Search results for: conflict potential
7350 Application of Artificial Neural Network for Prediction of High Tensile Steel Strands in Post-Tensioned Slabs
Authors: Gaurav Sancheti
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This study presents an impacting approach of Artificial Neural Networks (ANNs) in determining the quantity of High Tensile Steel (HTS) strands required in post-tensioned (PT) slabs. Various PT slab configurations were generated by varying the span and depth of the slab. For each of these slab configurations, quantity of required HTS strands were recorded. ANNs with backpropagation algorithm and varying architectures were developed and their performance was evaluated in terms of Mean Square Error (MSE). The recorded data for the quantity of HTS strands was used as a feeder database for training the developed ANNs. The networks were validated using various validation techniques. The results show that the proposed ANNs have a great potential with good prediction and generalization capability.Keywords: artificial neural networks, back propagation, conceptual design, high tensile steel strands, post tensioned slabs, validation techniques
Procedia PDF Downloads 2257349 One-Step Synthesis of Fluorescent Carbon Dots in a Green Way as Effective Fluorescent Probes for Detection of Iron Ions and pH Value
Authors: Mostafa Ghasemi, Andrew Urquhart
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In this study, fluorescent carbon dots (CDs) were synthesized in a green way using a one-step hydrothermal method. Carbon dots are carbon-based nanomaterials with a size of less than 10 nm, unique structure, and excellent properties such as low toxicity, good biocompatibility, tunable fluorescence, excellent photostability, and easy functionalization. These properties make them a good candidate to use in different fields such as biological sensing, photocatalysis, photodynamic, and drug delivery. Fourier transformed infrared (FTIR) spectra approved OH/NH groups on the surface of the as-synthesized CDs, and UV-vis spectra showed excellent fluorescence quenching effect of Fe (III) ion on the as-synthesized CDs with high selectivity detection compared with other metal ions. The probe showed a linear response concentration range (0–2.0 mM) to Fe (III) ion, and the limit of detection was calculated to be about 0.50 μM. In addition, CDs also showed good sensitivity to the pH value in the range from 2 to 14, indicating great potential as a pH sensor.Keywords: carbon dots, fluorescence, pH sensing, metal ions sensor
Procedia PDF Downloads 787348 Absorption Capability Examination of Heavy Metals by Spirogyra Alga in Ahvaz Water Treatment Plant
Authors: F. Fakheri Raof, F. Zobeidizadeh
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The present study examined the potential capability of Spirogyra algae remove heavy metals Zn, Pb, Cu, and Cr from the water. For this purpose, the water treatment No. 3 of Ahvaz County in Khuzestan Province of Iran was selected as a case study. From 8 sampling stations, 4 stations were dedicated to the water samples and 4 stations to the algae samples. According to the obtained results, the concentration of the heavy metals Cr, Cu, Pb, and Zn in water samples were within the ranges of 1.98-19.53, 0.67-13.45, 1-23.18, and 2.12-83.04 µg/L. Besides, the concentration of heavy metal Cr, Pb, Cu, and Zn in spirogyra algae samples varied between the ranges 2.30-3.61, 2.06-3.43, 2.29-2.56, and 9.88-10.84 µg/L. The highest amount of metal absorption in spirogyra algae samples was related to the zinc. The obtained results also indicated that the last spirogyra algae sample which was at the inlet of Tank 4 absorbed the lowest concentration of metals. This would be due to the treatment process along the course of ponds resulted in completely pure water at the outlet without the existence of algae on the sides. The paper also provides some useful recommendations on this issue.Keywords: absorption, Ahvaz, heavy metal, spirogyra algae, water treatment plants
Procedia PDF Downloads 2697347 Design of an Automated Deep Learning Recurrent Neural Networks System Integrated with IoT for Anomaly Detection in Residential Electric Vehicle Charging in Smart Cities
Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun
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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids
Procedia PDF Downloads 687346 Using Machine Learning to Predict Answers to Big-Five Personality Questions
Authors: Aadityaa Singla
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The big five personality traits are as follows: openness, conscientiousness, extraversion, agreeableness, and neuroticism. In order to get an insight into their personality, many flocks to these categories, which each have different meanings/characteristics. This information is important not only to individuals but also to career professionals and psychologists who can use this information for candidate assessment or job recruitment. The links between AI and psychology have been well studied in cognitive science, but it is still a rather novel development. It is possible for various AI classification models to accurately predict a personality question via ten input questions. This would contrast with the hundred questions that normal humans have to answer to gain a complete picture of their five personality traits. In order to approach this problem, various AI classification models were used on a dataset to predict what a user may answer. From there, the model's prediction was compared to its actual response. Normally, there are five answer choices (a 20% chance of correct guess), and the models exceed that value to different degrees, proving their significance. By utilizing an MLP classifier, decision tree, linear model, and K-nearest neighbors, they were able to obtain a test accuracy of 86.643, 54.625, 47.875, and 52.125, respectively. These approaches display that there is potential in the future for more nuanced predictions to be made regarding personality.Keywords: machine learning, personally, big five personality traits, cognitive science
