Search results for: performance comparison
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 16974

Search results for: performance comparison

3594 Hydrogen Sulfide Removal from Biogas Using Biofilm on Packed Bed of Salak Fruit Seeds

Authors: Retno A. S. Lestari, Wahyudi B. Sediawan, Siti Syamsiah, Sarto

Abstract:

Sulfur-oxidizing bacteria were isolated and then grown on snakefruits seeds forming biofilm. Their performance in sulfide removal were experimentally observed. Snakefruit seeds were then used as packing material in a cylindrical tube. Biological treatment of hydrogen sulfide from biogas was investigated using biofilm on packed bed of snakefruits seeds. Biogas containing 27,9512 ppm of hydrogen sulfide was flown through the bed. Then the hydrogen sulfide concentrations in the outlet at various times were analyzed. A set of simple kinetics model for the rate of the sulfide removal and the bacterial growth was proposed. The axial sulfide concentration gradient in the flowing liquid are assumed to be steady-state. Mean while the biofilm grows on the surface of the seeds and the oxidation takes place in the biofilm. Since the biofilm is very thin, the sulfide concentration in the biofilm is assumed to be uniform. The simultaneous ordinary differential equations obtained were then solved numerically using Runge-Kutta method. The acuracy of the model proposed was tested by comparing the calcultion results using the model with the experimental data obtained. It turned out that the model proposed can be applied to describe the removal of sulfide liquid using bio-filter in packed bed. The values of the parameters were also obtained by curve-fitting. The biofilter could remove 89,83 % of the inlet of hydrogen sulfide from biogas for 2.5 h, and optimum loading of 8.33 ml/h.

Keywords: Sulfur-oxidizing bacteria, snakefruits seeds, biofilm, packing material, biogas

Procedia PDF Downloads 409
3593 High Performance of Square GAA SOI MOSFET Using High-k Dielectric with Metal Gate

Authors: Fatima Zohra Rahou, A. Guen Bouazza, B. Bouazza

Abstract:

Multi-gate SOI MOSFETs has shown better results in subthreshold performances. The replacement of SiO2 by high-k dielectric can fulfill the requirements of Multi-gate MOSFETS with a scaling trend in device dimensions. The advancement in fabrication technology has also boosted the use of different high -k dielectric materials as oxide layer at different places in MOSFET structures. One of the most important multi-gate structures is square GAA SOI MOSFET that is a strong candidate for the next generation nanoscale devices; show an even stronger control of short channel effects. In this paper, GAA SOI MOSFET structure with using high -k dielectrics materials Al2O3 (k~9), HfO2 (k~20), La2O3 (k~30) and metal gate TiN are simulated by using 3-D device simulator DevEdit and Atlas of SILVACO TCAD tools. Square GAA SOI MOSFET transistor with High-k HfO2 gate dielectrics and TiN metal gate exhibits significant improvements performances compared to Al2O3 and La2O3 dielectrics for the same structure. Simulation results of GAA SOI MOSFET transistor with HfO2 dielectric show the increase in saturation current and Ion/Ioff ratio while leakage current, subthreshold slope and DIBL effect are decreased.

Keywords: technology SOI, short-channel effects (SCEs), multi-gate SOI MOSFET, square GAA SOI MOSFET, high-k dielectric, Silvaco software

Procedia PDF Downloads 265
3592 Random Forest Classification for Population Segmentation

Authors: Regina Chua

Abstract:

To reduce the costs of re-fielding a large survey, a Random Forest classifier was applied to measure the accuracy of classifying individuals into their assigned segments with the fewest possible questions. Given a long survey, one needed to determine the most predictive ten or fewer questions that would accurately assign new individuals to custom segments. Furthermore, the solution needed to be quick in its classification and usable in non-Python environments. In this paper, a supervised Random Forest classifier was modeled on a dataset with 7,000 individuals, 60 questions, and 254 features. The Random Forest consisted of an iterative collection of individual decision trees that result in a predicted segment with robust precision and recall scores compared to a single tree. A random 70-30 stratified sampling for training the algorithm was used, and accuracy trade-offs at different depths for each segment were identified. Ultimately, the Random Forest classifier performed at 87% accuracy at a depth of 10 with 20 instead of 254 features and 10 instead of 60 questions. With an acceptable accuracy in prioritizing feature selection, new tools were developed for non-Python environments: a worksheet with a formulaic version of the algorithm and an embedded function to predict the segment of an individual in real-time. Random Forest was determined to be an optimal classification model by its feature selection, performance, processing speed, and flexible application in other environments.

Keywords: machine learning, supervised learning, data science, random forest, classification, prediction, predictive modeling

Procedia PDF Downloads 98
3591 Islamic Banking Adoption Model from Technology Prospective

Authors: Amer Alzaidi

Abstract:

Islamic banking is an alternative solution to those people who are worried about Riba (interest) in all forms of transaction while using banking services and products. Today, banks around the world have Islamic banking services and products the in one form or another. The use of Islamic banking is not only restricted to Muslims world but have reached to non-Muslim countries like UK, USA, Australia and Canada as well. Compared to conventional banking, the adoption rate of Islamic banking is low because of unawareness of customers, financial cost, and performance issues. The interest in Islamic banking by financial institutions as well as low adoption rate motivated us to look this matter into detail in order to identify Critical Success Factors, which are positively motivating customers to use Islamic banking services/ products and Critical Risk Factors, which have significantly negative effect on the adoption of Islamic banking. The CSFs and CRFs will be initially identified from the literature using methodology called Systematic Literature Review, followed by the empirical analysis of these factors using survey research method. Later, we will develop Islamic Banking Adoption Model (IBAM) to help banks to assess their Islamic banking strategic positioning and to improve their operational efficiency. The first potential contribution of this research study will be the development of IBAM protocol that will provide us guidelines for conducting our actual SLR. The second major contribution of this research will be the development of Islamic Banking Adoption Model (IBAM), and the third contribution of this research study will be the evaluation of the developed IBMA.

