Search results for: lifetime estimation

Authors: Sara ElElimy, Samir Moustafa

Abstract:

Mobile network operators start to face many challenges in the digital era, especially with high demands from customers. Since mobile network operators are considered a source of big data, traditional techniques are not effective with new era of big data, Internet of things (IoT) and 5G; as a result, handling effectively different big datasets becomes a vital task for operators with the continuous growth of data and moving from long term evolution (LTE) to 5G. So, there is an urgent need for effective Big data analytics to predict future demands, traffic, and network performance to full fill the requirements of the fifth generation of mobile network technology. In this paper, we introduce data science techniques using machine learning and deep learning algorithms: the autoregressive integrated moving average (ARIMA), Bayesian-based curve fitting, and recurrent neural network (RNN) are employed for a data-driven application to mobile network operators. The main framework included in models are identification parameters of each model, estimation, prediction, and final data-driven application of this prediction from business and network performance applications. These models are applied to Telecom Italia Big Data challenge call detail records (CDRs) datasets. The performance of these models is found out using a specific well-known evaluation criteria shows that ARIMA (machine learning-based model) is more accurate as a predictive model in such a dataset than the RNN (deep learning model).

Keywords: big data analytics, machine learning, CDRs, 5G

Procedia PDF Downloads 126

Authors: Catalina Sau Man Ng

Abstract:

Workplace bullying is generally defined as a form of direct and indirect maltreatment at work including harassing, offending, socially isolating someone or negatively affecting someone’s work tasks. Workplace bullying is unfortunately commonplace around the world, which makes it a social phenomenon worth researching. However, the measurements and estimation methods of workplace bullying seem to be diverse in different studies, leading to dubious results. Hence, this paper attempts to examine the prevalence of workplace bullying in Hong Kong using the latent class analysis approach. It is often argued that the traditional classification of workplace bullying into the dichotomous 'victims' and 'non-victims' may not be able to fully represent the complex phenomenon of bullying. By treating workplace bullying as one latent variable and examining the potential categorical distribution within the latent variable, a more thorough understanding of workplace bullying in real-life situations may hence be provided. As a result, this study adopts a latent class analysis method, which was tested to demonstrate higher construct and higher predictive validity previously. In the present study, a representative sample of 2814 employees (Male: 54.7%, Female: 45.3%) in Hong Kong was recruited. The participants were asked to fill in a self-reported questionnaire which included measurements such as Chinese Workplace Bullying Scale (CWBS) and Chinese Version of Depression Anxiety Stress Scale (DASS). It is estimated that four latent classes will emerge: 'non-victims', 'seldom bullied', 'sometimes bullied', and 'victims'. The results of each latent class and implications of the study will also be discussed in this working paper.

Keywords: latent class analysis, prevalence, survey, workplace bullying

Procedia PDF Downloads 313

Authors: Sara Bahariderakhshan, Morteza Ahmadifar

Abstract:

Leakage is one of the most important problems that water distribution networks face which first reason is high-pressure existence. There are many approaches to control this excess pressure, which using pressure reducing valves (PRVs) or reducing pipe diameter are ones. In the other hand, Pumps are using electricity or fossil fuels to supply needed pressure in distribution networks but excess pressure are made in some branches due to topology problems and water networks’ variables therefore using pressure valves will be inevitable. Although using PRVs is inevitable but it leads to waste electricity or fuels used by pumps because PRVs just waste excess hydraulic pressure to lower it. Pumps working in reverse or Pumps as Turbine (called PaT in this article) are easily available and also effective sources of reducing the equipment cost in small hydropower plants. Urban areas of developing countries are facing increasing in area and maybe water scarcity in near future. These cities need wider water networks which make it hard to predict, control and have a better operation in the urban water cycle. Using more energy and, therefore, more pollution, slower repairing services, more user dissatisfaction and more leakage are these networks’ serious problems. Therefore, more effective systems are needed to monitor and act in these complicated networks than what is used now. In this article a new approach is proposed and evaluated: Using PAT to produce enough energy for remote valves and sensors in the water network. These sensors can be used to determine the discharge, pressure, water quality and other important network characteristics. With the help of remote valves pipeline discharge can be controlled so Instead of wasting excess hydraulic pressure which may be destructive in some cases, obtaining extra pressure from pipeline and producing clean electricity used by remote instruments is this articles’ goal. Furthermore due to increasing the area of the network there is unwanted high pressure in some critical points which is not destructive but lowering the pressure results to longer lifetime for pipeline networks without users’ dissatisfaction. This strategy proposed in this article, leads to use PaT widely for pressure containment and producing energy needed for remote valves and sensors like what happens in supervisory control and data acquisition (SCADA) systems which make it easy for us to monitor, receive data from urban water cycle and make any needed changes in discharge and pressure of pipelines easily and remotely. This is a clean project of energy production without significant environmental impacts and can be used in urban drinking water networks, without any problem for consumers which leads to a stable and dynamic network which lowers leakage and pollution.

Keywords: new energies, pump as turbine, drinking water, distribution network, remote control equipments

Procedia PDF Downloads 446

Authors: Rajesh Kumar G

Abstract:

A challenging aspect of any clinical trial is to carefully plan the study design to meet the study objective in optimum way and to validate the assumptions made during protocol designing. And when it is a pediatric study, there is the added challenge of stringent guidelines and difficulty in recruiting the necessary subjects. Unlike adult trials, there is not much historical data available for pediatrics, which is required to validate assumptions for planning pediatric trials. Typically, pediatric studies are initiated as soon as approval is obtained for a drug to be marketed for adults, so with the adult study historical information and with the available pediatric pilot study data or simulated pediatric data, the pediatric study can be well planned. Generalizing the historical adult study for new pediatric study is a tedious task; however, it is possible by integrating various statistical techniques and utilizing the advantage of hybrid study design, which will help to achieve the study objective in a smoother way even with the presence of many constraints. This research paper will explain how well the hybrid study design can be planned along with integrated technique (SEV) to plan the pediatric study; In brief the SEV technique (Simulation, Estimation (using borrowed adult data and applying Bayesian methods)) incorporates the use of simulating the planned study data and getting the desired estimates to Validate the assumptions.This method of validation can be used to improve the accuracy of data analysis, ensuring that results are as valid and reliable as possible, which allow us to make informed decisions well ahead of study initiation. With professional precision, this technique based on the collected data allows to gain insight into best practices when using data from historical study and simulated data alike.

