Search results for: indoor network performance
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 16455

Search results for: indoor network performance

10755 Predictive Analysis of the Stock Price Market Trends with Deep Learning

Authors: Suraj Mehrotra

Abstract:

The stock market is a volatile, bustling marketplace that is a cornerstone of economics. It defines whether companies are successful or in spiral. A thorough understanding of it is important - many companies have whole divisions dedicated to analysis of both their stock and of rivaling companies. Linking the world of finance and artificial intelligence (AI), especially the stock market, has been a relatively recent development. Predicting how stocks will do considering all external factors and previous data has always been a human task. With the help of AI, however, machine learning models can help us make more complete predictions in financial trends. Taking a look at the stock market specifically, predicting the open, closing, high, and low prices for the next day is very hard to do. Machine learning makes this task a lot easier. A model that builds upon itself that takes in external factors as weights can predict trends far into the future. When used effectively, new doors can be opened up in the business and finance world, and companies can make better and more complete decisions. This paper explores the various techniques used in the prediction of stock prices, from traditional statistical methods to deep learning and neural networks based approaches, among other methods. It provides a detailed analysis of the techniques and also explores the challenges in predictive analysis. For the accuracy of the testing set, taking a look at four different models - linear regression, neural network, decision tree, and naïve Bayes - on the different stocks, Apple, Google, Tesla, Amazon, United Healthcare, Exxon Mobil, J.P. Morgan & Chase, and Johnson & Johnson, the naïve Bayes model and linear regression models worked best. For the testing set, the naïve Bayes model had the highest accuracy along with the linear regression model, followed by the neural network model and then the decision tree model. The training set had similar results except for the fact that the decision tree model was perfect with complete accuracy in its predictions, which makes sense. This means that the decision tree model likely overfitted the training set when used for the testing set.

Keywords: machine learning, testing set, artificial intelligence, stock analysis

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10754 Prediction of Wind Speed by Artificial Neural Networks for Energy Application

Authors: S. Adjiri-Bailiche, S. M. Boudia, H. Daaou, S. Hadouche, A. Benzaoui

Abstract:

In this work the study of changes in the wind speed depending on the altitude is calculated and described by the model of the neural networks, the use of measured data, the speed and direction of wind, temperature and the humidity at 10 m are used as input data and as data targets at 50m above sea level. Comparing predict wind speeds and extrapolated at 50 m above sea level is performed. The results show that the prediction by the method of artificial neural networks is very accurate.

Keywords: MATLAB, neural network, power low, vertical extrapolation, wind energy, wind speed

Procedia PDF Downloads 670
10753 Effect of Diet Inulin Prebiotic on Growth, Reproductive Performance, Carcass Composition and Resistance to Environmental Stresses in Zebra Danio (Danio rerio)

Authors: Ehsan Ahmadifar

Abstract:

In this research, the effects of different levels (control group (T0), (T1)1, (T2)2 and (T3)3 gr Inulin per Kg diet) of prebiotic Inulin as nutritional supplement on Danio rerio were investigated for 4 month. Since the beginning of feeding larvae until adult (average weight: 67.1 g, length: 4.5 cm) were fed with experimental diets. The survival rate of fish had no significant effect on rate survival (P > 0.05). The highest food conversion ratio (FCR) was in control group and the lowest was observed in T3. Treatment of T3 significantly caused the best feed conversion ratio in Zebra fish (P < 0.05). By increasing the inulin diet during the experiment, specific growth rate increased. The highest and the lowest body weight gain and condition factor were observed in T3 and control, respectively (P < 0.05). Adding 3 gr inulin in Zebra fish diet can improve the performance of the growth indices and final biomass, also this prebiotic can be considered as a suitable supplement for Cyprinidae diet. In the first sampling stage for feeding fish, fat and muscle protein was significantly higher than the second sampling stage (P < 0.05). Given that the second stage fish were full sexual maturity, the amount of fat in muscle decreased (P < 0.05). Moisture and ash levels were significantly (P < 0.05) higher in the second stage sampling than the first stage. Overall, different stage of living affected on muscle chemical composition muscle. Reproductive performance in treatment T2 and T3 were significantly higher than other treatments (P < 0.05). According to the results, the prebiotic inulin does not have a significant impact on the sex ratio in zebrafish (P > 0.05). Based on histology of the gonads, the use of dietary inulin accelerates the process of gonad development in zebrafish.

Keywords: inulin, zebrafish, reproduction, histology

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10752 Performing Fat Activism in Australia: An Autoethnographic Exploration

Authors: Jenny Lee

Abstract:

Fat Studies is emerging as an interdisciplinary area of study, intersecting with Gender Studies, Sociology, Human Development and the Creative Arts. A focus on weight loss, and, therefore, fat hatred, has resulted in a form of discriminatory institutional practice that impacts women in the Western world. This focus is sanctioned by a large dieting industry, medical associations, the media, and at times, government initiatives. This paper will discuss the emergence of the so-called ‘Obesity Epidemic’ in Australia and the Western world and the stereotypes that thin equals healthy and fat equals unhealthy. This paper will argue that, for those with a health focus, ‘Health at every size’ is a more effective principle, which involves striving for healthy living, without a focus on weight loss. This discussion will contextualise an autoethnographic exploration of how fat acceptance and Health at Every Size can be encouraged through fat activism and fat political art. As part of this paper, a selection of the recent performance, writing and art in Australia will be presented, including Aquaporko, the fat femme synchronised swim team and VaVaBoomBah, the Melbourne fat burlesque performances.