Procedia PDF Downloads 1487345 Biosynthesis of Titanium Dioxide Nanoparticles and Their Antibacterial Property
Authors: Prachi Singh
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This paper presents a low-cost, eco-friendly and reproducible microbe mediated biosynthesis of TiO2 nanoparticles. TiO2 nanoparticles synthesized using the bacterium, Bacillus subtilis, from titanium as a precursor, were confirmed by TEM analysis. The morphological characteristics state spherical shape, with the size of individual or aggregate nanoparticles, around 30-40 nm. Microbial resistance represents a challenge for the scientific community to develop new bioactive compounds. Here, the antibacterial effect of TiO2 nanoparticles on Escherichia coli was investigated, which was confirmed by CFU (Colony-forming unit). Further, growth curve study of E. coli Hb101 in the presence and absence of TiO2 nanoparticles was done. Optical density decrease was observed with the increase in the concentration of TiO2. It could be attributed to the inactivation of cellular enzymes and DNA by binding to electron-donating groups such as carboxylates, amides, indoles, hydroxyls, thiols, etc. which cause little pores in bacterial cell walls, leading to increased permeability and cell death. This justifies that TiO2 nanoparticles have efficient antibacterial effect and have potential to be used as an antibacterial agent for different purposes.Keywords: antibacterial effect, CFU, Escherichia coli Hb101, growth curve, TEM, TiO2 nanoparticle, Toxicity, UV-Vis
Procedia PDF Downloads 2987344 Strategies to Accelerate Indonesian Halal Food Export to the Japan Market
Authors: Ferry Syarifuddin
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The potential for growth in the Japanese halal industry is promising, especially for the export of processed food products, due to the significant increase in the Muslim population over the past decade. Japan is also the second largest destination for processed food export from developing countries. However, there has been a decline in the export of processed food from Indonesia, a Muslim-majority developing country, to Japan, dropping from $350 million in 2019 to $119 million in 2023. To address this issue, this study aims to assess the strengths, weaknesses, opportunities, and threats (SWOT) of Indonesian halal processed food products export to the Japanese market, investigate successful strategies employed by other countries and recommend the most prioritized strategy for exporting Indonesian halal processed food products to the Japan market. Our findings identify collaborating with Japan's food industry associations and trade organizations as the key strategy for successful export to the Japanese market.Keywords: ANP-SWOT, export strategy, halal product, Japan market
Procedia PDF Downloads 537343 Modeling of a Concentrating Photovoltaic Module with and without Cooling System
Authors: Intissar Benrhouma, Marta Victoria, Ignacio Anton, Bechir Chaouachi
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Concentrating photovoltaic systems CPV use optical elements, such as Fresnel lenses, to concentrate solar intensity. The concentrated solar energy is delivered to the solar cell from 20 to 100 W/cm². Some of this energy is converted to electricity, while the rest must be disposed of as a residual heat. Solar cells cooling should be a necessary part of CPV modeling because these systems allowed increasing the power received by the cell. This high power can rise the electrons’ potential causing the heating of the cell, which reduces the global module’s efficiency. This work consists of modeling a concentrating photovoltaic module with and without a cooling system. We have established a theoretical model based on energy balances carried out on a photovoltaic module using solar radiation concentration cells. Subsequently, we developed a calculation program on Matlab which allowed us to simulate the functioning of this module. The obtained results show that the addition of a cooling system to the module improves greatly the performance of our CPV system.Keywords: solar energy, photovoltaic, concentration, cooling, performance improvement
Procedia PDF Downloads 4027342 Physical Characteristics of Cookies Enriched with Microencapsulated Cherry Pomace Extract
Authors: Jovana Petrović, Ivana Lončarević, Vesna Tumbas Šaponjac, Biljana Pajin, Danica Zarić
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Pomace, a by-product from fruit processing industry is the potential source of valuable bioactive. Cookies are popular, ready to eat and low price foods; therefore, enrichment of these products is of great importance. In this work, bioactive compounds extracted from cherry pomace, encapsulated in soy and whey proteins, have been incorporated in cookies, replacing 10 (SP10 and WP10) and 15% of wheat flour (SP15 and WP15). Cookie geometry (diameter (D), thickness (T) and spread ratio (D/T)), cookie weight, cookie hardness and cookie surface colour were measured. Sensory characteristics are also examined. The results show that encapsulated cherry pomace bioactives have positively influenced the cookie mass. Diameter, redness (a* value) and cookie hardness increased. Sensory evaluation of cookies, revealed that up to 15% substitution of wheat flour with WP encapsulate produced acceptable cookies similar to the control (100% wheat flour) cookies.Keywords: cherry pomace, polyphenols, microencapsulation, cookies, physical characteristics
Procedia PDF Downloads 4717341 Capture of Co₂ From Natural Gas Using Modified Imidazolium Ionic Liquids
Authors: Alaa A. Ghanem, S. E. M. Desouky