Keywords: adaptive design, simulation, borrowing data, bayesian model

Procedia PDF Downloads 64

Authors: Sifriyani Sifriyani, I Nyoman Budiantara, Sri Haryatmi, Gunardi Gunardi

Abstract:

East Java Province has a first rank as a province that has the most counties and cities in Indonesia and has the largest population. In 2015, the population reached 38.847.561 million, this figure showed a very high population growth. High population growth is feared to lead to increase the levels of unemployment. In this study, the researchers mapped and modeled the unemployment rate with 6 variables that were supposed to influence. Modeling was done by nonparametric geographically weighted regression methods with truncated spline approach. This method was chosen because spline method is a flexible method, these models tend to look for its own estimation. In this modeling, there were point knots, the point that showed the changes of data. The selection of the optimum point knots was done by selecting the most minimun value of Generalized Cross Validation (GCV). Based on the research, 6 variables were declared to affect the level of unemployment in eastern Java. They were the percentage of population that is educated above high school, the rate of economic growth, the population density, the investment ratio of total labor force, the regional minimum wage and the ratio of the number of big industry and medium scale industry from the work force. The nonparametric geographically weighted regression models with truncated spline approach had a coefficient of determination 98.95% and the value of MSE equal to 0.0047.

Keywords: East Java, nonparametric geographically weighted regression, spatial, spline approach, unemployed rate

Procedia PDF Downloads 307

Authors: Haruna Maama

Abstract:

Environmental, social and governance (ESG) reporting is gaining considerable attention despite being voluntary. Meanwhile, it consumes resources to provide ESG reporting, raising a question of its value relevance. The study examined the impact of ESG reporting on the market value of listed firms in SSA. The annual and integrated reports of 276 listed sub-Sahara Africa (SSA) firms. The integrated reporting scores of the firm were analysed using a content analysis method. A multiple regression estimation technique using a GMM approach was employed for the analysis. The results revealed that ESG has a positive relationship with firms’ market value, suggesting that investors are interested in the ESG information disclosure of firms in SSA. This suggests that extensive ESG disclosures are attempts by firms to obtain the approval of powerful social, political and environmental stakeholders, especially institutional investors. Furthermore, the market value analysis evidence is consistent with signalling theory, which postulates that firms provide integrated reports as a signal to influence the behaviour of stakeholders. This finding reflects the value placed on investors' social, environmental and governance disclosures, which affirms the views that conventional investors would care about the social, environmental and governance issues of their potential or existing investee firms. Overall, the evidence is consistent with the prediction of signalling theory. In the context of this theory, integrated reporting is seen as part of firms' overall competitive strategy to influence investors' behaviour. The findings of this study make unique contributions to knowledge and practice in corporate reporting.

Keywords: environmental accounting, ESG accounting, signalling theory, sustainability reporting, sub-saharan Africa

Procedia PDF Downloads 60

Authors: Fally Titikpina, Abderafi Charki, Antoine Caucheteux, David Bigaud

Abstract:

The building sector is one of the largest energy consumer with about 40% of the final energy consumption in the European Union. Ensuring building energy performance is of scientific, technological and sociological matter. To assess a building energy performance, the consumption being predicted or estimated during the design stage is compared with the measured consumption when the building is operational. When valuing this performance, many buildings show significant differences between the calculated and measured consumption. In order to assess the performance accurately and ensure the thermal efficiency of the building, it is necessary to evaluate the uncertainties involved not only in measurement but also those induced by the propagation of dynamic and static input data in the model being used. The evaluation of measurement uncertainty is based on both the knowledge about the measurement process and the input quantities which influence the result of measurement. Measurement uncertainty can be evaluated within the framework of conventional statistics presented in the \textit{Guide to the Expression of Measurement Uncertainty (GUM)} as well as by Bayesian Statistical Theory (BST). Another choice is the use of numerical methods like Monte Carlo Simulation (MCS). In this paper, we proposed to evaluate the uncertainty associated to the use of a simplified model for the estimation of the energy consumption of a given building. A detailed review and discussion of these three approaches (GUM, MCS and BST) is given. Therefore, an office building has been monitored and multiple sensors have been mounted on candidate locations to get required data. The monitored zone is composed of six offices and has an overall surface of 102 $m^2$. Temperature data, electrical and heating consumption, windows opening and occupancy rate are the features for our research work.

Keywords: building energy performance, uncertainty evaluation, GUM, bayesian approach, monte carlo method

Procedia PDF Downloads 444

Authors: Morteza Ahmadifar, Sarah Bahari Derakhshan

Abstract:

Leakage is one of the most important problems that water distribution networks face which first reason is high-pressure existence. There are many approaches to control this excess pressure, which using pressure reducing valves (PRVs) or reducing pipe diameter are ones. On the other hand, Pumps are using electricity or fossil fuels to supply needed pressure in distribution networks but excess pressure are made in some branches due to topology problems and water networks’ variables, therefore using pressure valves will be inevitable. Although using PRVs is inevitable but it leads to waste electricity or fuels used by pumps because PRVs just waste excess hydraulic pressure to lower it. Pumps working in reverse or Pumps as Turbine (called PAT in this article) are easily available and also effective sources of reducing the equipment cost in small hydropower plants. Urban areas of developing countries are facing increasing in area and maybe water scarcity in near future. These cities need wider water networks which make it hard to predict, control and have a better operation in the urban water cycle. Using more energy and therefore more pollution, slower repairing services, more user dissatisfaction and more leakage are these networks’ serious problems. Therefore, more effective systems are needed to monitor and act in these complicated networks than what is used now. In this article a new approach is proposed and evaluated: Using PAT to produce enough energy for remote valves and sensors in the water network. These sensors can be used to determine the discharge, pressure, water quality and other important network characteristics. With the help of remote valves pipeline discharge can be controlled so Instead of wasting excess hydraulic pressure which may be destructive in some cases, obtaining extra pressure from pipeline and producing clean electricity used by remote instruments is this articles’ goal. Furthermore, due to increasing the area of network there is unwanted high pressure in some critical points which is not destructive but lowering the pressure results to longer lifetime for pipeline networks without users’ dissatisfaction. This strategy proposed in this article, leads to use PAT widely for pressure containment and producing energy needed for remote valves and sensors like what happens in supervisory control and data acquisition (SCADA) systems which make it easy for us to monitor, receive data from urban water cycle and make any needed changes in discharge and pressure of pipelines easily and remotely. This is a clean project of energy production without significant environmental impacts and can be used in urban drinking water networks, without any problem for consumers which leads to a stable and dynamic network which lowers leakage and pollution.

Keywords: clean energies, pump as turbine, remote control, urban water distribution network

Procedia PDF Downloads 376

Authors: Ayesha S. Rahman, Khaled Haddad, Ataur Rahman

Abstract:

At-site flood frequency analysis is used to estimate flood quantiles when at-site record length is reasonably long. In Australia, FLIKE software has been introduced for at-site flood frequency analysis. The advantage of FLIKE is that, for a given application, the user can compare a number of most commonly adopted probability distributions and parameter estimation methods relatively quickly using a windows interface. The new version of FLIKE has been incorporated with the multiple Grubbs and Beck test which can identify multiple numbers of potentially influential low flows. This paper presents a case study considering six catchments in eastern Australia which compares two outlier identification tests (original Grubbs and Beck test and multiple Grubbs and Beck test) and two commonly applied probability distributions (Generalized Extreme Value (GEV) and Log Pearson type 3 (LP3)) using FLIKE software. It has been found that the multiple Grubbs and Beck test when used with LP3 distribution provides more accurate flood quantile estimates than when LP3 distribution is used with the original Grubbs and Beck test. Between these two methods, the differences in flood quantile estimates have been found to be up to 61% for the six study catchments. It has also been found that GEV distribution (with L moments) and LP3 distribution with the multiple Grubbs and Beck test provide quite similar results in most of the cases; however, a difference up to 38% has been noted for flood quantiles for annual exceedance probability (AEP) of 1 in 100 for one catchment. These findings need to be confirmed with a greater number of stations across other Australian states.

Keywords: floods, FLIKE, probability distributions, flood frequency, outlier

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Authors: Christian H. Girsang, M. Razi B. Mansoor, Noorizal N. Huang

Abstract:

An offshore platform was installed in 1977 at about 260km offshore West Malaysia at the water depth of 73.6m. Twelve (12) piles were installed with four (4) are skirt piles. The piles have 1.219m outside diameter and wall thickness of 31mm and were driven to 109m below seabed. Deterministic analyses of the pile capacity under axial loading were conducted using the current API (American Petroleum Institute) method and the four (4) CPT-based methods: the ICP (Imperial College Pile)-method, the NGI (Norwegian Geotechnical Institute)-Method, the UWA (University of Western Australia)-method and the Fugro-method. A statistical analysis of the model uncertainty associated with each pile capacity method was performed. There were two (2) piles analysed: Pile 1 and piles other than Pile 1, where Pile 1 is the pile that was most affected by shallow gas problems. Using the mean estimate of soil properties, the five (5) methods used for deterministic estimation of axial pile capacity in compression predict an axial capacity from 28 to 42MN for Pile 1 and 32 to 49MN for piles other than Pile 1. These values refer to the static capacity shortly after pile installation. They do not include the effects of cyclic loading during the design storm or time after installation on the axial pile capacity. On average, the axial pile capacity is expected to have increased by about 40% because of ageing since the installation of the platform in 1977. On the other hand, the cyclic loading effects during the design storm may reduce the axial capacity of the piles by around 25%. The study concluded that all piles have sufficient safety factor when the pile aging and cyclic loading effect are considered, as all safety factors are above 2.0 for maximum operating and storm loads.

Keywords: axial capacity, cyclic loading, pile ageing, shallow gas

Procedia PDF Downloads 327

Authors: Sankha Chakrabortty, Biswajit Ruj, Parimal Pal

Abstract:

Methanol is one of the most important chemical products and intermediates. It can be used as a solvent, intermediate or raw material for a number of higher valued products, fuels or additives. From the last one decay, the total global demand of methanol has increased drastically which forces the scientists to produce a large amount of methanol from a renewable source to meet the global demand with a sustainable way. Different types of non-renewable based raw materials have been used for the synthesis of methanol on a large scale which makes the process unsustainable. In this circumstances, photocatalytic conversion of CO₂ into methanol under solar/UV excitation becomes a viable approach to give a sustainable production approach which not only meets the environmental crisis by recycling CO₂ to fuels but also reduces CO₂ amount from the atmosphere. Development of such sustainable production approach for CO₂ conversion into methanol still remains a major challenge in the current research comparing with conventional energy expensive processes. In this backdrop, the development of environmentally friendly materials, like photocatalyst has taken a great perspective for methanol synthesis. Scientists in this field are always concerned about finding an improved photocatalyst to enhance the photocatalytic performance. Graphene-based hybrid and composite materials with improved properties could be a better nanomaterial for the selective conversion of CO₂ to methanol under visible light (solar energy) or UV light. The present invention relates to synthesis an improved heterogeneous graphene-based photocatalyst with improved catalytic activity and surface area. Graphene with enhanced surface area is used as coupled material of copper-loaded titanium oxide to improve the electron capture and transport properties which substantially increase the photoinduced charge transfer and extend the lifetime of photogenerated charge carriers. A fast reduction method through H₂ purging has been adopted to synthesis improved graphene whereas ultrasonication based sol-gel method has been applied for the preparation of graphene coupled copper loaded titanium oxide with some enhanced properties. Prepared photocatalysts were exhaustively characterized using different characterization techniques. Effects of catalyst dose, CO₂ flow rate, reaction temperature and stirring time on the efficacy of the system in terms of methanol yield and productivity have been studied in the present study. The study shown that the newly synthesized photocatalyst with an enhanced surface resulting in a sustained productivity and yield of methanol 0.14 g/Lh, and 0.04 g/gcat respectively, after 3 h of illumination under UV (250W) at an optimum catalyst dosage of 10 g/L having 1:2:3 (Graphene: TiO₂: Cu) weight ratio.