Keywords: activism, fat, health, obesity, performance

Procedia PDF Downloads 168
10751 Artificial Neural Network Based Model for Detecting Attacks in Smart Grid Cloud

Authors: Sandeep Mehmi, Harsh Verma, A. L. Sangal

Abstract:

Ever since the idea of using computing services as commodity that can be delivered like other utilities e.g. electric and telephone has been floated, the scientific fraternity has diverted their research towards a new area called utility computing. New paradigms like cluster computing and grid computing came into existence while edging closer to utility computing. With the advent of internet the demand of anytime, anywhere access of the resources that could be provisioned dynamically as a service, gave rise to the next generation computing paradigm known as cloud computing. Today, cloud computing has become one of the most aggressively growing computer paradigm, resulting in growing rate of applications in area of IT outsourcing. Besides catering the computational and storage demands, cloud computing has economically benefitted almost all the fields, education, research, entertainment, medical, banking, military operations, weather forecasting, business and finance to name a few. Smart grid is another discipline that direly needs to be benefitted from the cloud computing advantages. Smart grid system is a new technology that has revolutionized the power sector by automating the transmission and distribution system and integration of smart devices. Cloud based smart grid can fulfill the storage requirement of unstructured and uncorrelated data generated by smart sensors as well as computational needs for self-healing, load balancing and demand response features. But, security issues such as confidentiality, integrity, availability, accountability and privacy need to be resolved for the development of smart grid cloud. In recent years, a number of intrusion prevention techniques have been proposed in the cloud, but hackers/intruders still manage to bypass the security of the cloud. Therefore, precise intrusion detection systems need to be developed in order to secure the critical information infrastructure like smart grid cloud. Considering the success of artificial neural networks in building robust intrusion detection, this research proposes an artificial neural network based model for detecting attacks in smart grid cloud.

Keywords: artificial neural networks, cloud computing, intrusion detection systems, security issues, smart grid

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10750 Effect of Feeding Broilers on Diets Enriching With Omega-3 Fatty Acids Sources

Authors: Khalid Mahmoud Gaafar

Abstract:

In human diets , ω-6 and ω-3 are important essential fatty acids for immunity and health. However, considerable alteration in dietary patterns and contents has resulted in change of the consumption of such fatty acids ,with subsequent increase in the consumption of ω-6 fatty acids and a marked decrease in the consumption of ω-3 fatty acids. This dietary alteration has led to an imbalance in the ratio for ω-6/ω-3, which at 20:1 now differs considerably from the original ratio (1:1). Therefore, dietary supplements such as eggs and meat enriched with omega 3 are necessary to increase the consumption of ω-3 to meet the recommended need for ω-3. Foods that supply ω-6 fatty acids include soybean, palm , sunflower, and rapeseed oils, whereas foods that supply ω-3 fatty acids such as linseed and fish oils. Lin seed oils contain Alpha – linolenic acid (ALA), which can be converted to DHA and EPA in the birds body, with linseed oil containing more than 50% ALA. On the other hand, high doses of omega 6 sources in the diet may have deleterious effects on humans. Maintaining an optimum ratio of ω-3 and ω-6fatty acids not only improves performance but also prevents these health risks. The ratio of n-6:ω-3 fatty acids also plays an important role in the immune response, production performance of broilers and designing meat enriched with ω-3 polyunsaturated fatty acids (PUFAs). Birds of three experimental groups fed on basal starter (0-2nd weeks), grower (3rd -4th weeks) and finisher (5th week) rations. The first is control group fed during the grower-finisher periods on basic diet with two replicate (one fed on basic diet contain vegetable oil and the other don’t) without any additives. The three experimental groups (T1 – T2 –T3) fed during the grower- finisher periods on diets free from vegetable oils and contain of 5% of extruded mixture of soybean and linseed (60%:40%). The second (T2) and third (T3) experimental groups supplemented with vitamin B12 and enzyme mixture. The first experimental groups don’t receive vitamins or enzymes. The obtained results showed a significant increased growth performance, immune response, highest antioxidant activity and serum HDL with lowest serum LDL and triglycerides levels in all experimental groups compared with control group, which was highly significant in group fed on vitamin B6.

Keywords: omega fatty acids, broiler, feeding, human health, growth performance, immunity

Procedia PDF Downloads 98
10749 Extracting Opinions from Big Data of Indonesian Customer Reviews Using Hadoop MapReduce

Authors: Veronica S. Moertini, Vinsensius Kevin, Gede Karya

Abstract:

Customer reviews have been collected by many kinds of e-commerce websites selling products, services, hotel rooms, tickets and so on. Each website collects its own customer reviews. The reviews can be crawled, collected from those websites and stored as big data. Text analysis techniques can be used to analyze that data to produce summarized information, such as customer opinions. Then, these opinions can be published by independent service provider websites and used to help customers in choosing the most suitable products or services. As the opinions are analyzed from big data of reviews originated from many websites, it is expected that the results are more trusted and accurate. Indonesian customers write reviews in Indonesian language, which comes with its own structures and uniqueness. We found that most of the reviews are expressed with “daily language”, which is informal, do not follow the correct grammar, have many abbreviations and slangs or non-formal words. Hadoop is an emerging platform aimed for storing and analyzing big data in distributed systems. A Hadoop cluster consists of master and slave nodes/computers operated in a network. Hadoop comes with distributed file system (HDFS) and MapReduce framework for supporting parallel computation. However, MapReduce has weakness (i.e. inefficient) for iterative computations, specifically, the cost of reading/writing data (I/O cost) is high. Given this fact, we conclude that MapReduce function is best adapted for “one-pass” computation. In this research, we develop an efficient technique for extracting or mining opinions from big data of Indonesian reviews, which is based on MapReduce with one-pass computation. In designing the algorithm, we avoid iterative computation and instead adopt a “look up table” technique. The stages of the proposed technique are: (1) Crawling the data reviews from websites; (2) cleaning and finding root words from the raw reviews; (3) computing the frequency of the meaningful opinion words; (4) analyzing customers sentiments towards defined objects. The experiments for evaluating the performance of the technique were conducted on a Hadoop cluster with 14 slave nodes. The results show that the proposed technique (stage 2 to 4) discovers useful opinions, is capable of processing big data efficiently and scalable.

