Search results for: models synthesis
2918 Experimental and Numerical Analysis of the Effects of Ball-End Milling Process upon Residual Stresses and Cutting Forces
Authors: Belkacem Chebil Sonia, Bensalem Wacef
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The majority of ball end milling models includes only the influence of cutting parameters (cutting speed, feed rate, depth of cut). Furthermore, this influence is studied in most of works on cutting force. Therefore, this study proposes an accurate ball end milling process modeling which includes also the influence of tool workpiece inclination. In addition, a characterization of residual stresses resulting of thermo mechanical loading in the workpiece was also presented. Moreover, the study of the influence of tool workpiece inclination and cutting parameters was made on residual stresses distribution. In order to achieve the predetermination of cutting forces and residual stresses during a milling operation, a thermo mechanical three-dimensional numerical model of ball end milling was developed. Furthermore, an experimental companion of ball end milling tests was realized on a 5-axis machining center to determine the cutting forces and characterize the residual stresses. The simulation results are compared with the experiment to validate the Finite Element Model and subsequently identify the optimum inclination angle and cutting parameters.Keywords: ball end milling, cutting forces, cutting parameters, residual stress, tool-workpiece inclination
Procedia PDF Downloads 3072917 Phytochemical and Biological Study of Chrozophora oblongifolia
Authors: Al-Braa Kashegari, Ali M. El-Halawany, Akram A. Shalabi, Sabrin R. M. Ibrahim, Hossam M. Abdallah
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Chemical investigation of Chrozophora oblongifolia resulted in the isolation of five major compounds that were identified as apeginin-7-O-glucoside (1), quercetin-3-O-glucuronic acid (2), quercetin-3-O-glacturonic acid (3), rutin (4), and 1,3,6-trigalloyl glucose (5). The identity of isolated compounds was assessed by different spectroscopic methods, including one- and two-dimensional NMR. The isolated compounds were tested for their antioxidant activity using different assays viz., DPPH, FRAP, ABTS, ORAC, and metal chelation effects. In addition, the inhibition of target enzymes involved in the metabolic syndrome, such as alpha-glucosidase and pancreatic lipase, were carried out. Moreover, the effect of the compounds on the advanced glycation end-products (AGEs) as one of the major complications of oxidative stress and hyperglycemia in metabolic syndromes were carried out using BSA‐fructose (bovine serum albumin), BSA-methylglyoxal, and arginine methylglyoxal models. The pure isolates showed a protective effect in metabolic syndromes as well as promising antioxidant activity. The results showed potent activity of compound 5 in all measured parameters meanwhile, none of the tested compounds showed activity against pancreatic lipase.Keywords: Chrozophora oblongifolia, antioxidant, pancreatic lipase, metabolic syndromes
Procedia PDF Downloads 1102916 Obesity and Cancer: Current Scientific Evidence and Policy Implications
Authors: Martin Wiseman, Rachel Thompson, Panagiota Mitrou, Kate Allen
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Since 1997 World Cancer Research Fund (WCRF) International and the American Institute for Cancer Research (AICR) have been at the forefront of synthesising and interpreting the accumulated scientific literature on the link between diet, nutrition, physical activity and cancer, and deriving evidence-based Cancer Prevention Recommendations. The 2007 WCRF/AICR 2nd Expert Report was a landmark in the analysis of evidence linking diet, body weight and physical activity to cancer and led to the establishment of the Continuous Update Project (CUP). In 2018, as part of the CUP, WCRF/AICR will publish a new synthesis of the current evidence and update the Cancer Prevention Recommendations. This will ensure that everyone - from policymakers and health professionals to members of the public - has access to the most up-to-date information on how to reduce the risk of developing cancer. Overweight and obesity play a significant role in cancer risk, and rates of both are increasing in many parts of the world. This session will give an overview of new evidence relating obesity to cancer since the 2007 report. For example, since the 2007 Report, the number of cancers for which obesity is judged to be a contributory cause has increased from seven to eleven. The session will also shed light on the well-established mechanisms underpinning obesity and cancer links. Additionally, the session will provide an overview of diet and physical activity related factors that promote positive energy imbalance, leading to overweight and obesity. Finally, the session will highlight how policy can be used to address overweight and obesity at a population level, using WCRF International’s NOURISHING Framework. NOURISHING formalises a comprehensive package of policies to promote healthy diets and reduce obesity and non-communicable diseases; it is a tool for policymakers to identify where action is needed and assess if an approach is sufficiently comprehensive. The framework brings together ten policy areas across three domains: food environment, food system, and behaviour change communication. The framework is accompanied by a regularly updated database providing an extensive overview of implemented government policy actions from around the world. In conclusion, the session will provide an overview of obesity and cancer, highlighting the links seen in the epidemiology and exploring the mechanisms underpinning these, as well as the influences that help determine overweight and obesity. Finally, the session will illustrate policy approaches that can be taken to reduce overweight and obesity worldwide.Keywords: overweight, obesity, nutrition, cancer, mechanisms, policy
Procedia PDF Downloads 1572915 Improving Forecasting Demand for Maintenance Spare Parts: Case Study
Authors: Abdulaziz Afandi
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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.Keywords: neural network, LSTM, MLP, forecasting demand, inventory management
Procedia PDF Downloads 1262914 3D Human Body Reconstruction Based on Multiple Viewpoints
Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo
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The aim of this study was to improve the effects of human body 3D reconstruction. The MvP algorithm was adopted to obtain key point information from multiple perspectives. This algorithm allowed the capture of human posture and joint positions from multiple angles, providing more comprehensive and accurate data. The study also incorporated the SMPL-X model, which has been widely used for human body modeling, to achieve more accurate 3D reconstruction results. The use of the MvP algorithm made it possible to observe the reconstructed object from multiple angles, thus reducing the problems of blind spots and missing information. This algorithm was able to effectively capture key point information, including the position and rotation angle of limbs, providing key data for subsequent 3D reconstruction. Compared with traditional single-view methods, the method of multi-view fusion significantly improved the accuracy and stability of reconstruction. By combining the MvP algorithm with the SMPL-X model, we successfully achieved better human body 3D reconstruction effects. The SMPL-X model is highly scalable and can generate highly realistic 3D human body models, thus providing more detail and shape information.Keywords: 3D human reconstruction, multi-view, joint point, SMPL-X
Procedia PDF Downloads 672913 Aspect-Level Sentiment Analysis with Multi-Channel and Graph Convolutional Networks
Authors: Jiajun Wang, Xiaoge Li
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The purpose of the aspect-level sentiment analysis task is to identify the sentiment polarity of aspects in a sentence. Currently, most methods mainly focus on using neural networks and attention mechanisms to model the relationship between aspects and context, but they ignore the dependence of words in different ranges in the sentence, resulting in deviation when assigning relationship weight to other words other than aspect words. To solve these problems, we propose a new aspect-level sentiment analysis model that combines a multi-channel convolutional network and graph convolutional network (GCN). Firstly, the context and the degree of association between words are characterized by Long Short-Term Memory (LSTM) and self-attention mechanism. Besides, a multi-channel convolutional network is used to extract the features of words in different ranges. Finally, a convolutional graph network is used to associate the node information of the dependency tree structure. We conduct experiments on four benchmark datasets. The experimental results are compared with those of other models, which shows that our model is better and more effective.Keywords: aspect-level sentiment analysis, attention, multi-channel convolution network, graph convolution network, dependency tree
Procedia PDF Downloads 2142912 Active Contours for Image Segmentation Based on Complex Domain Approach
Authors: Sajid Hussain
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The complex domain approach for image segmentation based on active contour has been designed, which deforms step by step to partition an image into numerous expedient regions. A novel region-based trigonometric complex pressure force function is proposed, which propagates around the region of interest using image forces. The signed trigonometric force function controls the propagation of the active contour and the active contour stops on the exact edges of the object accurately. The proposed model makes the level set function binary and uses Gaussian smoothing kernel to adjust and escape the re-initialization procedure. The working principle of the proposed model is as follows: The real image data is transformed into complex data by iota (i) times of image data and the average iota (i) times of horizontal and vertical components of the gradient of image data is inserted in the proposed model to catch complex gradient of the image data. A simple finite difference mathematical technique has been used to implement the proposed model. The efficiency and robustness of the proposed model have been verified and compared with other state-of-the-art models.Keywords: image segmentation, active contour, level set, Mumford and Shah model
Procedia PDF Downloads 1122911 Development of Low-Cost Vibro-Acoustic, and Fire-Resistant, Insulation Material from Natural and Sustainable Sources
Authors: K. Nasir, S. Ahmad, A. Khan, H. Benkreira
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The topic of the research is to develop sustainable fire-resistant materials for vibration and acoustic damping of structure and airborne noises from sustainable recycled materials and biodegradable binders. The paper reports, methods and techniques of enhancing fire resistive, vibration and acoustic properties of building insulation materials made from natural resources like wood and recycled materials like rubber and textile waste. The structures are designed to optimize the number, size and stratification of closed (heat insulating) and open (noise insulating) pores. The samples produced are tested for their heat and noise insulating properties, including vibration damping and their structural properties (airflow resistivity, porosity, tortuosity and elastic modulus). The structural properties are then used in theoretical models to check the acoustic insulation measurements. Initial data indicate that one layer of such material can yield as much as 18 times more damping, increasing the loss factor by 18%.Keywords: fire resistant, vibration damping, acoustic material, vibro-acoustic, thermal insulation, sustainable material, low cost materials, recycled materials, construction material
Procedia PDF Downloads 1312910 Electrical Resistivity of Solid and Liquid Pt: Insight into Electrical Resistivity of ε-Fe
Authors: Innocent C. Ezenwa, Takashi Yoshino