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Natural gas (NG) is considered one of the most essential global energy sources. NG fields are often far away from the market, and a long-distance transporting pipeline usually is required. Production of NG with high content of CO₂ leads to severe problems such as equipment corrosion along with the production line until refinery.in addition to a high level of toxicity and decreasing in calorific value of the NG. So it is recommended to remove or decrease the CO₂ percent to meet transport specifications. This can be reached using different removal techniques such as physical and chemical absorption, pressure swing adsorption, membrane separation, or low-temperature separation. Many solvents and chemicals are being used to capture carbon dioxide on a large scale; among them, Ionic liquids have great potential due to their tunable properties; low vapour pressure, low melting point, and sensible thermal stability. In this research, three modifiedimidazolium ionic liquids will be synthesized and characterized using different tools of analysis such as FT-IR, 1H NMR. Thermal stability and surface activity will be studied. The synthesized compounds will be evaluated as selective solvents for CO₂ removal from natural gas using PVT cell.Keywords: natural gas, CO₂ capture, imidazolium ionic liquid, PVT cell
Procedia PDF Downloads 1777340 Adoption of Big Data by Global Chemical Industries
Authors: Ashiff Khan, A. Seetharaman, Abhijit Dasgupta
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The new era of big data (BD) is influencing chemical industries tremendously, providing several opportunities to reshape the way they operate and help them shift towards intelligent manufacturing. Given the availability of free software and the large amount of real-time data generated and stored in process plants, chemical industries are still in the early stages of big data adoption. The industry is just starting to realize the importance of the large amount of data it owns to make the right decisions and support its strategies. This article explores the importance of professional competencies and data science that influence BD in chemical industries to help it move towards intelligent manufacturing fast and reliable. This article utilizes a literature review and identifies potential applications in the chemical industry to move from conventional methods to a data-driven approach. The scope of this document is limited to the adoption of BD in chemical industries and the variables identified in this article. To achieve this objective, government, academia, and industry must work together to overcome all present and future challenges.Keywords: chemical engineering, big data analytics, industrial revolution, professional competence, data science
Procedia PDF Downloads 897339 Digital Image Correlation Based Mechanical Response Characterization of Thin-Walled Composite Cylindrical Shells
Authors: Sthanu Mahadev, Wen Chan, Melanie Lim
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Anisotropy dominated continuous-fiber composite materials have garnered attention in numerous mechanical and aerospace structural applications. Tailored mechanical properties in advanced composites can exhibit superiority in terms of stiffness-to-weight ratio, strength-to-weight ratio, low-density characteristics, coupled with significant improvements in fatigue resistance as opposed to metal structure counterparts. Extensive research has demonstrated their core potential as more than just mere lightweight substitutes to conventional materials. Prior work done by Mahadev and Chan focused on formulating a modified composite shell theory based prognosis methodology for investigating the structural response of thin-walled circular cylindrical shell type composite configurations under in-plane mechanical loads respectively. The prime motivation to develop this theory stemmed from its capability to generate simple yet accurate closed-form analytical results that can efficiently characterize circular composite shell construction. It showcased the development of a novel mathematical framework to analytically identify the location of the centroid for thin-walled, open cross-section, curved composite shells that were characterized by circumferential arc angle, thickness-to-mean radius ratio, and total laminate thickness. Ply stress variations for curved cylindrical shells were analytically examined under the application of centric tensile and bending loading. This work presents a cost-effective, small-platform experimental methodology by taking advantage of the full-field measurement capability of digital image correlation (DIC) for an accurate assessment of key mechanical parameters such as in-plane mechanical stresses and strains, centroid location etc. Mechanical property measurement of advanced composite materials can become challenging due to their anisotropy and complex failure mechanisms. Full-field displacement measurements are well suited for characterizing the mechanical properties of composite materials because of the complexity of their deformation. This work encompasses the fabrication of a set of curved cylindrical shell coupons, the design and development of a novel test-fixture design and an innovative experimental methodology that demonstrates the capability to very accurately predict the location of centroid in such curved composite cylindrical strips via employing a DIC based strain measurement technique. Error percentage difference between experimental centroid measurements and previously estimated analytical centroid results are observed to be in good agreement. The developed analytical modified-shell theory provides the capability to understand the fundamental behavior of thin-walled cylindrical shells and offers the potential to generate novel avenues to understand the physics of such structures at a laminate level.Keywords: anisotropy, composites, curved cylindrical shells, digital image correlation
Procedia PDF Downloads 3187338 Seed Germination and Recovery Responses of Suaeda Heterophylla to Abiotic Stresses
Authors: Abdul Hameed, Muhammad Zaheer Ahmed, Salman Gulzar, Bilquees Gul, Jan Alam, Ahmad K. Hegazy, Abdel Rehman A. Alatar, M. Ajmal Khan