Keywords: Islamic banking, adoption model, protocol, technology

Procedia PDF Downloads 282
3590 The Myth of Mohini and Ardhanarishvara: A Queer Reading

Authors: Anindita Roy

Abstract:

This paper offers a queer reading of the myth of Mohini and Ardhanarishvara in Indian mythology to explore the transformative capacity of gender performativity with a view to focusing on the notion of female and male as harmonious contributors in culture and nature. The qualitative study of these two narratives ponders on the issues of dualism in Indian mythology. These myths approach different queer experiences in different ways - the first, an incarnation of Vishnu into Mohini by body swapping and the latter, the myth of Ardhanarishvara in which one sacred body upholds two different biological identities together- male and female. Emphasizing on the transformation of sex, the present paper re-reads how these queer-transformations can become transformative in the society. The study is explained in three parts. The first one focuses on the two select myths to explore the idea of gender as performance and the concept of queer ecofeminism where nature/culture, heterosexuality/queer female/male dualism exist in a paradigm. The second segment analyzes whether these myths destabilize or promote the access of queer and the experience of ‘other’ in the society and resistance against domination. The third section inquires to rethink the whole world about the value and hierarchy of men over women, heterosexuality over queer, culture over nature to call for a recovery of the female/male, nature/culture principles as complementary. What the paper intends to investigate is if and how gender transformations in religious myths have the capacity to transform personal and social notions and practices of different hierarchies.

Keywords: dualism, Indian myth, queer, transformativity

Procedia PDF Downloads 179
3589 Concept Mapping of Teachers Regarding Conflict Management

Authors: Tahir Mehmood, Mumtaz Akhter

Abstract:

The global need for conflict management is greater now in the early 21st century than ever before. According to UNESCO, half of the world’s 195 countries will have to expand their stock of educationist significantly, some by tens of thousands, if the goal development targets are desired to achieve. Socioeconomic inequities, political instability, demographic changes and crises such as the HIV/AIDs epidemic have engendered huge shortfalls in teacher supply and low teacher quality in many developing countries. Education serves as back bone in development process. Open learning and distance education programs are serving as pivotal part of development process. It is now clear that ‘bricks and mortar’ approaches to expanding teacher education may not be adequate if the current and projected shortfalls in teacher supply and low teacher quality are to be properly addressed. The study is designed to measure the perceptions of teaching learning community about conflict management with special reference to open and distance learning. It was descriptive study which targeted teachers, students, community members and experts. Data analysis was carried out by using statistical techniques served by SPSS. Findings reflected that audience perceives open and distance learning as change agent and as development tool. It is noticed that target audience has driven prominent performance by using facility of open and distance learning.

Keywords: conflict management, open and distance learning, teachers, students

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3588 Topographic and Thermal Analysis of Plasma Polymer Coated Hybrid Fibers for Composite Applications

Authors: Hande Yavuz, Grégory Girard, Jinbo Bai

Abstract:

Manufacturing of hybrid composites requires particular attention to overcome various critical weaknesses that are originated from poor interfacial compatibility. A large number of parameters have to be considered to optimize the interfacial bond strength either to avoid flaw sensitivity or delamination that occurs in composites. For this reason, surface characterization of reinforcement phase is needed in order to provide necessary data to drive an assessment of fiber-matrix interfacial compatibility prior to fabrication of composite structures. Compared to conventional plasma polymerization processes such as radiofrequency and microwave, dielectric barrier discharge assisted plasma polymerization is a promising process that can be utilized to modify the surface properties of carbon fibers in a continuous manner. Finding the most suitable conditions (e.g., plasma power, plasma duration, precursor proportion) for plasma polymerization of pyrrole in post-discharge region either in the presence or in the absence of p-toluene sulfonic acid monohydrate as well as the characterization of plasma polypyrrole coated fibers are the important aspects of this work. Throughout the current investigation, atomic force microscopy (AFM) and thermogravimetric analysis (TGA) are used to characterize plasma treated hybrid fibers (CNT-grafted Toray T700-12K carbon fibers, referred as T700/CNT). TGA results show the trend in the change of decomposition process of deposited polymer on fibers as a function of temperature up to 900 °C. Within the same period of time, all plasma pyrrole treated samples began to lose weight with relatively fast rate up to 400 °C which suggests the loss of polymeric structures. The weight loss between 300 and 600 °C is attributed to evolution of CO2 due to decomposition of functional groups (e.g. carboxyl compounds). With keeping in mind the surface chemical structure, the higher the amount of carbonyl, alcohols, and ether compounds, the lower the stability of deposited polymer. Thus, the highest weight loss is observed in 1400 W 45 s pyrrole+pTSA.H2O plasma treated sample probably because of the presence of less stable polymer than that of other plasma treated samples. Comparison of the AFM images for untreated and plasma treated samples shows that the surface topography may change on a microscopic scale. The AFM image of 1800 W 45 s treated T700/CNT fiber possesses the most significant increase in roughening compared to untreated T700/CNT fiber. Namely, the fiber surface became rougher with ~3.6 fold that of the T700/CNT fiber. The increase observed in surface roughness compared to untreated T700/CNT fiber may provide more contact points between fiber and matrix due to increased surface area. It is believed to be beneficial for their application as reinforcement in composites.