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Knowledge of the transport properties of Fe and its alloys at extreme high pressure (P), temperature (T) conditions are essential for understanding the generation and sustainability of the magnetic field of the rocky planets with a metallic core. Since Pt, an unfilled d-band late transition metal with an electronic structure of Xe4f¹⁴5d⁹6s¹, is paramagnetic and remains close-packed structure at ambient conditions and high P-T, it is expected that its transport properties at these conditions would be similar to those of ε-Fe. We investigated the T-dependent electrical resistivity of solid and liquid Pt up to 8 GPa and found it constant along its melting curve both on the liquid and solid sides in agreement with theoretical prediction and experimental results estimated from thermal conductivity measurements. Our results suggest that the T-dependent resistivity of ε-Fe is linear and would not saturate at high P, T conditions. This, in turn, suggests that the thermal conductivity of liquid Fe at Earth’s core conditions may not be as high as previously suggested by models employing saturation resistivity. Hence, thermal convection could have powered the geodynamo before the birth of the inner core. The electrical resistivity and thermal conductivity on the liquid and solid sides of the inner core boundary of the Earth would be significantly different in values.Keywords: electrical resistivity, thermal conductivity, transport properties, geodynamo and geomagnetic field
Procedia PDF Downloads 1412909 Gynocentrism and Self-Orientalization: A Visual Trend in Chinese Fashion Photography
Authors: Zhen Sun
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The study adopts the method of visual social semiotics to analyze a sample of fashion photos that were recently published in Chinese fashion magazines that target towards both male and female readers. It identifies a new visual trend in fashion photography, which is characterized by two features. First, the photos represent young, confident, and stylish female models with lower-class sloppy old men. The visual inharmony between the sexually desirable women and the aged men has suggested an impossibly accomplished sexuality and eroticism. Though the women are still under the male gaze, they are depicted as unreachable objects of voyeurism other than sexual objects subordinated to men. Second, the represented people are usually put in the backdrop of tasteless or vulgar Chinese town life, which is congruent with the images of men but makes the modern city girls out of place. The photographers intentionally contrast the images of women with that of men and with the background, which implies an imaginary binary division of modern Orientalism and the photographers’ self-orientalization strategy. Under the theoretical umbrella of neoliberal postfeminism, this study defines a new kind of gynocentric stereotype in Chinese fashion photography, which challenges the previous observations on gender portrayals in fashion magazines.Keywords: fashion photography, gynocentrism, neoliberal postfeminism, self-orientalization
Procedia PDF Downloads 4222908 Identification of Peroxisome Proliferator-Activated Receptors α/γ Dual Agonists for Treatment of Metabolic Disorders, Insilico Screening, and Molecular Dynamics Simulation
Authors: Virendra Nath, Vipin Kumar
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Background: TypeII Diabetes mellitus is a foremost health problem worldwide, predisposing to increased mortality and morbidity. Undesirable effects of the current medications have prompted the researcher to develop more potential drug(s) against the disease. The peroxisome proliferator-activated receptors (PPARs) are members of the nuclear receptors family and take part in a vital role in the regulation of metabolic equilibrium. They can induce or repress genes associated with adipogenesis, lipid, and glucose metabolism. Aims: Investigation of PPARα/γ agonistic hits were screened by hierarchical virtual screening followed by molecular dynamics simulation and knowledge-based structure-activity relation (SAR) analysis using approved PPAR α/γ dual agonist. Methods: The PPARα/γ agonistic activity of compounds was searched by using Maestro through structure-based virtual screening and molecular dynamics (MD) simulation application. Virtual screening of nuclear-receptor ligands was done, and the binding modes with protein-ligand interactions of newer entity(s) were investigated. Further, binding energy prediction, Stability studies using molecular dynamics (MD) simulation of PPARα and γ complex was performed with the most promising hit along with the structural comparative analysis of approved PPARα/γ agonists with screened hit was done for knowledge-based SAR. Results and Discussion: The silicone chip-based approach recognized the most capable nine hits and had better predictive binding energy as compared to the reference drug compound (Tesaglitazar). In this study, the key amino acid residues of binding pockets of both targets PPARα/γ were acknowledged as essential and were found to be associated in the key interactions with the most potential dual hit (ChemDiv-3269-0443). Stability studies using molecular dynamics (MD) simulation of PPARα and γ complex was performed with the most promising hit and found root mean square deviation (RMSD) stabile around 2Å and 2.1Å, respectively. Frequency distribution data also revealed that the key residues of both proteins showed maximum contacts with a potent hit during the MD simulation of 20 nanoseconds (ns). The knowledge-based SAR studies of PPARα/γ agonists were studied using 2D structures of approved drugs like aleglitazar, tesaglitazar, etc. for successful designing and synthesis of compounds PPARγ agonistic candidates with anti-hyperlipidimic potential.Keywords: computational, diabetes, PPAR, simulation
Procedia PDF Downloads 1012907 Standard Model-Like Higgs Decay into Displaced Heavy Neutrino Pairs in U(1)' Models
Authors: E. Accomando, L. Delle Rose, S. Moretti, E. Olaiya, C. Shepherd-Themistocleous
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Heavy sterile neutrinos are almost ubiquitous in the class of Beyond Standard Model scenarios aimed at addressing the puzzle that emerged from the discovery of neutrino flavour oscillations, hence the need to explain their masses. In particular, they are necessary in a U(1)’ enlarged Standard Model (SM). We show that these heavy neutrinos can be rather long-lived producing distinctive displaced vertices and tracks. Indeed, depending on the actual decay length, they can decay inside a Large Hadron Collider (LHC) detector far from the main interaction point and can be identified in the inner tracking system or the muon chambers, emulated here through the Compact Muon Solenoid (CMS) detector parameters. Among the possible production modes of such heavy neutrino, we focus on their pair production mechanism in the SM Higgs decay, eventually yielding displaced lepton signatures following the heavy neutrino decays into weak gauge bosons. By employing well-established triggers available for the CMS detector and using the data collected by the end of the LHC Run 2, these signatures would prove to be accessible with negligibly small background. Finally, we highlight the importance that the exploitation of new triggers, specifically, displaced tri-lepton ones, could have for this displaced vertex search.Keywords: beyond the standard model, displaced vertex, Higgs physics, neutrino physics