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Seed germination and recovery from salt stress of an annual halophyte Suaeda heterophylla (Kar. and Kir.) Bunge to different iso-osmotic concentrations (0, -0.46, -0.92, -1.38, -1.84, and -2.30 MPa) of NaCl and PEG-6000 at 15/25, 20/30 and 25/35°C in both 12-h temperature and light regimes and in complete darkness were studied. Maximum number of seeds germinated in distilled water and increase in concentrations of both NaCl and PEG-6000 decreased germination at all temperature regimes, light and dark conditions, with higher inhibition in NaCl than PEG-6000. Recovery of germination and viability of seeds were lower in NaCl than PEG-6000 both in the light and dark. Moderate alternate temperatures (20/30°C) and 12-h photoperiod were found to be the optimal for seed germination and recovery. Better seed germination of S. heterophylla when osmotic potential caused both by NaCl and PEG 6000 is lower, temperature regime of 20/30°C and light regime is for 12 h.Keywords: seed germination, abiotic stresses, Suaeda heterophylla, molecular biology
Procedia PDF Downloads 4437337 Australian Teachers and School Leaders’ Use of Differentiated Learning Experiences as Responsive Teaching for Students with ADHD
Authors: Kathy Gibbs
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There is a paucity of research in Australia about educators’ use of differentiated instruction (DI) to support the learning of students with ADHD. This study reports on small-scale, qualitative research using interviews with teachers and school leaders to identify how they use DI as an effective teaching instruction for students with ADHD. Findings showed that teachers and school leaders have a good understanding of ADHD; teachers use DI as an effective teaching practice to enhance learning for this student group and ensure the classroom environment is safe and secure. However, they do not adjust assessments for students with ADHD. School leaders are not clear on how teachers differentiate assessments or adapt to the classroom environment. These results highlight the need for further research at the teacher and teacher-educator level teachers to ensure teaching practices are effective in reducing unwanted behaviours that prevent students with ADHD from achieving their full academic potential.Keywords: teachers, differentiated instruction, ADHD, student learning, educators knowledge
Procedia PDF Downloads 567336 Negative Perceptions of Ageing Predicts Greater Dysfunctional Sleep Related Cognition Among Adults Aged 60+
Authors: Serena Salvi
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Ageistic stereotypes and practices have become a normal and therefore pervasive phenomenon in various aspects of everyday life. Over the past years, renewed awareness towards self-directed age stereotyping in older adults has given rise to a line of research focused on the potential role of attitudes towards ageing on seniors’ health and functioning. This set of studies has showed how a negative internalisation of ageistic stereotypes would discourage older adults in seeking medical advice, in addition to be associated to negative subjective health evaluation. An important dimension of mental health that is often affected in older adults is represented by sleep quality. Self-reported sleep quality among older adults has shown to be often unreliable when compared to their objective sleep measures. Investigations focused on self-reported sleep quality among older adults have suggested how this portion of the population would tend to accept disrupted sleep if believed to be up to standard for their age. On the other hand, unrealistic expectations, and dysfunctional beliefs towards sleep in ageing, might prompt older adults to report sleep disruption even in the absence of objective disrupted sleep. Objective of this study is to examine an association between personal attitudes towards ageing in adults aged 60+ and dysfunctional sleep related cognition. More in detail, this study aims to investigate a potential association between personal attitudes towards ageing, sleep locus of control and dysfunctional beliefs towards sleep among this portion of the population. Data in this study were statistically analysed in SPSS software. Participants were recruited through the online participants recruitment system Prolific. Inclusion of attention check questions throughout the questionnaire and consistency of responses were looked at. Prior to the commencement of this study, Ethical Approval was granted (ref. 39396). Descriptive statistics were used to determine the frequency, mean, and SDs of the variables. Pearson coefficient was used for interval variables, independent T-test for comparing means between two independent groups, analysis of variance (ANOVA) test for comparing the means in several independent groups, and hierarchical linear regression models for predicting criterion variables based on predictor variables. In this study self-perceptions of ageing were assessed using APQ-B’s subscales, while dysfunctional sleep related cognition was operationalised using the SLOC and the DBAS16 scales. Of the final subscales taken in consideration in the brief version of the APQ questionnaire, Emotional Representations (ER), Control Positive (PC) and Control and Consequences Negative (NC) have shown to be of particularly relevance for the remits of this study. Regression analysis show how an increase in the APQ-B subscale Emotional Representations (ER) predicts an increase in dysfunctional beliefs and attitudes towards sleep in this sample, after controlling for subjective sleep quality, level of depression and chronological age. A second regression analysis showed that APQ-B subscales Control Positive (PC) and Control and Consequences Negative (NC) were significant predictors in the change of variance of SLOC, after controlling for subjective sleep quality, level of depression and dysfunctional beliefs about sleep.Keywords: sleep-related cognition, perceptions of aging, older adults, sleep quality
Procedia PDF Downloads 1057335 Evaluation of Mango Seed Extract as Surfactant for Enhanced Oil Recovery
Authors: Ezzaddin Rashid Hussein