Keywords: hybrid fibers, surface characterization, surface roughness, thermal stability

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3587 Automated End-to-End Pipeline Processing Solution for Autonomous Driving

Authors: Ashish Kumar, Munesh Raghuraj Varma, Nisarg Joshi, Gujjula Vishwa Teja, Srikanth Sambi, Arpit Awasthi

Abstract:

Autonomous driving vehicles are revolutionizing the transportation system of the 21st century. This has been possible due to intensive research put into making a robust, reliable, and intelligent program that can perceive and understand its environment and make decisions based on the understanding. It is a very data-intensive task with data coming from multiple sensors and the amount of data directly reflects on the performance of the system. Researchers have to design the preprocessing pipeline for different datasets with different sensor orientations and alignments before the dataset can be fed to the model. This paper proposes a solution that provides a method to unify all the data from different sources into a uniform format using the intrinsic and extrinsic parameters of the sensor used to capture the data allowing the same pipeline to use data from multiple sources at a time. This also means easy adoption of new datasets or In-house generated datasets. The solution also automates the complete deep learning pipeline from preprocessing to post-processing for various tasks allowing researchers to design multiple custom end-to-end pipelines. Thus, the solution takes care of the input and output data handling, saving the time and effort spent on it and allowing more time for model improvement.

Keywords: augmentation, autonomous driving, camera, custom end-to-end pipeline, data unification, lidar, post-processing, preprocessing

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3586 Addressing Urban Security Challenges in Nigeria through Neighborhood Renewal: A Reflection of Mokola World Bank Slum Upgrading Pilot Project

Authors: Tabiti S. Tabiti, A. M. Jinadu, Daramola Japheth

Abstract:

Urban insecurity is among the challenges militating against sustainable urban governance; in the first place it distorts the peace of urban areas making them unsafe. On the other hand it hinders the effective performance of urban functions. Urban security challenges manifest in different forms such as, street violence, theft and robbery, accidents of different types kidnapping, killings etc.. Efforts to address urban security challenges in Nigeria have been concentrated in legislative, law enforcement and the use of community vigilante groups. However in this study, the place of physical planning strategy through effective neighbourhood renewal as practiced in Mokola is presented as an effective complementary approach for addressing urban insecurity. On this backdrop, the paper recommends the need for gradual rehabilitation of urban slum neighborhoods by the state government in collaboration with World Bank and other development financiers. The local governments should be made autonomy in Nigeria so as to make them more responsible to the people. Other recommendations suggested in the paper include creating enabling environment that will promote economic empowerment and public enlightment on personal and community sanitation. It is certain that if these recommendations are adopted the challenge of urban insecurity will reduce significantly in Nigerian cities.

Keywords: neighbourhood renewal, pilot project, slum upgrading, urban security

Procedia PDF Downloads 439
3585 Experiments on Weakly-Supervised Learning on Imperfect Data

Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

Abstract:

Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

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3584 Investigating Mathematical Knowledge of Teaching for Secondary Preservice Teachers in Papua New Guinea Based on Probabilities

Authors: Murray Olowa

Abstract:

This article examines the studies investigating the Mathematical Knowledge for Teaching (MKT) of secondary preservice teachers in Papua New Guinea based on probabilities. This research was conducted due to the continuous issues faced in the country in both primary and secondary education, like changes in curriculum, emphasis on mathematics and science education, and a decline in mathematics performance. Moreover, the mathematics curriculum doesn’t capture Pedagogical Content Knowledge (PCK) or Subject Matter Knowledge (SMK). The two main domains that have been identified are SMK and PCK, which have been further sub-divided into Common Content Knowledge (CCK), Specialised Content Knowledge (SCK) and Horizon Content Knowledge (HCK), and Knowledge of Content and Students (KCS), Knowledge of Content and Teaching (KCT) and Knowledge of Content and Curriculum (KCC), respectively. The data collected from 15-_year-_ ones and 15-_year-_fours conducted at St Peter Chanel Secondary Teachers College revealed that there is no significant difference in subject matter knowledge between year one and year four since the P-value of 0.22>0.05. However, it was revealed that year fours have higher pedagogical content knowledge than year one since P-value was 0.007<0.05. Finally, the research has proven that year fours have higher MKT than year one. This difference occurred due to final year preservice teachers’ hard work and engagement in mathematics curriculum and teaching practice.

Keywords: mathematical knowledge for teaching, subject matter knowledge, pedagogical content knowledge, Papua New Guinea, preservice teachers, probability

Procedia PDF Downloads 106
3583 A Preliminary Study on the Effects of Equestrian and Basketball Exercises in Children with Autism

Authors: Li Shuping, Shu Huaping, Yi Chaofan, Tao Jiang

Abstract:

Equestrian practice is often considered having a unique effect on improving symptoms in children with autism. This study evaluated and measured the changes in daily behavior, morphological, physical function, and fitness indexes of two group children with autism by means of 12 weeks of equestrian and basketball exercises. 19 clinically diagnosed children with moderate/mild autism were randomly divided into equestrian group (9 children, age=10.11±1.90y) and basketball group (10 children, age=10.70±2.16y). Both the equestrian and basketball groups practiced twice a week for 45 to 60 minutes each time. Three scales, the Autism Behavior Checklist (ABC), the Childhood Autism Rating Scale (CARS) and the Clancy Autism Behavior Scale (CABS) were used to assess their human behavior and psychology. Four morphological, seven physical function and fitness indicators were measured to evaluate the effects of the two exercises on the children’s body. The evaluations were taken by every four weeks ( pre-exercise, the 4th week, the 8th week and 12th week (post exercise). The result showed that the total scores of ABC, CARS and CABS, the dimension scores of ABC on the somatic motor, language and life self-care obtained after exercise were significantly lower than those obtained before 12 week exercises in both groups. The ABC feeling dimension scores of equestrian group and ABC communication dimension score of basketball group were significantly lower,and The upper arm circumference, sitting forward flexion, 40 second sit-up, 15s lateral jump, vital capacity, and single foot standing of both groups were significantly higher than that of before exercise.. The BMI of equestrian group was significantly reduced. The handgrip strength of basketball group was significantly increased. In conclusion, both types of exercises could improve daily behavior, morphological, physical function, and fitness indexes of the children with autism. However, the behavioral psychological scores, body morphology and function indicators and time points were different in the middle and back of the two interventions.But the indicators and the timing of the improvement were different. To the group of equestrian, the improvement of the flexibility occurred at week 4, the improvement of the sensory perception, control and use their own body, and promote the development of core strength endurance, coordination and cardiopulmonary function occurred at week 8,and the improvement of core strength endurance, coordination and cardiopulmonary function occurred at week 12. To the group of basketball, the improvement of the hand strength, balance, flexibility and cardiopulmonary function occurred at week 4, the improvement of the self-care ability and language expression ability, and core strength endurance and coordination occurred at week 8, the improvement of the control and use of their own body and social interaction ability occurred at week 12. In comparison of the exercise effects, the equestrian exercise improved the physical control and application ability appeared earlier than that of basketball group. Basketball exercise improved the language expression ability, self-care ability, balance ability and cardiopulmonary function of autistic children appeared earlier than that of equestrian group.

