sandwich cylindrical shell that have a rigid polyurethane foam core and steel facing occurs when the area covered by the shell becomes almost square with a ratio of core thickness to facing thickness lies between 45 and 49, while the optimum height to length ration varies from 0.03 to 0.08 depending on the aspect ratio of the shell and its boundary conditions.Keywords: composite structure, cylindrical shell, optimization, non-linear analysis, finite element
Procedia PDF Downloads 3912440 Characterization of Laminar Flow and Power Consumption in Agitated Vessel with Curved Blade Agitator
Authors: Amine Benmoussa, Mohamed Bouanini, Mebrouk Rebhi
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Stirring is one of the unifying processes which form part of the mechanical unit operations in process technology such chemical, biotechnological, pharmaceutical, petrochemical, cosmetic, and food processing. Therefore determining the level of mixing and overall behavior and performance of the mixing tanks are crucial from the product quality and process economics point of views. The most fundamental needs for the analysis of these processes from both a theoretical and industrial perspective are the knowledge of the hydrodynamic behavior and the flow structure in such tanks. Depending on the purpose of the operation carried out in mixer, the best choice for geometry of the tank and agitator type can vary widely. Initially, a local and global study namely the velocity and power number on a typical agitation system agitated by a mobile-type two-blade straight (d/D=0.5) allowed us to test the reliability of the CFD, the result were compared with those of experimental literature, a very good concordance was observed. The stream function, the velocity profile, the velocity fields and power number are analyzed. It was shown that the hydrodynamics is modified by the curvature of the mobile which plays a key role.Keywords: agitated vessels, curved blade agitator, laminar flow, finite volume method
Procedia PDF Downloads 2842439 Compromising Relevance for Elegance: A Danger of Dominant Growth Models for Backward Economies
Authors: Givi Kupatadze
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Backward economies are facing a challenge of achieving sustainable high economic growth rate. Dominant growth models represent a roadmap in framing economic development strategy. This paper examines a relevance of the dominant growth models for backward economies. Cobb-Douglas production function, the Harrod-Domar model of economic growth, the Solow growth model and general formula of gross domestic product are examined to undertake a comprehensive study of the dominant growth models. Deductive research method allows to uncover major weaknesses of the dominant growth models and to come up with practical implications for economic development strategy. The key finding of the paper shows, contrary to what used to be taught by textbooks of economics, that constant returns to scale property of the dominant growth models are a mere coincidence and its generalization over space and time can be regarded as one of the most unfortunate mistakes in the whole field of political economy. The major suggestion of the paper for backward economies is that understanding and considering taxonomy of economic activities based on increasing and diminishing returns to scale represent a cornerstone of successful economic development strategy.Keywords: backward economies, constant returns to scale, dominant growth models, taxonomy of economic activities
Procedia PDF Downloads 3752438 An Approach to Consumption of Exhaustible Resources Based on Islamic Justice and Hartwick Criteria
Authors: Hamed Najafi, Ghasem Nikjou
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Nowadays, there is an increasing attention to the resources scarcity issues. Because of failure in present patterns in the field of the allocation of exhaustible resources between generations and the challenges related to economic justice supply, it is supposed, to present a pattern from the Islamic perspective in this essay. By using content analysis of religious texts, we conclude that governments should remove the gap which is exists between the per capita income of the poor and their minimum consumption (necessary consumption). In order to preserve the exhaustible resources for poor people) not for all), between all generations, government should invest exhaustible resources on endless resources according to Hartwick’s criteria and should spend these benefits for poor people. But, if benefits did not cover the gap between minimum consumption and per capita income of poor levels in one generation, in this case, the government is responsible for covering this gap through the direct consumption of exhaustible resources. For an exact answer to this question, ‘how much of exhaustible resources should expense to maintain justice between generations?’ The theoretical and mathematical modeling has been used and proper function has been provided. The consumption pattern is presented for economic policy makers in Muslim countries, and non-Muslim even, it can be useful.Keywords: exhaustible resources, Islamic justice, intergenerational justice, distribution of resources, Hartwick criteria
Procedia PDF Downloads 1892437 Preparation and Characterization of Conductive Poly(N-Ethyl Aniline)/Kaolinite Composite Material by Chemical Polymerization
Authors: Hande Taşdemir, Meral Şahin, Mehmet Saçak