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This research investigates the viability of mango seed extract (MSE) using a surfactant to improve oil recovery (EOR). This research examines MSE-based surfactant solutions and compares them to more traditional synthetic surfactants in terms of phase behaviour and interfacial tension. The phase behaviour and interfacial tension of five samples of surfactant solutions with different concentrations were measured. Samples 1 (2.0 g) and 1 (1.5 g) performed closest to the critical micelle concentration (CMC) and displayed the greatest decrease in surface tension, according to the results. In addition, the measurement of IFT, contact angle, and pH, as well as comparison with prior research, highlights the potential environmental benefits of MSMEs as an eco-friendly alternative. It is recommended that additional research be conducted to assess their stability and behaviour under reservoir conditions. Overall, mango seed extract demonstrates promise as a natural and sustainable surfactant for enhancing oil recovery, paving the way for eco-friendly enhanced oil recovery techniques.Keywords: oil and gas, mango seed powder, surfactants, enhanced oil recovery, interfacial tension IFT, wettability, contacts angle, phase behavior, pH
Procedia PDF Downloads 847334 Dambreak Flood Analysis Using HEC-RAS and GIS Technologies
Authors: Oussama Derdous, Lakhdar Djemili, Hamza Bouchehed
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The potential risks associated with dam break flooding could be considerable and result in major damage, including loss of life and property destruction. In the past, Algeria experienced such flood disasters; let’s recall the failure of Fergoug dam in 1881, this accident cost 200 lives, many houses and bridges were destroyed by the flooding. Recently the Algerian government have obligated to dam owners the development of detailed dam break Emergency Action Plans for its 64 major dams. The research presented here was conducted within this framework, Zardezas dam which is located in the city of Skikda in the North East of Algeria was the case of study. The model HEC-RAS was used for the hydrodynamic routing of the dam break flood wave. In addition, Geographic Information System (GIS) was used to create inundation maps and produce a visualization of the flood propagation in the Saf-Saf River.The simulation results that demonstrate the significance of Zardezas dam break flooding; constitute a real tool for developing emergency response plans and assisting territorial communities in land use planning.Keywords: dam break, HEC-RAS, GIS, inundation maps, Emergency Action Plan
Procedia PDF Downloads 3977333 Estimation of the Curve Number and Runoff Height Using the Arc CN-Runoff Tool in Sartang Ramon Watershed in Iran
Authors: L.Jowkar. M.Samiee
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Models or systems based on rainfall and runoff are numerous and have been formulated and applied depending on the precipitation regime, temperature, and climate. In this study, the ArcCN-Runoff rain-runoff modeling tool was used to estimate the spatial variability of the rainfall-runoff relationship in Sartang Ramon in Jiroft watershed. In this study, the runoff was estimated from 6-hour rainfall. The results showed that based on hydrological soil group map, soils with hydrological groups A, B, C, and D covered 1, 2, 55, and 41% of the basin, respectively. Given that the majority of the area has a slope above 60 percent and results of soil hydrologic groups, one can conclude that Sartang Ramon Basin has a relatively high potential for producing runoff. The average runoff height for a 6-hour rainfall with a 2-year return period is 26.6 mm. The volume of runoff from the 2-year return period was calculated as the runoff height of each polygon multiplied by the area of the polygon, which is 137913486 m³ for the whole basin.Keywords: Arc CN-Run off, rain-runoff, return period, watershed
Procedia PDF Downloads 1317332 A Dynamic Software Product Line Approach to Self-Adaptive Genetic Algorithms
Authors: Abdelghani Alidra, Mohamed Tahar Kimour
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Genetic algorithm must adapt themselves at design time to cope with the search problem specific requirements and at runtime to balance exploration and convergence objectives. In a previous article, we have shown that modeling and implementing Genetic Algorithms (GA) using the software product line (SPL) paradigm is very appreciable because they constitute a product family sharing a common base of code. In the present article we propose to extend the use of the feature model of the genetic algorithms family to model the potential states of the GA in what is called a Dynamic Software Product Line. The objective of this paper is the systematic generation of a reconfigurable architecture that supports the dynamic of the GA and which is easily deduced from the feature model. The resultant GA is able to perform dynamic reconfiguration autonomously to fasten the convergence process while producing better solutions. Another important advantage of our approach is the exploitation of recent advances in the domain of dynamic SPLs to enhance the performance of the GAs.Keywords: self-adaptive genetic algorithms, software engineering, dynamic software product lines, reconfigurable architecture
Procedia PDF Downloads 2887331 Enhancement of Solar Energy Storage by Nanofluid-Glass Impurities Mixture
Authors: Farhan Lafta Rashid, Khudhair Abass Dawood, Ahmed Hashim
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Recent advancements in nanotechnology have originated the new emerging heat transfer fluids called nanofluids. Nanofluids are prepared by dispersing and stably suspending nanometer sized solid particles in conventional heat transfer fluids. Past researches have shown that a very small amount of suspending nano-particles have the potential to enhance the thermo physical, transport, and radiative properties of the base fluid. At this research adding very small quantities of nano particle (TiO2) to pure water with different weights percent ranged 0.1, 0.2, 0.3, and 0.4 wt.%, we found that the best weight percent is 0.2 that gave more heat absorbed. Then adding glass impurities ranged 10, 20, and 30 wt. Percentage to the nano-fluid in order to enhance the absorbed heat so energy storage. The best glass weights percent is 0.3.Keywords: energy storage, enhancement absorbed heat, glass impurities, solar energy