Keywords: intervention, children with autism, equestrain, basketball

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3582 Structural Analysis of Hole-Type Plate for Weight Lightening of Road Sign

Authors: Joon-Yeop Na, Sang-Keun Baik, Kyu-Soo Chong

Abstract:

Road sign sizes are related to their support and foundation, and the large-scale support that is generally installed at roadsides can cause inconvenience to pedestrians and damage the urban landscape. The most influential factor in determining the support and foundation of road signs is the wind load. In this study, we introduce a hole-type road sign to analyze its effects on reducing wind load. A hole-type road sign reduces the drag coefficient that is applied when considering the air and fluid resistance of a plate when the wind pressure is calculated, thus serving as an effective option for lightening the weights of road sign structures. A hole-type road sign is punctured with a perforator. Furthermore, the size of the holes and their distance is determined considering the damage to characters, the poor performance of reflective sheets, and legibility. For the calculation of the optimal specification of a hole-type road sign, we undertook a theoretical examination for reducing the wind loads on hole-type road signs, and analyzed the bending and reflectivity of sample road sign plates. The analytic results confirmed that a hole-type road sign sample that contains holes of 6 mm in diameter with a distance of 18 mm between the holes shows reflectivity closest to that of existing road signs; moreover, the average bending moment resulted in a reduction of 4.24%, and the support’s diameter is reduced by 40.2%.

Keywords: hole type, road sign, weight lightening, wind load

Procedia PDF Downloads 548
3581 Investigation of the Possibility of Using Carbon Onion Nanolubrication with DLC Cutting Tool to Reduce the Machining Power Consumption

Authors: Ahmed A. D. Sarhan, M. Sayuti, M. Hamdi

Abstract:

Due to rapid consumption of world's fossil fuel resources and impracticality of large-scale application and production of renewable energy, the significance of energy efficiency improvement of current available energy modes has been widely realized by both industry and academia. In the CNC machining field, the key solution for this issue is by increasing the effectiveness of the existing lubrication systems as it could reduce the power required to overcome the friction component in machining process. For more improvement, introducing the nanolubrication could produce much less power consumption as the rolling action of billions units of nanoparticle in the tool chip interface could reduce the cutting forces significantly. In this research, the possibility of using carbon onion nanolubrication with DLC cutting tool is investigated to reduce the machining power consumption. Carbon onion nanolubrication has been successfully developed with high tribology performance and mixed with ordinary mineral oil. The proper sonification method is used to provide a way to mix and suspend the particles thoroughly and efficiently. Furthermore, Diamond-Like Carbon (DLC) cutting tool is used and expected to play significant role in reducing friction and cutting forces and increasing abrasion resistance. The results showed significant reduction of the cutting force and the working power compared with the other conditions of using carbon black and normal lubrication systems.

Keywords: carbon onion, nanolubrication, machining power consumption, DLC cutting tool

Procedia PDF Downloads 436
3580 Quantification of Peptides (linusorbs) in Gluten-free Flaxseed Fortified Bakery Products

Authors: Youn Young Shim, Ji Hye Kim, Jae Youl Cho, Martin JT Reaney

Abstract:

Flaxseed (Linumusitatissimum L.) is gaining popularity in the food industry as a superfood due to its health-promoting properties. Linusorbs (LOs, a.k.a. Cyclolinopeptide) are bioactive compounds present in flaxseed exhibiting potential health effects. The study focused on the effects of processing and storage on the stability of flaxseed-derived LOs added to various bakery products. The flaxseed meal fortified gluten-free (GF) bakery bread was prepared, and the changes of LOs during the bread-making process (meal, fortified flour, dough, and bread) and storage (0, 1, 2, and 4 weeks) at different temperatures (−18 °C, 4 °C, and 22−23 °C) were analyzed by high-performance liquid chromatography-diode array detection. The total oxidative LOs and LO1OB2 were almost kept stable in flaxseed meals at storage temperatures of 22−23 °C, −18 °C, and 4 °C for up to four weeks. Processing steps during GF-bread production resulted in the oxidation of LOs. Interestingly, no LOs were detected in the dough sample; however, LOs appeared when the dough was stored at −18 °C for one week, suggesting that freezing destroyed the sticky structure of the dough and resulted in the release of LOs. The final product, flaxseed meal fortified bread, could be stored for up to four weeks at −18 °C and 4 °C, and for one week at 22−23 °C. All these results suggested that LOs may change during processing and storage and that flaxseed flour-fortified bread should be stored at low temperatures to preserve effective LOs components.