Keywords: renewable energy, CO₂ capture, photocatalytic conversion, methanol

Procedia PDF Downloads 98

Authors: Azita Ramezani, Ghazal Mashhadiagha, Bahareh Sanabakhsh

Abstract:

This study researches the combination of Random. Forest classifiers with large language models (LLMs) and natural language processing (NLP) to improve diagnostic accuracy in chest X-ray analysis using the Indiana University dataset. Utilizing advanced NLP techniques, the research preprocesses textual data from radiological reports to extract key features, which are then merged with image-derived data. This improved dataset is analyzed with Random Forest classifiers to predict specific clinical results, focusing on the identification of health issues and the estimation of case urgency. The findings reveal that the combination of NLP, LLMs, and machine learning not only increases diagnostic precision but also reliability, especially in quickly identifying critical conditions. Achieving an accuracy of 99.35%, the model shows significant advancements over conventional diagnostic techniques. The results emphasize the large potential of machine learning in medical imaging, suggesting that these technologies could greatly enhance clinician judgment and patient outcomes by offering quicker and more precise diagnostic approximations.

Keywords: natural language processing (NLP), large language models (LLMs), random forest classifier, chest x-ray analysis, medical imaging, diagnostic accuracy, indiana university dataset, machine learning in healthcare, predictive modeling, clinical decision support systems

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Authors: Muhammad Umair, Yasir Nawab, Khubab Shaker, Muhammad Maqsood, Adeel Zulfiqar, Danish Mahmood Baitab

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Fabric is a flexible woven material consisting of a network of natural or artificial fibers often referred to as thread or yarn. Today fabrics are produced by weaving, braiding, knitting, tufting and non-woven. Weaving is a method of fabric production in which warp and weft yarns are interlaced perpendicular to each other. There is infinite number of ways for the interlacing of warp and weft yarn. Each way produces a different fabric structure. The yarns parallel to the machine direction are called warp yarns and the yarns perpendicular to the machine direction are called weft or filling yarns. Air jet weaving is the modern method of weft insertion and considered as high speed loom. The twist loss in air jet during weft insertion affects the strength. The aim of this study was to investigate the effect of twist change in weft yarn during air-jet weft insertion. A total number of 8 samples were produced using 1/1 plain and 3/1 twill weave design with two fabric widths having same loom settings. Two different types of yarns like cotton and PC blend were used. The effect of material type, weave design and fabric width on twist change of weft yarn was measured and discussed. Twist change in the different types of weft yarn and weave design was measured and compared the twist change in the weft yarn with the yarn before weft yarn insertion and twist loss is measured. Wider fabric leads to higher twist loss in the yarn.

Keywords: air jet loom, twist per inch, twist loss, weft yarn

Procedia PDF Downloads 385

Authors: Jane E. Hill

Abstract:

Quality of life is an important component for many. With that in mind, everyone will experience some type of loss within his or her lifetime. A person can experience loss due to break up, separation, divorce, estrangement, or death. An individual may experience loss of a job, loss of capacity, or loss caused by human or natural-caused disasters. An individual’s response to such a loss is unique to them, and not everyone will seek services to assist them with their grief due to loss. Counseling can promote positive outcomes for clients that are grieving by addressing the client’s personal loss and helping the client process their grief. However, a lack of understanding on the part of counselors of how people grieve may result in negative client outcomes such as poor health, psychological distress, or an increased risk of depression. Education and training in grief counseling can improve counselors’ problem recognition and skills in treatment planning. The purpose of this study was to examine whether the Council for Accreditation of Counseling and Related Educational Programs (CACREP) master’s degree counseling students view themselves as having been adequately trained in grief theories and skills. Many people deal with grief issues that prevent them from having joy or purpose in their lives and that leaves them unable to engage in positive opportunities or relationships. This study examined CACREP-accredited master’s counseling students’ self-reported competency, training, and education in providing grief counseling. The implications for positive social change arising from the research may be to incorporate and promote education and training in grief theories and skills in a majority of counseling programs and to provide motivation to incorporate professional standards for grief training and practice in the mental health counseling field. The theoretical foundation used was modern grief theory based on John Bowlby’s work on Attachment Theory. The overall research question was how competent do master’s-level counselors view themselves regarding the education or training they received in grief theories or counseling skills in their CACREP-accredited studies. The author used a non-experimental, one shot survey comparative quantitative research design. Cicchetti’s Grief Counseling Competency Scale (GCCS) was administered to CACREP master’s-level counseling students enrolled in their practicum or internship experience, which resulted in 153 participants. Using a MANCOVA, there was significance found for relationships between coursework taken and (a) perceived assessment skills (p = .029), (b) perceived treatment skills (p = .025), and (c) perceived conceptual skills and knowledge (p = .003). Results of this study provided insight for CACREP master’s-level counseling programs to explore and discuss curriculum coursework inclusion of education and training in grief theories and skills.