Procedia PDF Downloads 4367330 Two-Step Patterning of Microfluidic Structures in Paper by Laser Cutting and Wax Printing for Mass Fabrication of Biosensor
Authors: Bong Keun Kang, Sung Suk Oh, Jeong-Woo Sohn, Jong-Ryul Choi, Young Ho Kim
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In this paper, we describe two-step micro-pattering by using laser cutting and wax printing. Wax printing is performed only on the bridges for hydrophobic barriers. We prepared 405nm blue-violet laser module and wax pencil module. And, this two modules combine x-y plot. The hollow microstructure formed by laser patterning define the hydrophilic flowing paths. However, bridges are essential to avoid the cutting area being the island. Through the support bridges, microfluidic solution spread out to the unnecessary areas. Chromatography blotting paper was purchased from Whatman. We used 20x20 cm and 46x57 cm of chromatography blotting paper. Axis moving speed of x-y plot was the main parameter of optimization. For aligning between the two patterning, the paper sheet was taped at the bottom. After the two-step patterning, temperature curing step was done at 110-130 °C. The resolution of the fabrication and the potential of the multiplex detection were investigated.Keywords: µPADs, microfluidic, biosensor, mass-fabrication
Procedia PDF Downloads 4697329 Redefining Infrastructure as Code Orchestration Using AI
Authors: Georges Bou Ghantous
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This research delves into the transformative impact of Artificial Intelligence (AI) on Infrastructure as Code (IaaC) practices, specifically focusing on the redefinition of infrastructure orchestration. By harnessing AI technologies such as machine learning algorithms and predictive analytics, organizations can achieve unprecedented levels of efficiency and optimization in managing their infrastructure resources. AI-driven IaaC introduces proactive decision-making through predictive insights, enabling organizations to anticipate and address potential issues before they arise. Dynamic resource scaling, facilitated by AI, ensures that infrastructure resources can seamlessly adapt to fluctuating workloads and changing business requirements. Through case studies and best practices, this paper sheds light on the tangible benefits and challenges associated with AI-driven IaaC transformation, providing valuable insights for organizations navigating the evolving landscape of digital infrastructure management.Keywords: artificial intelligence, infrastructure as code, efficiency optimization, predictive insights, dynamic resource scaling, proactive decision-making
Procedia PDF Downloads 397328 Magnetic Properties and Cytotoxicity of Ga-Mn Magnetic Ferrites Synthesized by the Citrate Sol-Gel Method
Authors: Javier Sánchez, Laura Elena De León Prado, Dora Alicia Cortés Hernández
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Magnetic spinel ferrites are materials that possess size, magnetic properties and heating ability adequate for their potential use in biomedical applications. The Mn0.5Ga0.5Fe2O4 magnetic nanoparticles (MNPs) were synthesized by sol-gel method using citric acid as chelating agent of metallic precursors. The synthesized samples were identified by X-Ray Diffraction (XRD) as an inverse spinel structure with no secondary phases. Saturation magnetization (Ms) of crystalline powders was 45.9 emu/g, which was higher than those corresponding to GaFe2O4 (14.2 emu/g) and MnFe2O4 (40.2 emu/g) synthesized under similar conditions, while the coercivity field (Hc) was 27.9 Oe. The average particle size was 18 ± 7 nm. The heating ability of the MNPs was enough to increase the surrounding temperature up to 43.5 °C in 7 min when a quantity of 4.5 mg of MNPs per mL of liquid medium was tested. Cytotoxic effect (hemolysis assay) of MNPs was determined and the results showed hemolytic values below 1% in all tested cases. According to the results obtained, these synthesized nanoparticles can be potentially used as thermoseeds for hyperthermia therapy.Keywords: manganese-gallium ferrite, magnetic hyperthermia, heating ability, cytotoxicity
Procedia PDF Downloads 3977327 Synthesis and Characterization of Akermanite Nanoparticles (AMN) as a Bio-Ceramic Nano Powder by Sol-Gel Method for Use in Biomedical
Authors: Seyedmahdi Mousavihashemi
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Natural Akermanite (NAM) has been successfully prepared by a modified sol-gel method. Optimization in calcination temperature and mechanical ball milling resulted in a pure and nano-sized powder which characterized by means of scanning electron microscopy (SEM), X-ray diffraction (XRD), transmission electron microscopy (TEM) and Fourier transform infrared Spectroscopy (FT–IR). We hypothesized that nano-sized Akermanite (AM) would mimic more efficiently the nanocrystal structure and function of natural bone apatite, owing to the higher surface area, compare to conventional micron-size Akermanite (AM). Accordingly, we used the unique advantage of nanotechnology to improve novel nano akermanite particles as a potential candidate for bone tissue regeneration whether as a per implant filling powder or in combination with other biomaterials as a composite scaffold. Pure Akermanite (PAM) powders were successfully obtained via a simple sol-gel method followed by calcination at 1250 °C. Mechanical grinding in a ceramic ball mill for 7 hours resulted in akermanite (AM) nanoparticles in the range of about 30- 45 nm.Keywords: biomedical engineering, nano composite, SEM, TEM
Procedia PDF Downloads 2417326 Recovery of Waste: Feasibility and Sustainable Application of Residues from Drinking Water Treatment in Building Materials
Authors: Flavio Araujo, Julio Lima, Paulo Scalize, Antonio Albuquerque, Isabela Santos