Keywords: big data analysis, Hadoop MapReduce, analyzing text data, mining Indonesian reviews

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10748 Thermodynamic Attainable Region for Direct Synthesis of Dimethyl Ether from Synthesis Gas

Authors: Thulane Paepae, Tumisang Seodigeng

Abstract:

This paper demonstrates the use of a method of synthesizing process flowsheets using a graphical tool called the GH-plot and in particular, to look at how it can be used to compare the reactions of a combined simultaneous process with regard to their thermodynamics. The technique uses fundamental thermodynamic principles to allow the mass, energy and work balances locate the attainable region for chemical processes in a reactor. This provides guidance on what design decisions would be best suited to developing new processes that are more effective and make lower demands on raw material and energy usage.

Keywords: attainable regions, dimethyl ether, optimal reaction network, GH Space

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10747 Performance Analysis of a Hybrid DF-AF Hybrid RF/FSO System under Gamma Gamma Atmospheric Turbulence Channel Using MPPM Modulation

Authors: Hechmi Saidi, Noureddine Hamdi

Abstract:

The performance of hybrid amplify and forward - decode and forward (AF-DF) hybrid radio frequency/free space optical (RF/FSO) communication system, that adopts M-ary pulse position modulation (MPPM) techniques, is analyzed. Both exact and approximate symbol-error rates (SERs) are derived. The random variations of the received optical irradiance, produced by the atmospheric turbulence, is modeled by the gamma-gamma (GG) statistical distribution. A closed-form expression for the probability density function (PDF) is derived for the whole above system is obtained. Thanks to the use of hybrid AF-DF hybrid RF/FSO configuration and MPPM, the effects of atmospheric turbulence is mitigated; hence the capacity of combating atmospheric turbulence and the transmissitted signal quality are improved.

Keywords: free space optical, gamma gamma channel, radio frequency, decode and forward, error pointing, M-ary pulse position modulation, symbol error rate

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10746 Forced Degradation Study of Rifaximin Formulated Tablets to Determine Stability Indicating Nature of High-Performance Liquid Chromatography Analytical Method

Authors: Abid Fida Masih

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Forced degradation study of Rifaximin was conducted to determine the stability indicating potential of HPLC testing method for detection of Rifaximin in formulated tablets to be employed for quality control and stability testing. The questioned method applied with mobile phase methanol: water (70:30), 5µm, 250 x 4.6mm, C18 column, wavelength 293nm and flow rate of 1.0 ml/min. Forced degradation study was performed under oxidative, acidic, basic, thermal and photolytic conditions. The applied method successfully determined the degradation products after acidic and basic degradation without interfering with Rifaximin detection. Therefore, the method was said to be stability indicating and can be applied for quality control and stability testing of Rifaxmin tablets during its shelf life.

Keywords: forced degradation, high-performance liquid chromatography, method validation, rifaximin, stability indicating method

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10745 Understanding the Impact of Resilience Training on Cognitive Performance in Military Personnel

Authors: Haji Mohammad Zulfan Farhi Bin Haji Sulaini, Mohammad Azeezudde’en Bin Mohd Ismaon

Abstract:

The demands placed on military athletes extend beyond physical prowess to encompass cognitive resilience in high-stress environments. This study investigates the effects of resilience training on the cognitive performance of military athletes, shedding light on the potential benefits and implications for optimizing their overall readiness. In a rapidly evolving global landscape, armed forces worldwide are recognizing the importance of cognitive resilience alongside physical fitness. The study employs a mixed-methods approach, incorporating quantitative cognitive assessments and qualitative data from military athletes undergoing resilience training programs. Cognitive performance is evaluated through a battery of tests, including measures of memory, attention, decision-making, and reaction time. The participants, drawn from various branches of the military, are divided into experimental and control groups. The experimental group undergoes a comprehensive resilience training program, while the control group receives traditional physical training without a specific focus on resilience. The initial findings indicate a substantial improvement in cognitive performance among military athletes who have undergone resilience training. These improvements are particularly evident in domains such as attention and decision-making. The experimental group demonstrated enhanced situational awareness, quicker problem-solving abilities, and increased adaptability in high-stress scenarios. These results suggest that resilience training not only bolsters mental toughness but also positively impacts cognitive skills critical to military operations. In addition to quantitative assessments, qualitative data is collected through interviews and surveys to gain insights into the subjective experiences of military athletes. Preliminary analysis of these narratives reveals that participants in the resilience training program report higher levels of self-confidence, emotional regulation, and an improved ability to manage stress. These psychological attributes contribute to their enhanced cognitive performance and overall readiness. Moreover, this study explores the potential long-term benefits of resilience training. By tracking participants over an extended period, we aim to assess the durability of cognitive improvements and their effects on overall mission success. Early results suggest that resilience training may serve as a protective factor against the detrimental effects of prolonged exposure to stressors, potentially reducing the risk of burnout and psychological trauma among military athletes. This research has significant implications for military organizations seeking to optimize the performance and well-being of their personnel. The findings suggest that integrating resilience training into the training regimen of military athletes can lead to a more resilient and cognitively capable force. This, in turn, may enhance mission success, reduce the risk of injuries, and improve the overall effectiveness of military operations. In conclusion, this study provides compelling evidence that resilience training positively impacts the cognitive performance of military athletes. The preliminary results indicate improvements in attention, decision-making, and adaptability, as well as increased psychological resilience. As the study progresses and incorporates long-term follow-ups, it is expected to provide valuable insights into the enduring effects of resilience training on the cognitive readiness of military athletes, contributing to the ongoing efforts to optimize military personnel's physical and mental capabilities in the face of ever-evolving challenges.