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Conductive composite materials obtained by physical or chemical mixing of two or more components having conducting and insulating properties have been increasingly attracted. Kaolinite in kaolin clays is one of silicates with two layers of molecular sheets of (Si2O5)2− and [Al2(OH)4]2+ with the chemical composition Al2Si2O5(OH)4. The most abundant hydrophillic kaolinite is extensively used in industrial processes and therefore it is convenient for the preparation of organic/inorganic composites. In this study, conductive poly(N-ethylaniline)/kaolinite composite was prepared by chemical polymerization of N-ethyl aniline in the presence of kaolinite particles using ammonium persulfate as oxidant in aqueous acidic medium. Poly(N-ethylaniline) content and conductivity of composite prepared were systematically investigated as a function of polymerization conditions such as ammonium persulfate, N-ethyl aniline and HCl concentrations. Poly(N-ethylaniline) content and conductivity of composite increased with increasing oxidant and monomer concentrations up to 0.1 M and 0.2 M, respectively, and decreased at higher concentrations. The maximum yield of polymer in the composite (15.0%) and the highest conductivity value of the composite (5.0×10-5 S/cm) was achieved by polymerization for 2 hours at 20°C in HCl of 0.5 M. The structure, morphological analyses and thermal behaviours of poly(N-ethylaniline)/kaolinite composite were characterized by FTIR and XRD spectroscopy, SEM and TGA techniques.Keywords: kaolinite, poly(N-ethylaniline), conductive composite, chemical polymerization
Procedia PDF Downloads 2922436 Semantics of the Word “Nas” in the Verse 24 of Surah Al-Baqarah Based on Izutsus’ Semantic Field Theory
Authors: Seyedeh Khadijeh. Mirbazel, Masoumeh Arjmandi
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Semantics is a linguistic approach and a scientific stream, and like all scientific streams, it is dynamic. The study of meaning is carried out in the broad semantic collections of words that form the discourse. In other words, meaning is not something that can be found in a word; rather, the formation of meaning is a process that takes place in a discourse as a whole. One of the contemporary semantic theories is Izutsu's Semantic Field Theory. According to this theory, the discovery of meaning depends on the function of words and takes place within the context of language. The purpose of this research is to identify the meaning of the word "Nas" in the discourse of verse 24 of Surah Al-Baqarah, which introduces "Nas" as the firewood of hell, but the translators have translated it as "people". The present research has investigated the semantic structure of the word "Nas" using the aforementioned theory through the descriptive-analytical method. In the process of investigation, by matching the semantic fields of the Quranic word "Nas", this research came to the conclusion that "Nas" implies those persons who have forgotten God and His covenant in believing in His Oneness. For this reason, God called them "Nas (the forgetful)" - the imperfect participle of the noun /næsiwoɔn/ in single trinity of Arabic language, which means “to forget”. Therefore, the intended meaning of "Nas" in the verses that have the word "Nas" is not equivalent to "People" which is a general noun.Keywords: Nas, people, semantics, semantic field theory.
Procedia PDF Downloads 1892435 A Study of New Window Typology for Palestinian Residential Building for More Sustainable Building
Authors: Nisreen Ardda
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Fenestrations are one of the main building envelope elements that play an important role in home social-ecological l factors. They play a vital role in providing natural lighting and ventilation, visual, thermal, and acoustical comfort, and also provide weather-tightness, privacy, a feeling of openness. In most home buildings, fenestrations are controlled manually by the occupants, which significantly impacts occupants' comfort and energy use. Culture plays a central role in the Palestinians window operation behavior. Improved windows design that provides the desired privacy while maintaining the appropriate function of fenestration (natural lighting, thermal comfort, and visual openness) is becoming a necessity. Therefore, this paper proposes a window typology to achieve the social and environmental factors in residential buildings in the West Bank. The window typology and reference building were designed in Rivet 2021, and natural ventilation was carried out in Design Builder 4.3.0.039. The results showed that the proposed typology provides the desired privacy and the feeling of openness without compromising natural ventilation as the existing window did.Keywords: window design, passive design, sustainable built environment, building material
Procedia PDF Downloads 1862434 Numerical Solution of Transient Natural Convection in Vertical Heated Rectangular Channel between Two Vertical Parallel MTR-Type Fuel Plates
Authors: Djalal Hamed
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The aim of this paper is to perform, by mean of the finite volume method, a numerical solution of the transient natural convection in a narrow rectangular channel between two vertical parallel Material Testing Reactor (MTR)-type fuel plates, imposed under a heat flux with a cosine shape to determine the margin of the nuclear core power at which the natural convection cooling mode can ensure a safe core cooling, where the cladding temperature should not reach a specific safety limits (90 °C). For this purpose, a computer program is developed to determine the principal parameters related to the nuclear core safety, such as the temperature distribution in the fuel plate and in the coolant (light water) as a function of the reactor core power. Throughout the obtained results, we noticed that the core power should not reach 400 kW, to ensure a safe passive residual heat removing from the nuclear core by the upward natural convection cooling mode.Keywords: buoyancy force, friction force, finite volume method, transient natural convection
Procedia PDF Downloads 1962433 FLIME - Fast Low Light Image Enhancement for Real-Time Video
Authors: Vinay P., Srinivas K. S.