Keywords: counselor education and training, grief education and training, grief and loss, quality of life

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Authors: Elsher Lawson-Boyd

Abstract:

In the wake of the Human Genome Project, the life sciences have undergone some fascinating changes. In particular, conventional beliefs relating to gene expression are being challenged by advances in postgenomic sciences, especially by the field of epigenetics. Epigenetics is the modification of gene expression without changes in the DNA sequence. In other words, epigenetics dictates that gene expression, the process by which the instructions in DNA are converted into products like proteins, is not solely controlled by DNA itself. Unlike gene-centric theories of heredity that characterized much of the 20th Century (where the genes were considered as having almost god-like power to create life), gene expression in epigenetics insists on environmental ‘signals’ or ‘exposures’, a point that radically deviates from gene-centric thinking. Science and Technology Studies (STS) scholars have shown that epigenetic research is having vast implications for the ways in which chronic, non-communicable diseases are conceptualized, treated, and governed. However, to the author’s knowledge, there have not yet been any in-depth sociological engagements with neuroepigenetics that examine how the field is affecting mental health and trauma discourse. In this paper, the author discusses preliminary findings from a doctoral ethnographic study on neuroepigenetics, trauma, and embodiment. Specifically, this study investigates the kinds of causal relations neuroepigenetic researchers are making between experiences of trauma and the development of mental illnesses like complex post-traumatic stress disorder (PTSD), both throughout a human’s lifetime and across generations. Using qualitative interviews and nonparticipant observation, the author focuses on two public-facing research centers based in Melbourne: Florey Institute of Neuroscience and Mental Health (FNMH), and Murdoch Children’s Research Institute (MCRI). Preliminary findings indicate that a great deal of ambiguity characterizes this infant field, particularly when animal-model experiments are employed and the results are translated into human frameworks. Nevertheless, researchers at the FNMH and MCRI strongly suggest that adverse and traumatic life events have a significant effect on gene expression, especially when experienced during early development. Furthermore, they predict that neuroepigenetic research will have substantial implications for the ways in which mental illnesses like complex PTSD are diagnosed and treated. These preliminary findings shed light on why medical and health sociologists have good reason to be chiming in, engaging with and de-black-boxing ideations emerging from postgenomic sciences, as they may indeed have significant effects for vulnerable populations not only in Australia but other developing countries in the Global South.

Keywords: genetics, mental illness, neuroepigenetics, trauma

Procedia PDF Downloads 115

Authors: Reza Talebi

Abstract:

Wheat (Triticum aestivum) is one of the most important food staples in Iran. Understanding genetic variability among the landrace wheat germplasm is important for breeding. Landraces endemic to Iran are a genetic resource that is distinct from other wheat germplasm. In this study, 60 Iranian landrace wheat accessions were characterized AFLP and ISSR markers. Twelve AFLP primer pairs detected 128 polymorphic bands among the sixty genotypes. The mean polymorphism rate based on AFLP data was 31%; however, a wide polymorphism range among primer pairs was observed (22–40%). Polymorphic information content (PIC value) calculated to assess the informativeness of each marker ranged from 0.28 to 0.4, with a mean of 0.37. According to AFLP molecular data, cluster analysis grouped the genotypes in five distinct clusters. .ISSR markers generated 68 bands (average of 6 bands per primer), which 31 were polymorphic (45%) across the 60 wheat genotypes. Polymorphism information content (PIC) value for ISSR markers was calculated in the range of 0.14 to 0.48 with an average of 0.33. Based on data achieved by ISSR-PCR, cluster analysis grouped the genotypes in three distinct clusters. Both AFLP and ISSR markers able to showed that high level of genetic diversity in Iranian landrace wheat accessions has maintained a relatively constant level of genetic diversity during last years.

Keywords: wheat, genetic diversity, AFLP, ISSR

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Authors: Mohamed Mohamed, Philip Bonello, Peter Russhard

Abstract:

Blade Tip Timing (BTT) is a technology concerned with the estimation of both frequency and amplitude of rotating blades. A BTT system comprises two main parts: (a) the arrival time measurement system, and (b) the analysis algorithms. Simulators play an important role in the development of the analysis algorithms since they generate blade tip displacement data from the simulated blade vibration under controlled conditions. This enables an assessment of the performance of the different algorithms with respect to their ability to accurately reproduce the original simulated vibration. Such an assessment is usually not possible with real engine data since there is no practical alternative to BTT for blade vibration measurement. Most simulators used in the literature are based on a simple spring-mass-damper model to determine the vibration. In this work, a more realistic experimentally validated simulator based on the Finite Element (FE) model of a bladed disc (blisk) is first presented. It is then used to generate the necessary data for the assessment of different BTT algorithms. The FE modelling is validated using both a hammer test and two firewire cameras for the mode shapes. A number of autoregressive methods, fitting methods and state-of-the-art inverse methods (i.e. Russhard) are compared. All methods are compared with respect to both synchronous and asynchronous excitations with both single and simultaneous frequencies. The study assesses the applicability of each method for different conditions of vibration, amount of sampling data, and testing facilities, according to its performance and efficiency under these conditions.