Keywords: linum usitatissimum L., flaxseed, linusorb, stability, gluten-free, peptides, cyclolinopeptide

Procedia PDF Downloads 183
3579 Process of Dimensioning Small Type Annular Combustors

Authors: Saleh B. Mohamed, Mohamed H. Elhsnawi, Mesbah M. Salem

Abstract:

Current and future applications of small gas turbine engines annular type combustors have requirements presenting difficult disputes to the combustor designer. Reduced cost and fuel consumption and improved durability and reliability as well as higher temperatures and pressures for such application are forecast. Coupled with these performance requirements, irrespective of the engine size, is the demand to control the pollutant emissions, namely the oxides of nitrogen, carbon monoxide, smoke and unburned hydrocarbons. These technical and environmental challenges have made the design of small size combustion system a very hard task. Thus, the main target of this work is to generalize a calculation method of annular type combustors for small gas turbine engines that enables to understand the fundamental concepts of the coupled processes and to identify the proper procedure that formulates and solves the problems in combustion fields in as much simplified and accurate manner as possible. The combustion chamber in task is designed with central vaporizing unit and to deliver 516.3 KW of power. The geometrical constraints are 142 mm & 140 mm overall length and casing diameter, respectively, while the airflow rate is 0.8 kg/sec and the fuel flow rate is 0.012 kg/sec. The relevant design equations are programmed by using MathCAD language for ease and speed up of the calculation process.

Keywords: design of gas turbine, small engine design, annular type combustors, mechanical engineering

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3578 Sustainable Supply Chain Management Practices, Challenges, and Opportunities: A Case Study of Small and Medium-Sized Enterprises Within the Oil and Gas Sector

Authors: Igho Ekiugbo, Christos Papanagnou

Abstract:

The energy sector continues to face increased scrutiny due to climate change challenges emanating from the burning of fossil fuels, such as coal, oil, and gas. These climate change challenges have motivated industry practitioners and researchers alike to gain an interest in the way businesses operate. This paper aimed to investigate and assess how small and medium-sized enterprises (SMEs) are reducing the impact of their operations, especially those within their supply chains, by assessing the sustainability practices they have adopted and implemented as well as the benefits and challenges of adopting such practices. Data will be collected from SMEs operating across the downstream oil and gas sector in Nigeria using questionnaire surveys. To analyse the data, confirmatory factor analysis and regression analysis will be performed. This method is deemed more suitable and appropriate for testing predefined measurements of sustainable supply chain practices as contained in the extant literature. Preliminary observations indicate a consensus on the awareness of the sustainability concept amongst the target participants. To the best of our knowledge, this paper is among the first to investigate the sustainability practices of SMEs operating in the Nigerian oil and gas sector and will therefore contribute to the sustainability and circular economic literature.

Keywords: small and medium-sized enterprises, sustainability practices, supply chains, sustainable supply chain management, corporate sustainability, oil and gas, business performance

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3577 Impact of Saline Water and Water Restriction in Laying Hens

Authors: Reza Vakili

Abstract:

This experiment was conducted to investigate the effect of duration water restriction of drinking water and salinity level on production performance, egg quality and biochemical and hematological blood indices of laying hens. A total of 240 Hy-Line laying hens were used in a completely randomized design with a 2 × 2 factorial arrangement of treatments. Experimental treatments were: 1) free access to drinking water and a low level of salinity (TDS below 500 mg/L) (FAW+LS), 2) free access to water and a high level of salinity (TDS above 1500 mg/L), (FAW+HS), 3) 12 h nightly water restriction and a low level of salinity (LAW+LS), and 4) 12 h water restriction and a high level of salinity (LAW+HS). Intake of feed, percentage of egg production and egg weight and mass were not affected by water restriction or salinity level (P > 0.05), however, a trend (P < 0.01) for lower water consumption was detected in water-restricted hens, regardless of salinity level (213 vs 187). A tendency for lower eggshell and yolk weights was observed in hens that had limited access to water with high salinity compared to those had free access to high saline water (P = 0.08). Serum total protein and glucose concentrations significantly reduced (P < 0.05) in hens drank high salinity water, regardless of water restriction. Moreover, saline water increased the concentration of uric acid, creatinine, and cholesterol when compared to low salinity drank-hens (P < 0.05). The concentrations of ALT and AST increased with salinity level (P < 0.05) and water restriction caused an increment in AST content (P < 0.05). In conclusion, Hy-Line laying hens could withstand water restriction, whilst could not tolerate water salinity of about 1500 mg/L.

Keywords: chemical pollutants, eggs, laying hens, salinity, water quality

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3576 Introducing Global Navigation Satellite System Capabilities into IoT Field-Sensing Infrastructures for Advanced Precision Agriculture Services

Authors: Savvas Rogotis, Nikolaos Kalatzis, Stergios Dimou-Sakellariou, Nikolaos Marianos

Abstract:

As precision holds the key for the introduction of distinct benefits in agriculture (e.g., energy savings, reduced labor costs, optimal application of inputs, improved products, and yields), it steadily becomes evident that new initiatives should focus on rendering Precision Agriculture (PA) more accessible to the average farmer. PA leverages on technologies such as the Internet of Things (IoT), earth observation, robotics and positioning systems (e.g., the Global Navigation Satellite System – GNSS - as well as individual positioning systems like GPS, Glonass, Galileo) that allow: from simple data georeferencing to optimal navigation of agricultural machinery to even more complex tasks like Variable Rate Applications. An identified customer pain point is that, from one hand, typical triangulation-based positioning systems are not accurate enough (with errors up to several meters), while on the other hand, high precision positioning systems reaching centimeter-level accuracy, are very costly (up to thousands of euros). Within this paper, a Ground-Based Augmentation System (GBAS) is introduced, that can be adapted to any existing IoT field-sensing station infrastructure. The latter should cover a minimum set of requirements, and in particular, each station should operate as a fixed, obstruction-free towards the sky, energy supplying unit. Station augmentation will allow them to function in pairs with GNSS rovers following the differential GNSS base-rover paradigm. This constitutes a key innovation element for the proposed solution that encompasses differential GNSS capabilities into an IoT field-sensing infrastructure. Integrating this kind of information supports the provision of several additional PA beneficial services such as spatial mapping, route planning, and automatic field navigation of unmanned vehicles (UVs). Right at the heart of the designed system, there is a high-end GNSS toolkit with base-rover variants and Real-Time Kinematic (RTK) capabilities. The GNSS toolkit had to tackle all availability, performance, interfacing, and energy-related challenges that are faced for a real-time, low-power, and reliable in the field operation. Specifically, in terms of performance, preliminary findings exhibit a high rover positioning precision that can even reach less than 10-centimeters. As this precision is propagated to the full dataset collection, it enables tractors, UVs, Android-powered devices, and measuring units to deal with challenging real-world scenarios. The system is validated with the help of Gaiatrons, a mature network of agro-climatic telemetry stations with presence all over Greece and beyond ( > 60.000ha of agricultural land covered) that constitutes part of “gaiasense” (www.gaiasense.gr) smart farming (SF) solution. Gaiatrons constantly monitor atmospheric and soil parameters, thus, providing exact fit to operational requirements asked from modern SF infrastructures. Gaiatrons are ultra-low-cost, compact, and energy-autonomous stations with a modular design that enables the integration of advanced GNSS base station capabilities on top of them. A set of demanding pilot demonstrations has been initiated in Stimagka, Greece, an area with a diverse geomorphological landscape where grape cultivation is particularly popular. Pilot demonstrations are in the course of validating the preliminary system findings in its intended environment, tackle all technical challenges, and effectively highlight the added-value offered by the system in action.

Keywords: GNSS, GBAS, precision agriculture, RTK, smart farming

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3575 An Overbooking Model for Car Rental Service with Different Types of Cars

Authors: Naragain Phumchusri, Kittitach Pongpairoj

Abstract:

Overbooking is a very useful revenue management technique that could help reduce costs caused by either undersales or oversales. In this paper, we propose an overbooking model for two types of cars that can minimize the total cost for car rental service. With two types of cars, there is an upgrade possibility for lower type to upper type. This makes the model more complex than one type of cars scenario. We have found that convexity can be proved in this case. Sensitivity analysis of the parameters is conducted to observe the effects of relevant parameters on the optimal solution. Model simplification is proposed using multiple linear regression analysis, which can help estimate the optimal overbooking level using appropriate independent variables. The results show that the overbooking level from multiple linear regression model is relatively close to the optimal solution (with the adjusted R-squared value of at least 72.8%). To evaluate the performance of the proposed model, the total cost was compared with the case where the decision maker uses a naïve method for the overbooking level. It was found that the total cost from optimal solution is only 0.5 to 1 percent (on average) lower than the cost from regression model, while it is approximately 67% lower than the cost obtained by the naïve method. It indicates that our proposed simplification method using regression analysis can effectively perform in estimating the overbooking level.

Keywords: overbooking, car rental industry, revenue management, stochastic model

Procedia PDF Downloads 174
3574 Synergizing Additive Manufacturing and Artificial Intelligence: Analyzing and Predicting the Mechanical Behavior of 3D-Printed CF-PETG Composites

Authors: Sirine Sayed, Mostapha Tarfaoui, Abdelmalek Toumi, Youssef Qarssis, Mohamed Daly, Chokri Bouraoui

Abstract:

This paper delves into the combination of additive manufacturing (AM) and artificial intelligence (AI) to solve challenges related to the mechanical behavior of AM-produced parts. The article highlights the fundamentals and benefits of additive manufacturing, including creating complex geometries, optimizing material use, and streamlining manufacturing processes. The paper also addresses the challenges associated with additive manufacturing, such as ensuring stable mechanical performance and material properties. The role of AI in improving the static behavior of AM-produced parts, including machine learning, especially the neural network, is to make regression models to analyze the large amounts of data generated during experimental tests. It investigates the potential synergies between AM and AI to achieve enhanced functions and personalized mechanical properties. The mechanical behavior of parts produced using additive manufacturing methods can be further improved using design optimization, structural analysis, and AI-based adaptive manufacturing. The article concludes by emphasizing the importance of integrating AM and AI to enhance mechanical operations, increase reliability, and perform advanced functions, paving the way for innovative applications in different fields.

Keywords: additive manufacturing, mechanical behavior, artificial intelligence, machine learning, neural networks, reliability, advanced functionalities

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3573 Design of an Ensemble Learning Behavior Anomaly Detection Framework

Authors: Abdoulaye Diop, Nahid Emad, Thierry Winter, Mohamed Hilia

Abstract:

Data assets protection is a crucial issue in the cybersecurity field. Companies use logical access control tools to vault their information assets and protect them against external threats, but they lack solutions to counter insider threats. Nowadays, insider threats are the most significant concern of security analysts. They are mainly individuals with legitimate access to companies information systems, which use their rights with malicious intents. In several fields, behavior anomaly detection is the method used by cyber specialists to counter the threats of user malicious activities effectively. In this paper, we present the step toward the construction of a user and entity behavior analysis framework by proposing a behavior anomaly detection model. This model combines machine learning classification techniques and graph-based methods, relying on linear algebra and parallel computing techniques. We show the utility of an ensemble learning approach in this context. We present some detection methods tests results on an representative access control dataset. The use of some explored classifiers gives results up to 99% of accuracy.