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The aim of this study was to perform the physicochemical characterizations of the residue generated in the Meia-Ponte Water Treatment Plant, seeking to obtain normative parameters and consider sustainable alternatives for reincorporation of the residues in the productive chain for manufacturing various materials construction. In order to reduce the environmental liabilities generated by sanitation companies and discontinue unsustainable forms of disposal as the launching of the residue in the rivers, disposal in landfills or burning it, because such ways pollute watercourses, ground and air. The analyzes performed: Granulometry, identification of clay minerals, Scanning Electron Microscopy, and X-Ray Diffraction demonstrated the potential application of residues to replace the soil and sand, because it has characteristics compatible with small aggregate and can be used as feedstock for the manufacture of materials as ceramic and soil-cement bricks, mortars, interlocking floors and concrete artifacts.Keywords: recovery of waste, residue, sustainable, water treatment plant, WTR
Procedia PDF Downloads 5487325 Assessing P0.1 and Occlusion Pressures in Brain-Injured Patients on Pressure Support Ventilation: A Study Protocol
Authors: S. B. R. Slagmulder
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Monitoring inspiratory effort and dynamic lung stress in patients on pressure support ventilation in the ICU is important for protecting against self inflicted lung injury (P-SILI) and diaphragm dysfunction. Strategies to address the detrimental effects of respiratory drive and effort can lead to improved patient outcomes. Two non-invasive estimation methods, occlusion pressure (Pocc) and P0.1, have been proposed for achieving lung and diaphragm protective ventilation. However, their relationship and interpretation in neuro ICU patients is not well understood. P0.1 is the airway pressure measured during a 100-millisecond occlusion of the inspiratory port. It reflects the neural drive from the respiratory centers to the diaphragm and respiratory muscles, indicating the patient's respiratory drive during the initiation of each breath. Occlusion pressure, measured during a brief inspiratory pause against a closed airway, provides information about the inspiratory muscles' strength and the system's total resistance and compliance. Research Objective: Understanding the relationship between Pocc and P0.1 in brain-injured patients can provide insights into the interpretation of these values in pressure support ventilation. This knowledge can contribute to determining extubation readiness and optimizing ventilation strategies to improve patient outcomes. The central goal is to asses a study protocol for determining the relationship between Pocc and P0.1 in brain-injured patients on pressure support ventilation and their ability to predict successful extubation. Additionally, comparing these values between brain-damaged and non-brain-damaged patients may provide valuable insights. Key Areas of Inquiry: 1. How do Pocc and P0.1 values correlate within brain injury patients undergoing pressure support ventilation? 2. To what extent can Pocc and P0.1 values serve as predictive indicators for successful extubation in patients with brain injuries? 3. What differentiates the Pocc and P0.1 values between patients with brain injuries and those without? Methodology: P0.1 and occlusion pressures are standard measurements for pressure support ventilation patients, taken by attending doctors as per protocol. We utilize electronic patient records for existing data. Unpaired T-test will be conducted to compare P0.1 and Pocc values between both study groups. Associations between P0.1 and Pocc and other study variables, such as extubation, will be explored with simple regression and correlation analysis. Depending on how the data evolve, subgroup analysis will be performed for patients with and without extubation failure. Results: While it is anticipated that neuro patients may exhibit high respiratory drive, the linkage between such elevation, quantified by P0.1, and successful extubation remains unknown The analysis will focus on determining the ability of these values to predict successful extubation and their potential impact on ventilation strategies. Conclusion: Further research is pending to fully understand the potential of these indices and their impact on mechanical ventilation in different patient populations and clinical scenarios. Understanding these relationships can aid in determining extubation readiness and tailoring ventilation strategies to improve patient outcomes in this specific patient population. Additionally, it is vital to account for the influence of sedatives, neurological scores, and BMI on respiratory drive and occlusion pressures to ensure a comprehensive analysis.Keywords: brain damage, diaphragm dysfunction, occlusion pressure, p0.1, respiratory drive
Procedia PDF Downloads 697324 Optimal Design of the Power Generation Network in California: Moving towards 100% Renewable Electricity by 2045
Authors: Wennan Long, Yuhao Nie, Yunan Li, Adam Brandt
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To fight against climate change, California government issued the Senate Bill No. 100 (SB-100) in 2018 September, which aims at achieving a target of 100% renewable electricity by the end of 2045. A capacity expansion problem is solved in this case study using a binary quadratic programming model. The optimal locations and capacities of the potential renewable power plants (i.e., solar, wind, biomass, geothermal and hydropower), the phase-out schedule of existing fossil-based (nature gas) power plants and the transmission of electricity across the entire network are determined with the minimal total annualized cost measured by net present value (NPV). The results show that the renewable electricity contribution could increase to 85.9% by 2030 and reach 100% by 2035. Fossil-based power plants will be totally phased out around 2035 and solar and wind will finally become the most dominant renewable energy resource in California electricity mix.Keywords: 100% renewable electricity, California, capacity expansion, mixed integer non-linear programming
Procedia PDF Downloads 1727323 A Case Study on the Tourists' Satisfaction: Local Gastronomy in Pagudpud, Ilocos Norte