Keywords: blade tip timing, blisk, finite element, vibration measurement

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Authors: Cristina Diaz, Lucia Perez-Gandarillas, Gonzalo Garcia-Fuentes, Simone Visigalli, Roberto Canziani, Giuseppe Di Florio, Paolo Gronchi

Abstract:

During their lifetime, industrial machines are often subjected to chemical, mechanical and thermal extreme conditions. In some cases, the loss of efficiency comes from the degradation of the surface as a result of its exposition to abrasive environments that can cause wear. This is a common problem to be solved in industries of diverse nature such as food, paper or concrete industries, among others. For this reason, a good selection of the material is of high importance. In the machine design context, stainless steels such as AISI 304 and 316 are widely used. However, the severity of the external conditions can require additional protection for the steel and sometimes coating solutions are demanded in order to extend the lifespan of these materials. Therefore, the development of effective coatings with high wear resistance is of utmost technological relevance. In this research, bilayer coatings made of Titanium-Tantalum, Titanium-Niobium, Titanium-Hafnium, and Titanium-Zirconium have been developed using magnetron sputtering configuration by PVD (Physical Vapor Deposition) technology. Their tribological behavior has been measured and evaluated under different environmental conditions. Two kinds of steels were used as substrates: AISI 304, AISI 316. For the comparison with these materials, titanium alloy substrate was also employed. Regarding the characterization, wear rate and friction coefficient were evaluated by a tribo-tester, using a pin-on-ball configuration with different lubricants such as tomato sauce, wine, olive oil, wet compost, a mix of sand and concrete with water and NaCl to approximate the results to real extreme conditions. In addition, topographical images of the wear tracks were obtained in order to get more insight of the wear behavior and scanning electron microscope (SEM) images were taken to evaluate the adhesion and quality of the coating. The characterization was completed with the measurement of nanoindentation hardness and elastic modulus. Concerning the results, thicknesses of the samples varied from 100 nm (Ti-Zr layer) to 1.4 µm (Ti-Hf layer) and SEM images confirmed that the addition of the Ti layer improved the adhesion of the coatings. Moreover, results have pointed out that these coatings have increased the wear resistance in comparison with the original substrates under environments of different severity. Furthermore, nanoindentation hardness results showed an improvement of the elastic strain to failure and a high modulus of elasticity (approximately 200 GPa). As a conclusion, Ti-Ta, Ti-Zr, Ti-Nb, and Ti-Hf are very promising and effective coatings in terms of tribological behavior, improving considerably the wear resistance and friction coefficient of typically used machine materials.

Keywords: coating, stainless steel, tribology, wear

Procedia PDF Downloads 141

Authors: Ali Reza Ghanbarnezhad Ghazvini, Seyyed Hamid Reza Mosayyebi

Abstract:

In recent years, an earthquake has occurred approximately every five years in certain regions of Iran. To mitigate the impact of these seismic events, it is crucial to identify and thoroughly assess the vulnerability of buildings and infrastructure, ensuring their safety through principled reinforcement. By adopting new methods of risk assessment, we can effectively reduce the potential risks associated with future earthquakes. In our research, we have observed that the coefficient of behavior in the fourth chapter is 1.65 for the initial structure and 1.72 for the Superframe structure. This indicates that the Superframe structure can enhance the strength of the main structural members by approximately 10% through the utilization of super beams. Furthermore, based on the comparative analysis between the two structures conducted in this study, we have successfully designed a stronger structure with minimal changes in the coefficient of behavior. Additionally, this design has allowed for greater energy dissipation during seismic events, further enhancing the structure's resilience to earthquakes. By comprehensively examining and reinforcing the vulnerability of buildings and infrastructure, along with implementing advanced risk assessment techniques, we can significantly reduce casualties and damages caused by earthquakes in Iran. The findings of this study offer valuable insights for civil engineering professionals in the field of structural engineering, aiding them in designing safer and more resilient structures.

Keywords: modal pushover analysis, response modification factor, high-strength concrete, concrete shear walls, high-rise building

Procedia PDF Downloads 128

Authors: Ka C. Lam, Oluwafunmibi S. Idowu

Abstract:

Uncertainty in cost is a major factor affecting performance of construction projects. To our knowledge, several conceptual cost models have been developed with varying degrees of accuracy. Incorporating conceptual quantities into conceptual cost models could improve the accuracy of early predesign cost estimates. Hence, the development of quantity models for estimating conceptual quantities of framed reinforced concrete structures using supervised machine learning is the aim of the current research. Using measured quantities of structural elements and design variables such as live loads and soil bearing pressures, response and predictor variables were defined and used for constructing conceptual quantities models. Twenty-four models were developed for comparison using a combination of non-parametric support vector regression, linear regression, and bootstrap resampling techniques. R programming language was used for data analysis and model implementation. Gross soil bearing pressure and gross floor loading were discovered to have a major influence on the quantities of concrete and reinforcement used for foundations. Building footprint and gross floor loading had a similar influence on beams and slabs. Future research could explore the modelling of other conceptual quantities for walls, finishes, and services using machine learning techniques. Estimation of conceptual quantities would assist construction planners in early resource planning and enable detailed performance evaluation of early cost predictions.

Keywords: bootstrapping, conceptual quantities, modelling, reinforced concrete, support vector regression

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Authors: Anita Singh, Richa Naula, Manoj Raghav

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Nutrient rich and high-yielding varieties of fenugreek can be developed by using genotypes which are naturally high in nutrients. Gene banks harbour scanty germplasm collection of Trigonella spp. and a very little background information about its genetic diversity. The extent of genetic diversity in a specific breeding population depends upon the genotype included in it. The present investigation aims at the estimation of macronutrient (phosphorus by spectrophotometer and potassium by flame photometer), micronutrients, namely, iron, zinc, manganese, and copper from seeds of fenugreek genotypes using atomic absorption spectrophotometer, protein by Rapid N Cube Analyser and Steroidal Saponins. Twenty-eight genotypes of fenugreek along with two standard checks, namely, Pant Ragini and Pusa Early Bunching were collected from different parts of India, and nutrient contents of each genotype were determined at G. B. P. U. A. & T. Laboratory, Pantnagar. Highest potassium content was observed in PFG-35 (1207 mg/100g). PFG-37 and PFG-20 were richest in phosphorus, iron and manganese content among all the genotypes. The lowest zinc content was found in PFG-26 (1.19 mg/100g), while the maximum zinc content was found in PFG- 28 (4.43 mg/100g). The highest content of copper was found in PFG-26 (1.97 mg/100g). PFG-39 has the highest protein content (29.60 %). Significant differences were observed in the steroidal saponin among the genotypes. Saponin content ranged from 0.38 g/100g to 1.31 g/100g. Steroidal Saponins content was found the maximum in PFG-36 (1.31 g/100g) followed by PFG-17 (1.28 g/100g). Therefore, the genotypes which are rich in nutrient and oil content can be used for plant biofortification, dietary supplements, and herbal products.