Keywords: cybersecurity, data protection, access control, insider threat, user behavior analysis, ensemble learning, high performance computing

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3572 Control Power in Doubly Fed Induction Generator Wind Turbine with SVM Control Inverter

Authors: Zerzouri Nora, Benalia Nadia, Bensiali Nadia

Abstract:

This paper presents a grid-connected wind power generation scheme using Doubly Fed Induction Generator (DFIG). This can supply power at constant voltage and constant frequency with the rotor speed varying. This makes it suitable for variable speed wind energy application. The DFIG system consists of wind turbine, asynchronous wound rotor induction generator, and inverter with Space Vector Modulation (SVM) controller. In which the stator is connected directly to the grid and the rotor winding is in interface with rotor converter and grid converter. The use of back-to-back SVM converter in the rotor circuit results in low distortion current, reactive power control and operate at variable speed. Mathematical modeling of the DFIG is done in order to analyze the performance of the systems and they are simulated using MATLAB. The simulation results for the system are obtained and hence it shows that the system can operate at variable speed with low harmonic current distortion. The objective is to track and extract maximum power from the wind energy system and transfer it to the grid for useful work.

Keywords: Doubly Fed Induction Generator, Wind Energy Conversion Systems, Space Vector Modulation, distortion harmonics

Procedia PDF Downloads 487
3571 Proniosomes as a Drug Carrier for Topical Delivery of Tolnaftate

Authors: Mona Mahmoud Abou Samra, Alaa Hamed Salama, Ghada Awad, Soheir Said Mansy

Abstract:

Proniosomes are well documented for topical drug delivery and preferred over other vesicular systems because they are biodegradable, biocompatible, non-toxic, possess skin penetration ability and prolong the release of drugs by acting as depot in deeper layers of skin. Proniosome drug delivery was preferred due to improved stability of the system than niosomes. The present investigation aimed at formulation development and performance evaluation of proniosomal gel as a vesicular drug carrier system for antifungal drug tolnaftate. Proniosomes was developed using different nonionic surfactants such as span 60 and span 65 with cholesterol in different molar ratios by the Coacervation phase separation method in presence or absence of either lecithin or phospholipon 80 H. Proniosomal gel formulations of tolnaftate were characterized for vesicular shape & size, entrapment efficiency, rheological properties and release study. The effect of surfactants and additives on the entrapment efficiency, particle size and percent of drug released was studied. The selected proniosomal formulations for topical delivery of tolnaftate was subjected to a microbiological study in male rats infected with Trichophyton rubrum; the main cause of Tinea Pedis compared to the free drug and a market product and the results was recorded.

Keywords: fungal infection, proniosome, tolnaftate, trichophyton rubrum

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3570 Study on the Thermal Conductivity about Porous Materials in Wet State

Authors: Han Yan, Jieren Luo, Qiuhui Yan, Xiaoqing Li

Abstract:

The thermal conductivity of porous materials is closely related to the thermal and moisture environment and the overall energy consumption of the building. The study of thermal conductivity of porous materials has great significance for the realization of low energy consumption building and economic construction building. Based on the study of effective thermal conductivity of porous materials at home and abroad, the thermal conductivity under a variety of different density of polystyrene board (EPS), plastic extruded board (XPS) and polyurethane (PU) and phenolic resin (PF) in wet state through theoretical analysis and experimental research has been studied. Initially, the moisture absorption and desorption properties of specimens had been discussed under different density, which led a result indicates the moisture absorption of four porous materials all have three stages, fast, stable and gentle. For the moisture desorption, there are two types. One is the existence of the rapid phase of the stage, such as XPS board, PU board. The other one does not have the fast desorption, instead, it is more stabilized, such as XPS board, PF board. Furthermore, the relationship between water content and thermal conductivity of porous materials had been studied and fitted, which figured out that in the wake of the increasing water content, the thermal conductivity of porous material is continually improving. At the same time, this result also shows, in different density, when the same kind of materials decreases, the saturated moisture content increases. Finally, the moisture absorption and desorption properties of the four kinds of materials are compared comprehensively, and it turned out that the heat preservation performance of PU board is the best, followed by EPS board, XPS board, PF board.

Keywords: porous materials, thermal conductivity, moisture content, transient hot-wire method

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3569 Sustainable Housing Framework for the Czech Republic: A Comparative Analysis of International and National Strategies

Authors: Jakub Adamec, Svatava Janouskova, Tomas Hak

Abstract:

The necessity of sustainable housing is explicitly embedded in ‘The 2030 agenda for sustainable development’, in particular, goal 11 ‘sustainable cities and communities’. Every UN member state is obligated to implement strategies from the agenda, including a strategy for sustainable housing into the practice in the local context. As shown in many countries, the lack of knowledge represses the adaptation process of sustainable strategies by governments. Hence, this study explores the concept of sustainable housing within the Czech Republic. The research elaborates on this term, and its current definition concerning ‘Geneva UN Charter on Sustainable Housing’. To this day, the charter represents the most comprehensive framework for a sustainable housing concept. Researchers conducted a comparative analysis of 38 international and 195 Czech national strategic documents. As a result, the charter‘s and strategic documents‘ goals were interconnected, identifying the most represented targets (e.g. improved environmental and energy performance of dwellings, resilient urban settlements which use renewable energy, and sustainable and integrated transport systems). The research revealed, even though the concept of sustainable housing is still dominated by environmental aspects, that social aspects significantly increased its importance. Additionally, this theoretical framework will serve as a foundation for the sustainable housing index development for the Czech Republic.