Procedia PDF Downloads 1442906 Prediction Compressive Strength of Self-Compacting Concrete Containing Fly Ash Using Fuzzy Logic Inference System
Authors: Belalia Douma Omar, Bakhta Boukhatem, Mohamed Ghrici
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Self-compacting concrete (SCC) developed in Japan in the late 80s has enabled the construction industry to reduce demand on the resources, improve the work condition and also reduce the impact of environment by elimination of the need for compaction. Fuzzy logic (FL) approaches has recently been used to model some of the human activities in many areas of civil engineering applications. Especially from these systems in the model experimental studies, very good results have been obtained. In the present study, a model for predicting compressive strength of SCC containing various proportions of fly ash, as partial replacement of cement has been developed by using Adaptive Neuro-Fuzzy Inference System (ANFIS). For the purpose of building this model, a database of experimental data were gathered from the literature and used for training and testing the model. The used data as the inputs of fuzzy logic models are arranged in a format of five parameters that cover the total binder content, fly ash replacement percentage, water content, super plasticizer and age of specimens. The training and testing results in the fuzzy logic model have shown a strong potential for predicting the compressive strength of SCC containing fly ash in the considered range.Keywords: self-compacting concrete, fly ash, strength prediction, fuzzy logic
Procedia PDF Downloads 3342905 Application of Machine Learning Models to Predict Couchsurfers on Free Homestay Platform Couchsurfing
Authors: Yuanxiang Miao
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Couchsurfing is a free homestay and social networking service accessible via the website and mobile app. Couchsurfers can directly request free accommodations from others and receive offers from each other. However, it is typically difficult for people to make a decision that accepts or declines a request when they receive it from Couchsurfers because they do not know each other at all. People are expected to meet up with some Couchsurfers who are kind, generous, and interesting while it is unavoidable to meet up with someone unfriendly. This paper utilized classification algorithms of Machine Learning to help people to find out the Good Couchsurfers and Not Good Couchsurfers on the Couchsurfing website. By knowing the prior experience, like Couchsurfer’s profiles, the latest references, and other factors, it became possible to recognize what kind of the Couchsurfers, and furthermore, it helps people to make a decision that whether to host the Couchsurfers or not. The value of this research lies in a case study in Kyoto, Japan in where the author has hosted 54 Couchsurfers, and the author collected relevant data from the 54 Couchsurfers, finally build a model based on classification algorithms for people to predict Couchsurfers. Lastly, the author offered some feasible suggestions for future research.Keywords: Couchsurfing, Couchsurfers prediction, classification algorithm, hospitality tourism platform, hospitality sciences, machine learning
Procedia PDF Downloads 1312904 Effective Emergency Response and Disaster Prevention: A Decision Support System for Urban Critical Infrastructure Management
Authors: M. Shahab Uddin, Pennung Warnitchai
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Currently more than half of the world’s populations are living in cities, and the number and sizes of cities are growing faster than ever. Cities rely on the effective functioning of complex and interdependent critical infrastructures networks to provide public services, enhance the quality of life, and save the community from hazards and disasters. In contrast, complex connectivity and interdependency among the urban critical infrastructures bring management challenges and make the urban system prone to the domino effect. Unplanned rapid growth, increased connectivity, and interdependency among the infrastructures, resource scarcity, and many other socio-political factors are affecting the typical state of an urban system and making it susceptible to numerous sorts of diversion. In addition to internal vulnerabilities, urban systems are consistently facing external threats from natural and manmade hazards. Cities are not just complex, interdependent system, but also makeup hubs of the economy, politics, culture, education, etc. For survival and sustainability, complex urban systems in the current world need to manage their vulnerabilities and hazardous incidents more wisely and more interactively. Coordinated management in such systems makes for huge potential when it comes to absorbing negative effects in case some of its components were to function improperly. On the other hand, ineffective management during a similar situation of overall disorder from hazards devastation may make the system more fragile and push the system to an ultimate collapse. Following the quantum, the current research hypothesizes that a hazardous event starts its journey as an emergency, and the system’s internal vulnerability and response capacity determine its destination. Connectivity and interdependency among the urban critical infrastructures during this stage may transform its vulnerabilities into dynamic damaging force. An emergency may turn into a disaster in the absence of effective management; similarly, mismanagement or lack of management may lead the situation towards a catastrophe. Situation awareness and factual decision-making is the key to win a battle. The current research proposed a contextual decision support system for an urban critical infrastructure system while integrating three different models: 1) Damage cascade model which demonstrates damage propagation among the infrastructures through their connectivity and interdependency, 2) Restoration model, a dynamic restoration process of individual infrastructure, which is based on facility damage state and overall disruptions in surrounding support environment, and 3) Optimization model that ensures optimized utilization and distribution of available resources in and among the facilities. All three models are tightly connected, mutually interdependent, and together can assess the situation and forecast the dynamic outputs of every input. Moreover, this integrated model will hold disaster managers and decision makers responsible when it comes to checking all the alternative decision before any implementation, and support to produce maximum possible outputs from the available limited inputs. This proposed model will not only support to reduce the extent of damage cascade but will ensure priority restoration and optimize resource utilization through adaptive and collaborative management. Complex systems predictably fail but in unpredictable ways. System understanding, situation awareness, and factual decisions may significantly help urban system to survive and sustain.Keywords: disaster prevention, decision support system, emergency response, urban critical infrastructure system