Keywords: military athletes, cognitive performance, resilience training, cognitive enhancement program

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10744 High Temperature and High Pressure Purification of Hydrogen from Syngas Using Metal Organic Framework Adsorbent

Authors: Samira Rostom, Robert Symonds, Robin W. Hughes

Abstract:

Hydrogen is considered as one of the most important clean and renewable energy carriers for a sustainable energy future. However, its efficient and cost-effective purification remains challenging. This paper presents the potential of using metal–organic frameworks (MOFs) in combination with pressure swing adsorption (PSA) technology for syngas based H2 purification. PSA process analysis is done considering high pressure and elevated temperature process conditions, it reduces the demand for off-gas recycle to the fuel reactor and simultaneously permits higher desorption pressure, thereby reducing the parasitic load on the hydrogen compressor. The elevated pressure and temperature adsorption we present here is beneficial to minimizing overall process heating and cooling demand compared to existing processes. Here, we report the comparative performance of zeolite-5A, Cu-BTC, and the mix of zeolite-5A/Cu-BTC for H2 purification from syngas typical of those exiting water-gas-shift reactors. The MOFs were synthesized hydrothermally and then mixed systematically at different weight ratios to find the optimum composition based on the adsorption performance. The formation of different compounds were characterized by XRD, N2 adsorption and desorption, SEM, FT-IR, TG, and water vapor adsorption technologies. Single-component adsorption isotherms of CO2, CO, CH4, N2, and H2 over single materials and composites were measured at elevated pressures and different temperatures to determine their equilibrium adsorption capacity. The examination of the stability and regeneration performance of metal–organic frameworks was carried out using a gravimetric system at temperature ranges of 25-150℃ for a pressure range of 0-30 bar. The studies of adsorption/desorption on the MOFs showed selective adsorption of CO2, CH4, CO, and N2 over H2. Overall, the findings of this study suggest that the Ni-MOF-74/Cu-BTC composites are promising candidates for industrial H2 purification processes.

Keywords: MOF, H2 purification, high T, PSA

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10743 Dynamic Capability: An Exploratory Study Applied to Social Enterprise in South East Asia

Authors: Atiwat Khatpibunchai, Taweesak Kritjaroen

Abstract:

A social enterprise is the innovative hybrid organizations where its ultimate goal is to generate revenue and use it as a fund to solve the social and environmental problem. Although the evidence shows the clear value of economic, social and environmental aspects, the limitations of most of the social enterprises are the expanding impact of social and environmental aspects through the normal market mechanism. This is because the major sources of revenues of social enterprises derive from the business advocates who merely wish to support society and environment by using products and services of social enterprises rather than expect the satisfaction and the distinctive advantage of products and services. Thus, social enterprises cannot reach the achievement as other businesses do. The relevant concepts from the literature review revealed that dynamic capability is the ability to sense, integrate and reconfigure internal resources and utilize external resources to adapt to changing environments, create innovation and achieve competitive advantage. The objective of this research is to study the influence of dynamic capability that affects competitive advantage and sustainable performance, as well as to determine important elements of dynamic capability. The researchers developed a conceptual model from the related concepts and theories of dynamic capability. A conceptual model will support and show the influence of dynamic capability on competitive advantage and sustainable performance of social enterprises. The 230 organizations in South-East Asia served as participants in this study. The results of the study were analyzed by the structural equation model (SEM) and it was indicated that research model is consistent with empirical research. The results also demonstrated that dynamic capability has a direct and indirect influence on competitive advantage and sustainable performance. Moreover, it can be summarized that dynamic capability consists of the five elements: 1) the ability to sense an opportunity; 2) the ability to seize an opportunity; 3) the ability to integrate resources; 4) the ability to absorb resources; 5) the ability to create innovation. The study recommends that related sectors can use this study as a guideline to support and promote social enterprises. The focus should be pointed to the important elements of dynamic capability that are the development of the ability to transform existing resources in the organization and the ability to seize opportunity from changing market.

Keywords: dynamic capability, social enterprise, sustainable competitive advantage, sustainable performance

Procedia PDF Downloads 238
10742 A Survey of Domain Name System Tunneling Attacks: Detection and Prevention

Authors: Lawrence Williams

Abstract:

As the mechanism which converts domains to internet protocol (IP) addresses, Domain Name System (DNS) is an essential part of internet usage. It was not designed securely and can be subject to attacks. DNS attacks have become more frequent and sophisticated and the need for detecting and preventing them becomes more important for the modern network. DNS tunnelling attacks are one type of attack that are primarily used for distributed denial-of-service (DDoS) attacks and data exfiltration. Discussion of different techniques to detect and prevent DNS tunneling attacks is done. The methods, models, experiments, and data for each technique are discussed. A proposal about feasibility is made. Future research on these topics is proposed.