Authors: Reysand Mae A. Abapial, Christine Claire Z. Agra, Quenna Lyn V. De Guzman, Marielle Arianne Joyce Q. Hojilla, John Joseph A. Tiangco
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The study focused on the assessment of the tourists’ satisfaction on the local gastronomy in Pagudpud, Ilocos Norte as a tourist destination as perceived by 100 tourists visiting the tourist destination, which is determined through convenient random sampling. Mean, percentage frequency and Wilcoxon rank sum test were used in the collection of data. The results revealed that the tourists agree that the local establishments offering local cuisines are accessible in terms of the location, internet visibility and facilities for persons-with-disabilities. The tourist are also willing to pay for the local food because it is attainable, budget-friendly, worthy for an expensive price, satisfies the cravings, reflects the physical appearance of the establishment and its quantity is reasonable based on the price. However, the tourists disagree that the local food completes their overall experience as tourists and it does not have the potential to satisfy all types of tourists. Recommendations for the enhancement of the local cuisine and implications for future research are discussed.Keywords: gastronomy, local gastronomy, tourist satisfaction, Pagudpud
Procedia PDF Downloads 6737322 Implication of Multi-Walled Carbon Nanotubes on Polymer/MXene Nanocomposites
Authors: Mathias Aakyiir, Qunhui Zheng, Sherif Araby, Jun Ma
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MXene nanosheets stack in polymer matrices, while multi-walled carbon nanotubes (MWCNTs) entangle themselves when used to form composites. These challenges are addressed in this work by forming MXene/MWCNT hybrid nanofillers by electrostatic self-assembly and developing elastomer/MXene/MWCNTs nanocomposites using a latex compounding method. In a 3-phase nanocomposite, MWCNTs serve as bridges between MXene nanosheets, leading to nanocomposites with well-dispersed nanofillers. The high aspect ratio of MWCNTs and the interconnection role of MXene serve as a basis for forming nanocomposites of lower percolation threshold of electrical conductivity from the hybrid fillers compared with the 2-phase composites containing either MXene or MWCNTs only. This study focuses on discussing into detail the interfacial interaction of nanofillers and the elastomer matrix and the outstanding mechanical and functional properties of the resulting nanocomposites. The developed nanocomposites have potential applications in the automotive and aerospace industries.Keywords: elastomers, multi-walled carbon nanotubes, MXenes, nanocomposites
Procedia PDF Downloads 1667321 Seek First to Regulate, Then to Understand: The Case for Preemptive Regulation of Robots
Authors: Catherine McWhorter
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Robotics is a fast-evolving field lacking comprehensive and harm-mitigating regulation; it also lacks critical data on how human-robot interaction (HRI) may affect human psychology. As most anthropomorphic robots are intended as substitutes for humans, this paper asserts that the commercial robotics industry should be preemptively regulated at the federal level such that robots capable of embodying a victim role in criminal scenarios (“vicbots”) are prohibited until clinical studies determine their effects on the user and society. The results of these studies should then inform more permanent legislation that strives to mitigate risks of harm without infringing upon fundamental rights or stifling innovation. This paper explores these concepts through the lens of the sex robot industry. The sexbot industry offers some of the most realistic, interactive, and customizable robots for sale today. From approximately 2010 until 2017, some sex robot producers, such as True Companion, actively promoted ‘vicbot’ culture with personalities like “Frigid Farrah” and “Young Yoko” but received significant public backlash for fetishizing rape and pedophilia. Today, “Frigid Farrah” and “Young Yoko” appear to have vanished. Sexbot producers have replaced preprogrammed vicbot personalities in favor of one generic, customizable personality. According to the manufacturer ainidoll.com, when asked, there is only one thing the user won’t be able to program the sexbot to do – “…give you drama”. The ability to customize vicbot personas is possible with today’s generic personality sexbots and may undermine the intent of some current legislative efforts. Current debate on the effects of vicbots indicates a lack of consensus. Some scholars suggest vicbots may reduce the rate of actual sex crimes, and some suggest that vicbots will, in fact, create sex criminals, while others cite their potential for rehabilitation. Vicbots may have value in some instances when prescribed by medical professionals, but the overall uncertainty and lack of data further underscore the need for preemptive regulation and clinical research. Existing literature on exposure to media violence and its effects on prosocial behavior, human aggression, and addiction may serve as launch points for specific studies into the hyperrealism of vicbots. Of course, the customization, anthropomorphism and artificial intelligence of sexbots, and therefore more mainstream robots, will continue to evolve. The existing sexbot industry offers an opportunity to preemptively regulate and to research answers to these and many more questions before this type of technology becomes even more advanced and mainstream. Robots pose complicated moral, ethical, and legal challenges, most of which are beyond the scope of this paper. By examining the possibility for custom vicbots via the sexbots industry, reviewing existing literature on regulation, media violence, and vicbot user effects, this paper strives to underscore the need for preemptive federal regulation prohibiting vicbot capabilities in robots while advocating for further research into the potential for the user and societal harm by the same.Keywords: human-robot interaction effects, regulation, research, robots
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