Procedia PDF Downloads 2262903 Development of an Ecological Binder by Geopolymerization of Untreated Dredged Sediments
Authors: Lisa Monteiro, Jacqueline Saliba, Nadia Saiyouri, Humberto Y. Godoy
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Theevolution of the global environmental context incites companies to reduce their impact by reusing local materials and promoting circular economy. Dredged sediments represent a potential source of materials due to their large volume. Indeed, the dredging operations carried out in Gironde alone generated an annual volume of sediment of approximately 9 million m³. Moreover, on the eve of the evolution of laws concerning dredging practices, the recovery of sediments is necessary to create a viable economy for their management. This thesis work is oriented towards the development of an ecological binder from the fine fraction of untreated dredged sediments. In fact, their physico-chemical properties make them favorable for the synthesis of geopolymer, current competitor of cement, thanks to its lower carbon footprint and environmental impact. However, several obstacles must be overcome before implementing this new family of materials: the use of sediments without thermal or chemical treatment, the absence of a formulation approach, ignorance of the reactions produced, etc. During the first year of the thesis, a physico-chemical characterization of the sediments made it possible to validate their use as precursors forgeopolymerization according to three criteria: their fineness, their mineralogical composition, and the percentage of amorphous phase. Following these results, several formulations have been defined, taking into account the environmental impact. The sediments were activated with an alkaline solution of sodium hydroxide and sodium silicate. Two other formulations with cement and blast furnace slag have been defined for comparison. The results highlighted the possibility of forming geopolymers from untreated and still wet dredged sediments. The development of structural bonds through the formation of hydrated sodium aluminosilicate thus leads to higher strengths at 90 days (4.78 MPa) than a mixture with cement (0.75 MPa). A 30% gain in CO₂ emissions has also been obtained compared to cement. In order to reduce the uncertainties linked to the absence of a formulation approach, to optimize the number of experiments to be carried out in the laboratory, and to obtain an optimal formulation, an analysis by mixing plan was conducted in order to frame the responses according to the proportions of the constituents. Following the obtaining of an optimal binder, the work will focus on the study of the durability and the interspecific variability of the sediments on the mechanical properties by testing the binder developed with different sediments dredged from the Bordeaux estuary. , the Grand Port Maritime of Bayonne, La Rochelle, and the Bassinsd'Arcachon.Keywords: compressive strength, dredged sediments, ecological binder, geopolymers
Procedia PDF Downloads 982902 An In-Depth Study on the Experience of Novice Teachers
Authors: Tsafi Timor
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The research focuses on the exploration of the unique journey that novice teachers experience in their first year of teaching, among graduates of re-training programs into teaching. The study explores the experiences of success and failure and the factors that underpin positive experiences, as well as the journey (process) of this year with reference to the comparison between novice teachers and new immigrants. The content analysis that was adopted in the study was conducted on texts that were written by the teachers and detailed their first year of teaching. The findings indicate that experiences of success are featured by personal satisfaction, constant need of feedback, high motivation in challenging situations, and emotions. Failure experiences are featured by frustration, helplessness, sense of humiliation, feeling of rejection, and lack of efficacy. Factors that promote and inhibit positive experiences relate to personal, personality, professional and organizational levels. Most teachers reported feeling like new immigrants, and demonstrated different models of the process of the first year of teaching. Further research is recommended on the factors that promote and inhibit positive experiences, and on 'The Missing Link' of the relationship between Teacher Education Programs and the practices in schools.Keywords: first-year teaching, novice teachers, school practice, teacher education programs
Procedia PDF Downloads 2902901 Spatial Assessment of Soil Contamination from Informal E-Waste Recycling Site in Agbogbloshie, Ghana
Authors: Kyere Vincent Nartey, Klaus Greve, Atiemo Sampson
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E-waste is discarded electrical electronic equipment inclusive of all components, sub-assemblies and consumables which are part of the product at the time of discarding and known to contain both hazardous and valuable fractions. E-waste is recycled within the proposed ecological restoration of the Agbogbloshie enclave using crude and rudimental recycling procedures such as open burning and manual dismantling which result in pollution and contamination of soil, water and air. Using GIS, this study was conducted to examine the spatial distribution and extent of soil contamination by heavy metals from the e-waste recycling site in Agbogbloshie. From the month of August to November 2013, 146 soil samples were collected in addition to their coordinates using GPS. Elemental analysis performed on the collected soil samples using X-Ray fluorescence revealed over 30 elements including, Ni, Cr, Zn, Cu, Pb and Mn. Using geostatistical techniques in ArcGIS 10.1 spatial assessment and distribution maps were generated. Mathematical models or equations were used to estimate the degree of contamination and pollution index. Results from soil analysis from the Agbogbloshie enclave showed that levels of measured or observed elements were significantly higher than the Canadian EPA and Dutch environmental standards.Keywords: e-waste, geostatistics, soil contamination, spatial distribution