Keywords: DNS, tunneling, exfiltration, botnet

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10741 Effectiveness of an Intervention to Increase Physics Students' STEM Self-Efficacy: Results of a Quasi-Experimental Study

Authors: Stephanie J. Sedberry, William J. Gerace, Ian D. Beatty, Michael J. Kane

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Increasing the number of US university students who attain degrees in STEM and enter the STEM workforce is a national priority. Demographic groups vary in their rates of participation in STEM, and the US produces just 10% of the world’s science and engineering degrees (2014 figures). To address these gaps, we have developed and tested a practical, 30-minute, single-session classroom-based intervention to improve students’ self-efficacy and academic performance in University STEM courses. Self-efficacy is a psychosocial construct that strongly correlates with academic success. Self-efficacy is a construct that is internal and relates to the social, emotional, and psychological aspects of student motivation and performance. A compelling body of research demonstrates that university students’ self-efficacy beliefs are strongly related to their selection of STEM as a major, aspirations for STEM-related careers, and persistence in science. The development of an intervention to increase students’ self-efficacy is motivated by research showing that short, social-psychological interventions in education can lead to large gains in student achievement. Our intervention addresses STEM self-efficacy via two strong, but previously separate, lines of research into attitudinal/affect variables that influence student success. The first is ‘attributional retraining,’ in which students learn to attribute their successes and failures to internal rather than external factors. The second is ‘mindset’ about fixed vs. growable intelligence, in which students learn that the brain remains plastic throughout life and that they can, with conscious effort and attention to thinking skills and strategies, become smarter. Extant interventions for both of these constructs have significantly increased academic performance in the classroom. We developed a 34-item questionnaire (Likert scale) to measure STEM Self-efficacy, Perceived Academic Control, and Growth Mindset in a University STEM context, and validated it with exploratory factor analysis, Rasch analysis, and multi-trait multi-method comparison to coded interviews. Four iterations of our 42-week research protocol were conducted across two academic years (2017-2018) at three different Universities in North Carolina, USA (UNC-G, NC A&T SU, and NCSU) with varied student demographics. We utilized a quasi-experimental prospective multiple-group time series research design with both experimental and control groups, and we are employing linear modeling to estimate the impact of the intervention on Self-Efficacy,wth-Mindset, Perceived Academic Control, and final course grades (performance measure). Preliminary results indicate statistically significant effects of treatment vs. control on Self-Efficacy, Growth-Mindset, Perceived Academic Control. Analyses are ongoing and final results pending. This intervention may have the potential to increase student success in the STEM classroom—and ownership of that success—to continue in a STEM career. Additionally, we have learned a great deal about the complex components and dynamics of self-efficacy, their link to performance, and the ways they can be impacted to improve students’ academic performance.

Keywords: academic performance, affect variables, growth mindset, intervention, perceived academic control, psycho-social variables, self-efficacy, STEM, university classrooms

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10740 Prediction Modeling of Compression Properties of a Knitted Sportswear Fabric Using Response Surface Method

Authors: Jawairia Umar, Tanveer Hussain, Zulfiqar Ali, Muhammad Maqsood

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Different knitted structures and knitted parameters play a vital role in the stretch and recovery management of compression sportswear in addition to the materials use to generate this stretch and recovery behavior of the fabric. The present work was planned to predict the different performance indicators of a compression sportswear fabric with some ground parameters i.e. base yarn stitch length (polyester as base yarn and spandex as plating yarn involve to make a compression fabric) and linear density of the spandex which is a key material of any sportswear fabric. The prediction models were generated by response surface method for performance indicators such as stretch & recovery percentage, compression generated by the garment on body, total elongation on application of high power force and load generated on certain percentage extension in fabric. Certain physical properties of the fabric were also modeled using these two parameters.

Keywords: Compression, sportswear, stretch and recovery, statistical model, kikuhime

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10739 Quality of Education in Dilla Zone

Authors: Gezahegn Bekele Welldgiyorgise

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It is obvious that the economics, politics and social conditions of a country are determined by the quality and standard of its education. Indeed, education plays a vital role in changing the consciousness and awareness of society and transforming it on a large scale. Moreover, education contributes a lot to the advancement of science and technology, information and communication, and above all, it speeds up its progress in no time if it focuses mainly on the qualitative approach to education. Education brings about universal change and transformation and lightens mankind in all dimensions. It creates an educated, enlightened and brightened generation in society. The generation will be sharped, sharpened and well-oriented if it gets modern, sophisticated and standardized education in its field of study. The main goal of education is to produce well-qualified, well-trained and disciplined young offers in a given community. If the youth is well trained and well-mannered, he will certainly be enlightened, problem solvers and solution seekers, researchers, and innovators. In this respect, we have to provide the youth with modern education, a teaching-learning process led by active learning and a participatory approach with a new curriculum preparation for the age of children supported by modern facilities (ICT).In addition to that, the curriculum should have to give attention to mathematics and science lessons that include international experience in a comfortable school and classrooms. Therefore, the generation that will be created through such kinds of the guided education system will make the students active participants, self-confident, researchers and problem solvers, besides that result in changed life standards and a developed country. Similarly, our country, Ethiopia, has aimed to get such change in youth (generation) through modern education, designing a new educational policy and curriculum which was implemented for many years, although the goal of education has not reached the required level. To get the main idea of the article, I should have answered the question of why our country's educational goal had not reached the desired level because it is necessary to lay the foundation for research in finding out problems seen through students learning performance, the first task is selecting primary-school as a sample. Therefore, we selected “Dilla primary school (5-8)” which is a workplace for a teacher and gives me a chance to recognize students’ learning performance to recognize their learning grades (internal and external) and measure performance (achievement) of students easily’.