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Low Light Image Enhancement is of utmost impor- tance in computer vision based tasks. Applications include vision systems for autonomous driving, night vision devices for defence systems, low light object detection tasks. Many of the existing deep learning methods are resource intensive during the inference step and take considerable time for processing. The algorithm should take considerably less than 41 milliseconds in order to process a real-time video feed with 24 frames per second and should be even less for a video with 30 or 60 frames per second. The paper presents a fast and efficient solution which has two main advantages, it has the potential to be used for a real-time video feed, and it can be used in low compute environments because of the lightweight nature. The proposed solution is a pipeline of three steps, the first one is the use of a simple function to map input RGB values to output RGB values, the second is to balance the colors and the final step is to adjust the contrast of the image. Hence a custom dataset is carefully prepared using images taken in low and bright lighting conditions. The preparation of the dataset, the proposed model, the processing time are discussed in detail and the quality of the enhanced images using different methods is shown.Keywords: low light image enhancement, real-time video, computer vision, machine learning
Procedia PDF Downloads 2062432 Deconstructing and Reconstructing the Definition of Inhuman Treatment in International Law
Authors: Sonia Boulos
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The prohibition on ‘inhuman treatment’ constitutes one of the central tenets of modern international human rights law. It is incorporated in principal international human rights instruments including Article 5 of the Universal Declaration of Human Rights, and Article 7 of the International Covenant on Civil and Political Rights. However, in the absence of any legislative definition of the term ‘inhuman’, its interpretation becomes challenging. The aim of this article is to critically analyze the interpretation of the term ‘inhuman’ in international human rights law and to suggest a new approach to construct its meaning. The article is composed of two central parts. The first part is a critical appraisal of the interpretation of the term ‘inhuman’ by supra-national human rights law institutions. It highlights the failure of supra-national institutions to provide an independent definition for the term ‘inhuman’. In fact, those institutions consistently fail to distinguish the term ‘inhuman’ from its other kin terms, i.e. ‘cruel’ and ‘degrading.’ Very often, they refer to these three prohibitions as ‘CIDT’, as if they were one collective. They were primarily preoccupied with distinguishing ‘CIDT’ from ‘torture.’ By blurring the conceptual differences between these three terms, supra-national institutions supplemented them with a long list of specific and purely descriptive subsidiary rules. In most cases, those subsidiary rules were announced in the absence of sufficient legal reasoning explaining how they were derived from abstract and evaluative standards embodied in the prohibitions collectively referred to as ‘CIDT.’ By opting for this option, supra-national institutions have created the risk for the development of an incoherent body of jurisprudence on those terms at the international level. They also have failed to provide guidance for domestic courts on how to enforce these prohibitions. While blurring the differences between the terms ‘cruel,’ ‘inhuman,’ and ‘degrading’ has consequences for the three, the term ‘inhuman’ remains the most impoverished one. It is easy to link the term ‘cruel’ to the clause on ‘cruel and unusual punishment’ originating from the English Bill of Rights of 1689. It is also easy to see that the term ‘degrading’ reflects a dignatarian ideal. However, when we turn to the term ‘inhuman’, we are left without any interpretative clue. The second part of the article suggests that the ordinary meaning of the word ‘inhuman’ should be our first clue. However, regaining the conceptual independence of the term ‘inhuman’ requires more than a mere reflection on the word-meaning of the term. Thus, the second part introduces philosophical concepts related to the understanding of what it means to be human. It focuses on ‘the capabilities approach’ and the notion of ‘human functioning’, introduced by Amartya Sen and further explored by Martha Nussbaum. Nussbaum’s work on the basic human capabilities is particularly helpful or even vital for understanding the moral and legal substance of the prohibition on ‘inhuman’ treatment.Keywords: inhuman treatment, capabilities approach, human functioning, supra-national institutions
Procedia PDF Downloads 2782431 Electrokinetic Application for the Improvement of Soft Clays
Authors: Abiola Ayopo Abiodun, Zalihe Nalbantoglu
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The electrokinetic application (EKA), a relatively modern chemical treatment has a potential for in-situ ground improvement in an open field or under existing structures. It utilizes a low electrical gradient to transport electrolytic chemical ions between bespoke electrodes inserted in the fine-grained, low permeable soft soils. The paper investigates the efficacy of the EKA as a mitigation technique for the soft clay beds. The laboratory model of the EKA comprises of rectangular plexiglass test tank, electrolytes compartments, geosynthetic electrodes and direct electric current supply. Within this setup, the EK effects resulted from the exchange of ions between anolyte (anodic) and catholyte (cathodic) ends through the tested soil were examined by basic experimental laboratory testing methods. As such, the treated soft soil properties were investigated as a function of the anode-to-cathode distances and curing periods. The test results showed that there have been some changes in the physical and engineering properties of the treated soft soils. The significant changes in the physicochemical and electrical properties suggested that their corresponding changes can be utilized as a monitoring technique to evaluate the improvement in the engineering properties EK treated soft clay soils.Keywords: electrokinetic, electrolytes, exchange ions, geosynthetic electrodes, soft soils
Procedia PDF Downloads 3142430 Development of an EEG-Based Real-Time Emotion Recognition System on Edge AI
Authors: James Rigor Camacho, Wansu Lim
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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors
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