Keywords: genotypes, macronutrients, micronutrient, protein, seeds

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Authors: Kothuri Sriraman, Mattupalli Komal Teja

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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

Procedia PDF Downloads 332

Authors: Sanjukta Badhai, Durga Barik, Bairagi C. Mallick

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In the present study, Beta-Sitosterol in Lawsonia methanolic leaf extract embedded in controlled release nanocomposite was prepared and evaluated for in vivo anticancer efficacy in dimethyl hydrazine (DMH) induced colon cancer. In the present study, colon cancer was induced by s.c injection of DMH (20 mg/kg b.wt) for 15 weeks. The animals were divided into five groups as follows control, DMH alone, DMH and Beta Sitosterol nanocomposite (50mg/kg), DMH and Beta Sitosterol nanocomposite (100 mg/kg) and DMH and Standard Silymarin (100mg/kg) and the treatment was carried out for 15 weeks. At the end of the study period, the blood was withdrawn, and serum was separated for haematological, biochemical analysis and tumor markers. Further, the colonic tissue was removed for the estimation of antioxidants and histopathological analysis. The results of the study displays that DMH intoxication elicits altered haematological parameters (RBC,WBC, and Hb), elevated lipid peroxidation and decreased antioxidants level (SOD, CAT, GPX, GST and GSH), elevated lipid profiles (cholesterol and triglycerides), tumor markers (CEA and AFP) and altered colonic tissue histology. Meanwhile, treatment with Beta Sitosterol nanocomposites significantly restored the altered biochemicals parameters in DMH induced colon cancer mediated by its anticancer efficacy. Further, Beta Sitosterol nanocomposite (100 mg/kg) showed marked efficacy.

Keywords: nanocomposites, herbal formulation, henna, beta sitosterol, colon cancer, dimethyl hydrazine, antioxidant, lipid peroxidation

Procedia PDF Downloads 148

Authors: Rakesh Kumar, Fatima Electricwala

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One of the major thrusts of the Bus Rapid Transit System is to reduce the commuter’s dependency on private vehicles and increase the shares of public transport to make urban transportation system environmentally sustainable. In this study, commuter mode choice analysis is performed that examines behavioral responses to the proposed Bus Rapid Transit System (BRTS) in Surat, with estimation of the probable shift from private mode to public mode. Further, evaluation of the BRTS scenarios, using Surat’s transportation ecological footprint was done. A multi-modal simulation model was developed in Biogeme environment to explicitly consider private users behaviors and non-linear environmental impact. The data of the different factors (variables) and its impact that might cause modal shift of private mode users to proposed BRTS were collected through home-interview survey using revealed and stated preference approach. A multi modal logit model of mode-choice was then calibrated using the collected data and validated using proposed sample. From this study, a set of perception factors, with reliable and predictable data base, to explain the variation in modal shift behaviour and their impact on Surat’s ecological environment has been identified. A case study of the proposed BRTS connecting the Surat Industrial Hub to the coastal area is provided to illustrate the approach.

Keywords: BRTS, private modes, mode choice models, ecological footprint

Procedia PDF Downloads 507

Authors: Zama Mahmood

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The increasing demand of food management, monitoring of the crop growth and forecasting its yield well before harvest is very important. These days, yield assessment together with monitoring of crop development and its growth are being identified with the help of satellite and remote sensing images. Studies using remote sensing data along with field survey validation reported high correlation between vegetation indices and yield. With the development of remote sensing technique, the detection of crop and its mechanism using remote sensing data on regional or global scales have become popular topics in remote sensing applications. Punjab, specially the southern Punjab region is extremely favourable for wheat production. But measuring the exact amount of wheat production is a tedious job for the farmers and workers using traditional ground based measurements. However, remote sensing can provide the most real time information. In this study, using the Normalized Differentiate Vegetation Index (NDVI) indicator developed from Landsat satellite images, the yield of wheat has been estimated during the season of 2013-2014 for the agricultural area around Bahawalpur. The average yield of the wheat was found 35 kg/acre by analysing field survey data. The field survey data is in fair agreement with the NDVI values extracted from Landsat images. A correlation between wheat production (ton) and number of wheat pixels has also been calculated which is in proportional pattern with each other. Also a strong correlation between the NDVI and wheat area was found (R2=0.71) which represents the effectiveness of the remote sensing tools for crop monitoring and production estimation.

Keywords: landsat, NDVI, remote sensing, satellite images, yield

Procedia PDF Downloads 319

Authors: Alok Pal Jain, Santram Lodhi

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Martynia annua Linn. (Martyniaccae) is traditionally used in inflammation and applied locally to tuberculosis glands of camel’s neck. The leaves used topically to bites of venomous insects and wounds of domestic animals. Chemical examination of Martynia annua leaves revealed the presence of glycosides, tannins, proteins, phenols and flavonoids. The present study was aimed to evaluate the anti-arthritic activity of methanolic extract of Martynia annua leaves. Methanolic extract of Martynia annua leaves was tested by using in vivo collagen-induced arthritis mouse model to investigate the anti-rheumatoid arthritis activity. In addition, antioxidant effect of methanolic extract was determined by the estimation of antioxidants level in joint tissues. The severity of arthritis was assessed by arthritis score and edema. Levels of cytokines TNF-α and IL-6, in the joint tissue homogenate were measured using ELISA. A high dose (250 mg/kg) of methanolic extract was significantly reduced the degree of inflammation in mice as compared with reference drug. Antioxidants level and malondialdehyde (MDA) in joint tissue homogenate found significantly (p < 0.05) higher. Methanolic extract at dose of 250 mg/kg modulated the cytokines production and suppressed the oxidative stress in the mice with collagen-induced arthritis. This study suggested that Martynia annua might be alternative herbal medicine for the management of rheumatoid arthritis.