Procedia PDF Downloads 5132900 In vitro Cytotoxic and Genotoxic Effects of Arsenic Trioxide on Human Keratinocytes
Authors: H. Bouaziz, M. Sefi, J. de Lapuente, M. Borras, N. Zeghal
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Although arsenic trioxide has been the subject of toxicological research, in vitro cytotoxicity and genotoxicity studies using relevant cell models and uniform methodology are not well elucidated. Hence, the aim of the present study was to evaluate the cytotoxicity and genotoxicity induced by arsenic trioxide in human keratinocytes (HaCaT) using the MTT [3-(4, 5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] and alkaline single cell gel electrophoresis (Comet) assays, respectively. Human keratinocytes were treated with different doses of arsenic trioxide for 4 h prior to cytogenetic assessment. Data obtained from the MTT assay indicated that arsenic trioxide significantly reduced the viability of HaCaT cells in a dose-dependent manner, showing a IC50 value of 34.18 ± 0.6 µM. Data generated from the comet assay also indicated a significant dose-dependent increase in DNA damage in HaCaT cells associated with arsenic trioxide exposure. We observed a significant increase in comet tail length and tail moment, showing an evidence of arsenic trioxide -induced genotoxic damage in HaCaT cells. This study confirms that the comet assay is a sensitive and effective method to detect DNA damage caused by arsenic.Keywords: arsenic trioxide, cytotoxixity, genotoxicity, HaCaT
Procedia PDF Downloads 2552899 Taleghan Dam Break Numerical Modeling
Authors: Hamid Goharnejad, Milad Sadeghpoor Moalem, Mahmood Zakeri Niri, Leili Sadeghi Khalegh Abadi
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While there are many benefits to using reservoir dams, their break leads to destructive effects. From the viewpoint of International Committee of Large Dams (ICOLD), dam break means the collapse of whole or some parts of a dam; thereby the dam will be unable to hold water. Therefore, studying dam break phenomenon and prediction of its behavior and effects reduces losses and damages of the mentioned phenomenon. One of the most common types of reservoir dams is embankment dam. Overtopping in embankment dams occurs because of flood discharge system inability in release inflows to reservoir. One of the most important issues among managers and engineers to evaluate the performance of the reservoir dam rim when sliding into the storage, creating waves is large and long. In this study, the effects of floods which caused the overtopping of the dam have been investigated. It was assumed that spillway is unable to release the inflow. To determine outflow hydrograph resulting from dam break, numerical model using Flow-3D software and empirical equations was used. Results of numerical models and their comparison with empirical equations show that numerical model and empirical equations can be used to study the flood resulting from dam break.Keywords: embankment dam break, empirical equations, Taleghan dam, Flow-3D numerical model
Procedia PDF Downloads 3212898 Chemical Fabrication of Gold Nanorings: Controlled Reduction and Optical Tuning for Nanomedicine Applications
Authors: Mehrnaz Mostafavi, Jalaledin Ghanavi
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This research investigates the production of nanoring structures through a chemical reduction approach, exploring gradual reduction processes assisted by reductant agents, leading to the formation of these specialized nanorings. The study focuses on the controlled reduction of metal atoms within these agents, crucial for shaping these nanoring structures over time. The paper commences by highlighting the wide-ranging applications of metal nanostructures across fields like Nanomedicine, Nanobiotechnology, and advanced spectroscopy methods such as Surface Enhanced Raman Spectroscopy (SERS) and Surface Enhanced Infrared Absorption Spectroscopy (SEIRA). Particularly, gold nanoparticles, especially in the nanoring configuration, have gained significant attention due to their distinctive properties, offering accessible spaces suitable for sensing and spectroscopic applications. The methodology involves utilizing human serum albumin as a reducing agent to create gold nanoparticles through a chemical reduction process. This process involves the transfer of electrons from albumin's carboxylic groups, converting them into carbonyl, while AuCl4− acquires electrons to form gold nanoparticles. Various characterization techniques like Ultraviolet–visible spectroscopy (UV-Vis), Atomic-force microscopy (AFM), and Transmission electron microscopy (TEM) were employed to examine and validate the creation and properties of the gold nanoparticles and nanorings. The findings suggest that precise and gradual reduction processes, in conjunction with optimal pH conditions, play a pivotal role in generating nanoring structures. Experiments manipulating optical properties revealed distinct responses in the visible and infrared spectrums, demonstrating the tunability of these nanorings. Detailed examinations of the morphology confirmed the formation of gold nanorings, elucidating their size, distribution, and structural characteristics. These nanorings, characterized by an empty volume enclosed by uniform walls, exhibit promising potential in the realms of Nanomedicine and Nanobiotechnology. In summary, this study presents a chemical synthesis approach using organic reducing agents to produce gold nanorings. The results underscore the significance of controlled and gradual reduction processes in crafting nanoring structures with unique optical traits, offering considerable value across diverse nanotechnological applications.Keywords: nanoring structures, chemical reduction approach, gold nanoparticles, spectroscopy methods, nano medicine applications
Procedia PDF Downloads 1332897 IT Perspective of Service-Oriented e-Government Enterprise