Keywords: curriculum, performance, innovation, learning

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10738 Effect of High-Intensity Core Muscle Exercises Training on Sport Performance in Dancers

Authors: Che Hsiu Chen, Su Yun Chen, Hon Wen Cheng

Abstract:

Traditional core stability, core endurance, and balance exercises on a stable surface with isometric muscle actions, low loads, and multiple repetitions, which may not improvements the swimming and running economy performance. However, the effects of high intensity core muscle exercise training on jump height, sprint, and aerobic fitness remain unclear. The purpose of this study was to examine whether high intensity core muscle exercises training could improve sport performances in dancers. Thirty healthy university dancer students (28 women and 2 men; age 20.0 years, height 159.4 cm, body mass 52.7 kg) were voluntarily participated in this study, and each participant underwent five suspension exercises (e.g., hip abduction in plank alternative, hamstring curl, 45-degree row, lunge and oblique crunch). Each type of exercise was performed for 30-second, with 30-second of rest between exercises, two times per week for eight weeks and each exercise session was increased by 10-second every week. We measured agility, explosive force, anaerobic and cardiovascular fitness in dancer performance before and after eight weeks of training. The results showed that the 8-week high intensity core muscle training would significantly increase T-test agility (7.78%), explosive force of acceleration (3.35%), vertical jump height (8.10%), jump power (6.95%), lower extremity anaerobic ability (7.10%) and oxygen uptake efficiency slope (4.15%). Therefore, it can be concluded that eight weeks of high intensity core muscle exercises training can improve not only agility, sprint ability, vertical jump ability, anaerobic and but also cardiovascular fitness measures as well.

Keywords: balance, jump height, sprint, maximal oxygen uptake

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10737 Improving the Exploitation of Fluid in Elastomeric Polymeric Isolator

Authors: Haithem Elderrat, Huw Davies, Emmanuel Brousseau

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Elastomeric polymer foam has been used widely in the automotive industry, especially for isolating unwanted vibrations. Such material is able to absorb unwanted vibration due to its combination of elastic and viscous properties. However, the ‘creep effect’, poor stress distribution and susceptibility to high temperatures are the main disadvantages of such a system. In this study, improvements in the performance of elastomeric foam as a vibration isolator were investigated using the concept of Foam Filled Fluid (FFFluid). In FFFluid devices, the foam takes the form of capsule shapes, and is mixed with viscous fluid, while the mixture is contained in a closed vessel. When the FFFluid isolator is affected by vibrations, energy is absorbed, due to the elastic strain of the foam. As the foam is compressed, there is also movement of the fluid, which contributes to further energy absorption as the fluid shears. Also, and dependent on the design adopted, the packaging could also attenuate vibration through energy absorption via friction and/or elastic strain. The present study focuses on the advantages of the FFFluid concept over the dry polymeric foam in the role of vibration isolation. This comparative study between the performance of dry foam and the FFFluid was made according to experimental procedures. The paper concludes by evaluating the performance of the FFFluid isolator in the suspension system of a light vehicle. One outcome of this research is that the FFFluid may preferable over elastomer isolators in certain applications, as it enables a reduction in the effects of high temperatures and of ‘creep effects’, thereby increasing the reliability and load distribution. The stiffness coefficient of the system has increased about 60% by using an FFFluid sample. The technology represented by the FFFluid is therefore considered by this research suitable for application in the suspension system of a light vehicle.

Keywords: FFFluid, dry foam, anti-vibration devices, elastomeric polymer foam

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10736 Apply Activity-Based Costing Management System by Key Success Paths to Promote the Competitive Advantages and Operation Performance

Authors: Mei-Fang Wu, Shu-Li Wang, Feng-Tsung Cheng

Abstract:

Highly developed technology and highly competitive global market highlight the important role of competitive advantages and operation performances in sustainable company operation. Activity-Based Costing (ABC) provides accurate operation cost and operation performance information. Rich literature provide relevant research with cases study on Activity-Based Costing application, and yet, there is no research studying on cause relationship between key success factors of applying Activity-Based Costing and its specific outcomes, such as profitability or share market. These relationships provide the ways to handle the key success factors to achieve the specific outcomes for ensuring to promote the competitive advantages and operation performances. The main purposes of this research are exploring the key success paths by Key Success Paths approach which will lead the ways to apply Activity-Base Costing. The Key Success Paths is the innovative method which is exploring the cause relationships and explaining what are the effects of key success factors to specific outcomes of Activity-Based Costing implementation. The cause relationships between key success factors and successful specific outcomes are Key Success Paths (KSPs). KSPs are the guidelines to lead the cost management strategies to achieve the goals of competitive advantages and operation performances. The research findings indicate that good management system design may impact the good outcomes of Activity-Based Costing application and achieve to outstanding competitive advantage, operating performance and profitability as well by KSPs exploration.

Keywords: activity-based costing, key success factors, key success paths approach, key success paths, key failure paths

Procedia PDF Downloads 375
10735 Impact of Climate Change on Energy Consumption of the Residential Building Stock in Turkey

Authors: Sadik Yigit

Abstract:

The energy consumed in the buildings constitutes a large portion of the total energy consumption in the world. In this study, it was aimed to measure the impact of climate change on the energy consumption of residential building stock by analyzing a typical mid-rise residential building in four different climate regions of Turkey. An integrated system was developed using the "Distribution Evolutionary Algorithms in Python" tool and Energy Plus. By using the developed integrated system, the energy performance of the typical residential building was analyzed under the effect of different climate change scenarios. The results indicated that predicted overheating will be experienced in the future, which will significantly increase the cooling energy loads of the buildings. In addition, design solutions to improve the future energy performance of the buildings were proposed, considering budget constraints. The results of the study will guide researchers studying in this area of research and designers in the sector in finding climate change resilient design solutions.