Keywords: comparative analysis, Czech national strategy, Geneva un charter, sustainable housing, urban theory

Procedia PDF Downloads 139
3568 2,7-diazaindole as a Potential Photophysical Probe for Excited State Deactivation Processes

Authors: Simran Baweja, Bhavika Kalal, Surajit Maity

Abstract:

Photoinduced tautomerization reactions have been the centre of attention among scientific community over past several decades because of their significance in various biological systems. 7-azaindole (7AI) is considered as a model system for DNA base pairing and to understand the role of such tautomerization reactions in mutations. To the best of our knowledge, extensive studies have been carried on 7-azaindole and its solvent clusters exhibiting proton/ hydrogen transfer in both solution as well as gas phase. Derivatives of above molecule, like 2,7- and 2,6-diazaindoles are proposed to have even better photophysical properties due to the presence of -aza group on the 2nd position. However, there are a few studies in the solution phase which suggest the relevance of these molecules, but there are no experimental studies reported in the gas phase yet. In our current investigation, we present the first gas phase spectroscopic data of 2,7-diazaindole (2,7-DAI) and its solvent cluster (2,7-DAI-H2O). In this, we have employed state-of-the-art laser spectroscopic methods such as fluorescence excitation (LIF), dispersed fluorescence (DF), resonant two-photon ionization time of flight mass spectrometry (2C-R2PI), photoionization efficiency spectroscopy (PIE), IR-UV double resonance spectroscopy i.e. fluorescence-dip infrared spectroscopy (FDIR) and resonant ion-dip infrared spectroscopy (IDIR) to understand the electronic structure of the molecule. The origin band corresponding to S1 ← S0 transition of the bare 2,7-DAI is found to be positioned at 33910 cm-1 whereas the origin band corresponding to S1 ← S0 transition of the 2,7-DAI-H2O is positioned at 33074 cm-1. The red shifted transition in case of solvent cluster suggests the enhanced feasibility of excited state hydrogen/ proton transfer. The ionization potential for the 2,7-DAI molecule is found to be 8.92 eV, which is significantly higher that the previously reported 7AI (8.11 eV) molecule, making it a comparatively complex molecule to study. The ionization potential is reduced by 0.14 eV in case of 2,7-DAI-H2O (8.78 eV) cluster compared to that of 2,7-DAI. Moreover, on comparison with the available literature values of 7AI, we found the origin band of 2,7-DAI and 2,7-DAI-H2O to be red shifted by -729 and -280 cm-1 respectively. The ground and excited state N-H stretching frequencies of the 27DAI molecule were determined using fluorescence-dip infrared spectra (FDIR) and resonant ion dip infrared spectroscopy (IDIR), obtained at 3523 and 3467 cm-1, respectively. The lower value of vNH in the electronic excited state of 27DAI implies the higher acidity of the group compared to the ground state. Moreover, we have done extensive computational analysis, which suggests that the energy barrier in excited state reduces significantly as we increase the number of catalytic solvent molecules (S= H2O, NH3) as well as the polarity of solvent molecules. We found that the ammonia molecule is a better candidate for hydrogen transfer compared to water because of its higher gas-phase basicity. Further studies are underway to understand the excited state dynamics and photochemistry of such N-rich chromophores.

Keywords: photoinduced tautomerization reactions, gas phse spectroscopy, ), IR-UV double resonance spectroscopy, resonant two-photon ionization time of flight mass spectrometry (2C-R2PI)

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3567 3D Classification Optimization of Low-Density Airborne Light Detection and Ranging Point Cloud by Parameters Selection

Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

Abstract:

Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

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3566 Estimating Anthropometric Dimensions for Saudi Males Using Artificial Neural Networks

Authors: Waleed Basuliman

Abstract:

Anthropometric dimensions are considered one of the important factors when designing human-machine systems. In this study, the estimation of anthropometric dimensions has been improved by using Artificial Neural Network (ANN) model that is able to predict the anthropometric measurements of Saudi males in Riyadh City. A total of 1427 Saudi males aged 6 to 60 years participated in measuring 20 anthropometric dimensions. These anthropometric measurements are considered important for designing the work and life applications in Saudi Arabia. The data were collected during eight months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining 15 dimensions were set to be the measured variables (Model’s outcomes). The hidden layers varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was able to estimate the body dimensions of Saudi male population in Riyadh City. The network's mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found to be 0.0348 and 3.225, respectively. These results were found less, and then better, than the errors found in the literature. Finally, the accuracy of the developed neural network was evaluated by comparing the predicted outcomes with regression model. The ANN model showed higher coefficient of determination (R2) between the predicted and actual dimensions than the regression model.

Keywords: artificial neural network, anthropometric measurements, back-propagation

Procedia PDF Downloads 489
3565 Magnification Factor Based Seismic Response of Moment Resisting Frames with Open Ground Storey

Authors: Subzar Ahmad Bhat, Saraswati Setia, V. K.Sehgal

Abstract:

During the past earthquakes, open ground storey buildings have performed poorly due to the soft storey defect. Indian Standard IS 1893:2002 allows analysis of open ground storey buildings without considering infill stiffness but with a multiplication factor 2.5 in compensation for the stiffness discontinuity. Therefore, the aim of this paper is to check the applicability of the multiplication factor of 2.5 and study behaviour of the structure after the application of the multiplication factor. For this purpose, study is performed on models considering infill stiffness using SAP 2000 (Version 14) by linear static analysis and response spectrum analysis. Total seven models are analysed and designed for the range of multiplication factor ranging from 1.25 to 2.5. The value of multiplication factor equal to 2.5 has been found on the higher side, resulting in increased dimension and percentage of reinforcement without significant enhancement beyond a certain multiplication factor. When the building with OGS is designed for values of MF higher than 1.25 considering infill stiffness soft storey effect shifts from ground storey to first storey. For the analysis of the OGS structure best way to analysis the structure is to analyse it as the frame with stiffness and strength of the infill taken into account. The provision of infill walls in the upper storeys enhances the performance of the structure in terms of displacement and storey drift controls.

Keywords: open ground storey, multiplication factor, IS 1893:2002 provisions, static analysis, response spectrum analysis, infill stiffness, equivalent strut

Procedia PDF Downloads 397