Authors: Anu Paul, Varghese Paul
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The focal aspire of e-Government (eGovt) is to offer citizen-centered service delivery. Accordingly, the citizenry consumes services from multiple government agencies through national portal. Thus, eGovt is an enterprise with the primary business motive of transparent, efficient and effective public services to its citizenry and its logical structure is the eGovernment Enterprise Architecture (eGEA). Since eGovt is IT oriented multifaceted service-centric system, EA doesn’t do much on an automated enterprise other than the business artifacts. Service-Oriented Architecture (SOA) manifestation led some governments to pertain this in their eGovts, but it limits the source of business artifacts. The concurrent use of EA and SOA in eGovt executes interoperability and integration and leads to Service-Oriented e-Government Enterprise (SOeGE). Consequently, agile eGovt system becomes a reality. As an IT perspective eGovt comprises of centralized public service artifacts with the existing application logics belong to various departments at central, state and local level. The eGovt is renovating to SOeGE by apply the Service-Orientation (SO) principles in the entire system. This paper explores IT perspective of SOeGE in India which encompasses the public service models and illustrated with a case study the Passport service of India.Keywords: enterprise architecture, service-oriented e-Government enterprise, service interface layer, service model
Procedia PDF Downloads 5202896 Prediction of the Torsional Vibration Characteristics of a Rotor-Shaft System Using Its Scale Model and Scaling Laws
Authors: Jia-Jang Wu
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This paper presents the scaling laws that provide the criteria of geometry and dynamic similitude between the full-size rotor-shaft system and its scale model, and can be used to predict the torsional vibration characteristics of the full-size rotor-shaft system by manipulating the corresponding data of its scale model. The scaling factors, which play fundamental roles in predicting the geometry and dynamic relationships between the full-size rotor-shaft system and its scale model, for torsional free vibration problems between scale and full-size rotor-shaft systems are firstly obtained from the equation of motion of torsional free vibration. Then, the scaling factor of external force (i.e., torque) required for the torsional forced vibration problems is determined based on the Newton’s second law. Numerical results show that the torsional free and forced vibration characteristics of a full-size rotor-shaft system can be accurately predicted from those of its scale models by using the foregoing scaling factors. For this reason, it is believed that the presented approach will be significant for investigating the relevant phenomenon in the scale model tests.Keywords: torsional vibration, full-size model, scale model, scaling laws
Procedia PDF Downloads 3932895 Using Bidirectional Encoder Representations from Transformers to Extract Topic-Independent Sentiment Features for Social Media Bot Detection
Authors: Maryam Heidari, James H. Jones Jr.
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Millions of online posts about different topics and products are shared on popular social media platforms. One use of this content is to provide crowd-sourced information about a specific topic, event or product. However, this use raises an important question: what percentage of information available through these services is trustworthy? In particular, might some of this information be generated by a machine, i.e., a bot, instead of a human? Bots can be, and often are, purposely designed to generate enough volume to skew an apparent trend or position on a topic, yet the consumer of such content cannot easily distinguish a bot post from a human post. In this paper, we introduce a model for social media bot detection which uses Bidirectional Encoder Representations from Transformers (Google Bert) for sentiment classification of tweets to identify topic-independent features. Our use of a Natural Language Processing approach to derive topic-independent features for our new bot detection model distinguishes this work from previous bot detection models. We achieve 94\% accuracy classifying the contents of data as generated by a bot or a human, where the most accurate prior work achieved accuracy of 92\%.Keywords: bot detection, natural language processing, neural network, social media
Procedia PDF Downloads 1152894 Using Blockchain Technology to Extend the Vendor Managed Inventory for Sustainability
Authors: Elham Ahmadi, Roshaali Khaturia, Pardis Sahraei, Mohammad Niyayesh, Omid Fatahi Valilai
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Nowadays, Information Technology (IT) is changing the way traditional enterprise management concepts work. One of the most dominant IT achievements is the Blockchain Technology. This technology enables the distributed collaboration of stakeholders for their interactions while fulfilling the security and consensus rules among them. This paper has focused on the application of Blockchain technology to enhance one of traditional inventory management models. The Vendor Managed Inventory (VMI) has been considered one of the most efficient mechanisms for vendor inventory planning by the suppliers. While VMI has brought competitive advantages for many industries, however its centralized mechanism limits the collaboration of a pool of suppliers and vendors simultaneously. This paper has studied the recent research for VMI application in industries and also has investigated the applications of Blockchain technology for decentralized collaboration of stakeholders. Focusing on sustainability issue for total supply chain consisting suppliers and vendors, it has proposed a Blockchain based VMI conceptual model. The different capabilities of this model for enabling the collaboration of stakeholders while maintaining the competitive advantages and sustainability issues have been discussed.Keywords: vendor managed inventory, VMI, blockchain technology, supply chain planning, sustainability
Procedia PDF Downloads 2222893 Real-Time Network Anomaly Detection Systems Based on Machine-Learning Algorithms
Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez
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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data-set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.Keywords: temporal graph network, anomaly detection, cyber security, IDS
Procedia PDF Downloads 1022892 Toward Concerned Leadership: A Novel Conceptual Model to Raise the Well-Being of Employees and the Leaderful Practice of Organizations
Authors: Robert McGrath, Zara Qureshi
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A innovative leadership philosophy that is proposed herein is distinctly more humane than most leadership approaches Concerned Leadership. The central idea to this approach is to consider the whole person that comes to work; their professional skills and talents, as well as any personal, emotional challenges that could be affecting productivity and effectiveness at work. This paper explores Concerned Leadership as an integration of the two conceptual models areas examined in this paper –(1) leaderful organizations and practices, as well as (2) organizational culture, and defines leadership in the context of Mental Health and Wellness in the workplace. Leaderful organizations calls for organizations to implement leaderful practice. Leaderful practice is when leadership responsibility and decision-making is shared across all team members and levels, versus only delegated to top management as commonly seen. A healthy culture thrives off key aspects such as acceptance, employee pride, equal opportunity, and strong company leadership. Concerned Leadership is characterized by five main components: Self-Concern, Leaderful Practice, Human Touch, Belonging, and Compassion. As scholars and practitioners conceptualize leadership in practice, the present model seeks to uphold the dignity of each organizational member, thereby having the potential to transform workplaces and support all members.Keywords: leadership, mental health, reflective practice, organizational culture
Procedia PDF Downloads 802891 Safety Approach Highway Alignment Optimization
Authors: Seyed Abbas Tabatabaei, Marjan Naderan Tahan, Arman Kadkhodai
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An efficient optimization approach, called feasible gate (FG), is developed to enhance the computation efficiency and solution quality of the previously developed highway alignment optimization (HAO) model. This approach seeks to realistically represent various user preferences and environmentally sensitive areas and consider them along with geometric design constraints in the optimization process. This is done by avoiding the generation of infeasible solutions that violate various constraints and thus focusing the search on the feasible solutions. The proposed method is simple, but improves significantly the model’s computation time and solution quality. On the other, highway alignment optimization through Feasible Gates, eventuates only economic model by considering minimum design constrains includes minimum reduce of circular curves, minimum length of vertical curves and road maximum gradient. This modelling can reduce passenger comfort and road safety. In most of highway optimization models, by adding penalty function for each constraint, final result handles to satisfy minimum constraint. In this paper, we want to propose a safety-function solution by introducing gift function.Keywords: safety, highway geometry, optimization, alignment
Procedia PDF Downloads 4082890 Risk Based Building Information Modeling (BIM) for Urban Infrastructure Transportation Project
Authors: Debasis Sarkar
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Building Information Modeling (BIM) is a holistic documentation process for operational visualization, design coordination, estimation and project scheduling. BIM software defines objects parametrically and it is a tool for virtual reality. Primary advantage of implementing BIM is the visual coordination of the building structure and systems such as Mechanical, Electrical and Plumbing (MEP) and it also identifies the possible conflicts between the building systems. This paper is an attempt to develop a risk based BIM model which would highlight the primary advantages of application of BIM pertaining to urban infrastructure transportation project. It has been observed that about 40% of the Architecture, Engineering and Construction (AEC) companies use BIM but primarily for their outsourced projects. Also, 65% of the respondents agree that BIM would be used quiet strongly for future construction projects in India. The 3D models developed with Revit 2015 software would reduce co-ordination problems amongst the architects, structural engineers, contractors and building service providers (MEP). Integration of risk management along with BIM would provide enhanced co-ordination, collaboration and high probability of successful completion of the complex infrastructure transportation project within stipulated time and cost frame.Keywords: building information modeling (BIM), infrastructure transportation, project risk management, underground metro rail
Procedia PDF Downloads 3092889 Fast Adjustable Threshold for Uniform Neural Network Quantization
Authors: Alexander Goncharenko, Andrey Denisov, Sergey Alyamkin, Evgeny Terentev
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The neural network quantization is highly desired procedure to perform before running neural networks on mobile devices. Quantization without fine-tuning leads to accuracy drop of the model, whereas commonly used training with quantization is done on the full set of the labeled data and therefore is both time- and resource-consuming. Real life applications require simplification and acceleration of quantization procedure that will maintain accuracy of full-precision neural network, especially for modern mobile neural network architectures like Mobilenet-v1, MobileNet-v2 and MNAS. Here we present a method to significantly optimize training with quantization procedure by introducing the trained scale factors for discretization thresholds that are separate for each filter. Using the proposed technique, we quantize the modern mobile architectures of neural networks with the set of train data of only ∼ 10% of the total ImageNet 2012 sample. Such reduction of train dataset size and small number of trainable parameters allow to fine-tune the network for several hours while maintaining the high accuracy of quantized model (accuracy drop was less than 0.5%). Ready-for-use models and code are available in the GitHub repository.Keywords: distillation, machine learning, neural networks, quantization
Procedia PDF Downloads 324