Keywords: energy_efficient, residential buildings, climate change, energyplus

Procedia PDF Downloads 91
10734 The Sectoral Differences in the Use of Construction Incentive

Authors: Qiuwen Ma, Sai On Cheung

Abstract:

Incentive contracting has been developed to push the agent team for extra effort. Generally, there are three types of incentive arrangement, namely incentive/penalty for super performance/underperformance, risk/reward sharing and future business opportunities. It is found that there are significant differences in the use of incentive arrangement in private and public projects. In Hong Kong, very few public projects have used future business as incentivizer whereas private developers often signal repeated business coupled with heavy penalty. This study was conducted to identify various attributes affecting the use of I/D in both private and public engineering sectors of Hong Kong. The diverging preferences were unveiled with reference to a literature review and semi-structured interviews with industry experts. The findings reveal the public/private sectors would consider the implementation issues regarding the various performance targets. The most deterministic factor for the public sector is about accountability. The private sector is in general skeptical about the need to provide extra for the contractors for what they have already contracted to perform.

Keywords: construction incentive, public/private projects, semi-structured interview, hong kong

Procedia PDF Downloads 78
10733 Project Stakeholders' Perceptions of Sustainability: A Case Example From the Turkish Construction Industry

Authors: F. Heyecan Giritli, Gizem Akgül

Abstract:

Because of the raising population of world; the need for houses, buildings and infrastructures are increasing rapidly. Energy and water consumption, waste production continues to increase. If this situation of resources continues, there will be a significant loss for next generations. Therefore, there are a lot of researches and solutions developed in the world. Also sustainability criteria are collected together by some countries to serve construction industry with certification systems. Sustainable building production process’s scope requires different path from traditional building production process. Moreover, the key objective of sustainable buildings is that the process includes whole life cycle duration. The process approaches from the decision of the project to the end of it; so the project team is needed from the beginning of the integrated project delivery model. Further more, by defining project team at the beginning of the project provides communication among the team members and defined problem solving and decision making methods. In this research includes the certification systems among the world to comprehend the head lines and assessment criteria. Therefore, it is understand that usually all green building criteria have the same contents. The aim of this research is to assess the sustainable project stakeholder’ perceptions in Turkish construction industry from the point of occupation, job title and years of experience. Therefore, a survey is made to assess the perceptions of each attendant. In Turkey, sustainability criteria are not clearly defined; on the other hand some regulations like waste management, energy efficiency are made by legal agencies. LEED certification system is the most popular system in Turkey that has attended and certificated. From the LEED official data, it’s understood that 308 project registered in Turkey. Therefore, LEED sustainability criteria are used in the survey. Head lines of LEED certification criteria; sustainable sites, water efficiency, energy and atmosphere, material and resources, indoor environmental quality, innovation and regional priority are indicated to assess the perceptions of survey participants. Moreover, only surveying of criteria are not enough; so the equipment, methods, risks and benefits also considered.

Keywords: LEED, sustainability, perceptions, stakeholders, construction, Turkey, risk, benefit

Procedia PDF Downloads 287
10732 Performance Evaluation of Sand Casting Manufacturing Plant with WITNESS

Authors: Aniruddha Joshi

Abstract:

This paper discusses a simulation study of automated sand casting production system. Therefore, the first aims of this study is development of automated sand casting process model and analyze this model with a simulation software Witness. Production methodology aims to improve overall productivity through elimination of wastes and that leads to improve quality. Integration of automation with Simulation is beneficial to identify the obstacles in implementation and to take appropriate options to implement successfully. For this integration, there are different Simulation Software’s. To study this integration, with the help of “WITNESS” Simulation Software the model is created. This model is based on literature review. The input parameters are Setup Time, Number of machines, cycle time and output parameter is number of castings, avg, and time and percentage usage of machines. Obtained results are used for Statistical Analysis. This analysis concludes the optimal solution to get maximum output.

Keywords: automated sand casting production system, simulation, WITNESS software, performance evaluation

Procedia PDF Downloads 776
10731 An Investigation on Interface Shear Resistance of Twinwall Units for Tank Structures

Authors: Jaylina Rana, Chanakya Arya, John Stehle

Abstract:

Hybrid precast twinwall concrete units, mainly used in basement, core and crosswall construction, are now being adopted in water retaining tank structures. Their use offers many advantages compared with conventional in-situ concrete alternatives, however, the design could be optimised further via a deeper understanding of the unique load transfer mechanisms in the system. In the tank application, twinwall units, which consist of two precast concrete biscuits connected by steel lattices and in-situ concrete core, are subject to bending. Uncertainties about the degree of composite action between the precast biscuits and hence flexural performance of the units necessitated laboratory tests to investigate the interface shear resistance. Testing was also required to assess both the leakage performance and buildability of a variety of joint details. This paper describes some aspects of this novel approach to the design/construction of tank structures as well as selected results from some of the tests that were carried out.

Keywords: hybrid construction, twinwall, precast construction, composite action

Procedia PDF Downloads 461
10730 Structural Performances of Rubberized Concrete Wall Panel Utilizing Fiber Cement Board as Skin Layer

Authors: Jason Ting Jing Cheng, Lee Foo Wei, Yew Ming Kun, Mo Kim Hung, Yip Chun Chieh

Abstract:

This research delves into the structural characteristics of distinct construction material, rubberized lightweight foam concrete (RLFC) wall panels, which have been developed as a sustainable alternative for the construction industry. These panels are engineered with a RLFC core, possessing a density of 1150 kg/m3, which is specifically formulated to bear structural loads. The core is enveloped with high-strength fiber cement boards, selected for their superior load-bearing capabilities, and enhanced flexural strength when compared to conventional concrete. A thin bed adhesive, known as TPS, is employed to create a robust bond between the RLFC core and the fiber cement cladding. This study underscores the potential of RLFC wall panels as a viable and eco-friendly option for modern building construction, offering a combination of structural efficiency and environmental benefits.