Keywords: Martynia annua, collagen, rheumatoid arthritis, antioxidants

Procedia PDF Downloads 284

Authors: Mpaphi Major

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Soil erosion is becoming an important aspect of land degradation. Therefore it is of great consideration to note any factor that may escalate the rate of soil erosion in our arable land. There exist 3 main driving forces in soil erosion which are rainfall, wind and land use of which in this project only rainfall and land use will be looked at. With the increase in world population at an alarming rate, the demand for food production is expected to increase which will in turn lead to more land being converted from forests to agricultural use of which very few of it are now fertile. In our country Botswana, the rate of crop production is decreasing due to the wearing away of the fertile top soil and poor arable land management. As a result, some studies on the rate of soil loss and farm management practices should be conducted so that best soil and water conservation practices should be employed and hence reduce the risk of soil loss and increase the rate of crop production and yield. The Soil loss estimation model for Southern Africa (SLEMSA) will be used to estimate the rate of soil loss in some selected arable farms within the Palapye watershed and some field observations will be made to determine the management practices used and their impact on the arable land. Upon observations it have been found that many arable fields have been exposed to soil erosion, of which the affected parts are no longer suitable for any crop production unless the land areas are modified. Improper land practices such as ploughing along the slope and land cultivation practices were observed. As a result farmers need to be educated on best conservation practices that can be used to manage their arable land hence reduced risk of soil erosion and improved crop production.

Keywords: soil and water conservation, soil erosion, SLEMSA, land degradation

Procedia PDF Downloads 390

Authors: Dhanashree Aole, V. Hariharan, Swati Surushe

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Corrosion can cause serious and expensive damage to the automobile components. Various proven techniques for controlling and preventing corrosion depend on the specific material to be protected. Electrochemical Impedance Spectroscopy (EIS) and salt spray tests are commonly used to assess the corrosion degradation mechanism of coatings on metallic surfaces. While, the only test which monitors the corrosion rate in real time is known as Linear Polarisation Resistance (LPR). In this study, electrochemical tests (EIS & LPR) and spray test are reviewed to assess the corrosion resistance and durability of different coatings. The main objective of this study is to correlate the test results obtained using linear polarization resistance (LPR) and Electrochemical Impedance Spectroscopy (EIS) with the results obtained using standard salt spray test. Another objective of this work is to evaluate the performance of various coating systems- CED, Epoxy, Powder coating, Autophoretic, and Zn-trivalent coating for vehicle underbody application. The corrosion resistance coating are assessed. From this study, a promising correlation between different corrosion testing techniques is noted. The most profound observation is that electrochemical tests gives quick estimation of corrosion resistance and can detect the degradation of coatings well before visible signs of damage appear. Furthermore, the corrosion resistances and salt spray life of the coatings investigated were found to be according to the order as follows- CED> powder coating > Autophoretic > epoxy coating > Zn- Trivalent plating.

Keywords: Linear Polarization Resistance (LPR), Electrochemical Impedance Spectroscopy (EIS), salt spray test, sacrificial and barrier coatings

Procedia PDF Downloads 512

Authors: Seyed M. Khatami, H. Naderpour, R. Vahdani, R. C. Barros

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Many previous studies have been carried out to calculate the impact force and the dissipated energy between two neighboring buildings during seismic excitation, when they collide with each other. Numerical studies are an important part of impact, which several researchers have tried to simulate the impact by using different formulas. Estimation of the impact force and the dissipated energy depends significantly on some parameters of impact. Mass of bodies, stiffness of spring, coefficient of restitution, damping ratio of dashpot and impact velocity are some known and unknown parameters to simulate the impact and measure dissipated energy during collision. Collision is usually shown by force-displacement hysteresis curve. The enclosed area of the hysteresis loop explains the dissipated energy during impact. In this paper, the effect of using different types of impact models is investigated in order to calculate the impact force. To increase the accuracy of impact model and to optimize the results of simulations, a new damping equation is assumed and is validated to get the best results of impact force and dissipated energy, which can show the accuracy of suggested equation of motion in comparison with other formulas. This relation is called "n-m". Based on mathematical relation, an initial value is selected for the mentioned coefficients and kinetic energy loss is calculated. After each simulation, kinetic energy loss and energy dissipation are compared with each other. If they are equal, selected parameters are true and, if not, the constant of parameters are modified and a new analysis is performed. Finally, two unknown parameters are suggested to estimate the impact force and calculate the dissipated energy.

Keywords: impact force, dissipated energy, kinetic energy loss, damping relation

Procedia PDF Downloads 540

Authors: Sobar M. Johari, Ida Putri Anjarsari

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In the transmission of monetary instrument towards real sector of the economy, Bank Indonesia as monetary authority has developed Islamic Bank Indonesia Certificate (abbreviated as SBIS) as an instrument in Islamic open market operation. One of the monetary transmission channels could take place through financing channel from which the fund is used as the source of banking financing. This study aims to analyse the impact of Islamic monetary instrument towards output or economic growth. Data used in this research is taken from Bank Indonesia and Central Board of Statistics for the period of January 2008 until December 2015. The study employs Granger Causality Test, Vector Error Correction Model (VECM), Impulse Response Function (IRF) technique and Forecast Error Variance Decomposition (FEVD) as its analytical methods. The results show that, first, the transmission mechanism of banking financing channel are not linked to output. Second, estimation results of VECM show that SBIS, PUAS, and FIN have significant impact in the long term towards output. When there is monetary shock, output or economic growth could be recovered and stabilized in the short term. FEVD results show that Islamic banking financing contributes 1.33 percent to increase economic growth.

Keywords: Islamic monetary instrument, Islamic banking financing channel, economic growth, Vector Error Correction Model (VECM)

Procedia PDF Downloads 261