Keywords: structural performance, rubberized concrete wall panel, fiber cement board, insulation performance

Procedia PDF Downloads 46
10729 Concrete Performance Evaluation of Coarse Aggregate Replacement by Civil Construction Waste

Authors: Juliane P. De Oliveira, Carlos H. Dos Santos, Marcia Shoji, Maria E. C. Ferreira, Natalia U. Yamaguchi

Abstract:

The construction sector is considered a major generator of environmental impacts due to the high consumption of natural resources and waste generation. Thus, this article aims to evaluate the performance of a concrete produced by the partial and total replacement of natural coarse aggregate by recycled coarse aggregate, derived from the concrete residue of buildings and demolitions. The study was made by comparing the compressive strength and absorption of three different concrete traces, keeping the water/cement factor of 0.60 and changing only the proportions of recycled coarse aggregate between 0%, 50% and 100%. Traces 50% and 100% obtained good results by comparing the actual specific mass, because the material used is lighter to the natural coarse aggregate. It was concluded that the concrete produced with recycled aggregates, even with inferior results, can be used where it is not needed a structural function, giving an adequate destination to the construction and demolition waste and consequently reducing the extraction and consumption of natural resources.

Keywords: green concrete, recycled aggregate, recycling, sustainable development

Procedia PDF Downloads 134
10728 A Study to Understand the Factors Influencing the Behavioral Intentions of Individuals Towards Using Metaverse

Authors: Suktisuddha Goswami, Surekha Chukkali

Abstract:

Metaverse is a real time rendered 3D world which is an extension of the virtual reality, augmented reality, mixed reality, and holographic reality. While using the metaverse can enhance various aspects of our lives, it might also create certain challenges. However, since the concept of the metaverse is very new, there is a lack of research on factors influencing the individual’s behavioural intentions to use it. To address this gap, this quantitative research study was conducted to understand the factors influencing the behavioural intention of individuals towards metaverse usage. This research was conducted through a large-scale questionnaire survey of 325 Indian students at three major engineering colleges. The questionnaire was adequately customized for the present study. It was found that behavioral intention towards metaverse usage differs among individuals. There were few individuals who had no intention of using metaverse in near future, while some of them were already using it and a few were significantly inclined towards using it. The findings of this study have suggested that behavioural intention was significantly and positively related to performance expectancy and effort expectancy of individuals.

Keywords: behavioral intention, effort expectancy, performance expectancy, technology, metaverse

Procedia PDF Downloads 89
10727 Regional Flood Frequency Analysis in Narmada Basin: A Case Study

Authors: Ankit Shah, R. K. Shrivastava

Abstract:

Flood and drought are two main features of hydrology which affect the human life. Floods are natural disasters which cause millions of rupees’ worth of damage each year in India and the whole world. Flood causes destruction in form of life and property. An accurate estimate of the flood damage potential is a key element to an effective, nationwide flood damage abatement program. Also, the increase in demand of water due to increase in population, industrial and agricultural growth, has let us know that though being a renewable resource it cannot be taken for granted. We have to optimize the use of water according to circumstances and conditions and need to harness it which can be done by construction of hydraulic structures. For their safe and proper functioning of hydraulic structures, we need to predict the flood magnitude and its impact. Hydraulic structures play a key role in harnessing and optimization of flood water which in turn results in safe and maximum use of water available. Mainly hydraulic structures are constructed on ungauged sites. There are two methods by which we can estimate flood viz. generation of Unit Hydrographs and Flood Frequency Analysis. In this study, Regional Flood Frequency Analysis has been employed. There are many methods for estimating the ‘Regional Flood Frequency Analysis’ viz. Index Flood Method. National Environmental and Research Council (NERC Methods), Multiple Regression Method, etc. However, none of the methods can be considered universal for every situation and location. The Narmada basin is located in Central India. It is drained by most of the tributaries, most of which are ungauged. Therefore it is very difficult to estimate flood on these tributaries and in the main river. As mentioned above Artificial Neural Network (ANN)s and Multiple Regression Method is used for determination of Regional flood Frequency. The annual peak flood data of 20 sites gauging sites of Narmada Basin is used in the present study to determine the Regional Flood relationships. Homogeneity of the considered sites is determined by using the Index Flood Method. Flood relationships obtained by both the methods are compared with each other, and it is found that ANN is more reliable than Multiple Regression Method for the present study area.

Keywords: artificial neural network, index flood method, multi layer perceptrons, multiple regression, Narmada basin, regional flood frequency

Procedia PDF Downloads 401
10726 A Hybrid Pareto-Based Swarm Optimization Algorithm for the Multi-Objective Flexible Job Shop Scheduling Problems

Authors: Aydin Teymourifar, Gurkan Ozturk

Abstract:

In this paper, a new hybrid particle swarm optimization algorithm is proposed for the multi-objective flexible job shop scheduling problem that is very important and hard combinatorial problem. The Pareto approach is used for solving the multi-objective problem. Several new local search heuristics are integrated into an algorithm based on the critical block concept to enhance the performance of the algorithm. The algorithm is compared with the recently published multi-objective algorithms based on benchmarks selected from the literature. Several metrics are used for quantifying performance and comparison of the achieved solutions. The algorithms are also compared based on the Weighting summation of objectives approach. The proposed algorithm can find the Pareto solutions more efficiently than the compared algorithms in less computational time.

Keywords: swarm-based optimization, local search, Pareto optimality, flexible job shop scheduling, multi-objective optimization

Procedia PDF Downloads 360