Search results for: adaptive estimation

Authors: Peiming Li

Abstract:

This paper presents an innovative blockchain-based approach to enhance the reliability and efficiency of federated learning systems. By integrating a decentralized oracle consensus mechanism into the federated learning framework, we address key challenges of data and model integrity. Our approach utilizes a network of redundant oracles, functioning as independent validators within an epoch-based training system in the federated learning model. In federated learning, data is decentralized, residing on various participants' devices. This scenario often leads to concerns about data integrity and model quality. Our solution employs blockchain technology to establish a transparent and tamper-proof environment, ensuring secure data sharing and aggregation. The decentralized oracles, a concept borrowed from blockchain systems, act as unbiased validators. They assess the contributions of each participant using a Hidden Markov Model (HMM), which is crucial for evaluating the consistency of participant inputs and safeguarding against model poisoning and malicious activities. Our methodology's distinct feature is its epoch-based training. An epoch here refers to a specific training phase where data is updated and assessed for quality and relevance. The redundant oracles work in concert to validate data updates during these epochs, enhancing the system's resilience to security threats and data corruption. The effectiveness of this system was tested using the Mnist dataset, a standard in machine learning for benchmarking. Results demonstrate that our blockchain-oriented federated learning approach significantly boosts system resilience, addressing the common challenges of federated environments. This paper aims to make these advanced concepts accessible, even to those with a limited background in blockchain or federated learning. We provide a foundational understanding of how blockchain technology can revolutionize data integrity in decentralized systems and explain the role of oracles in maintaining model accuracy and reliability.

Keywords: federated learning system, block chain, decentralized oracles, hidden markov model

Procedia PDF Downloads 63

Authors: Rick Denley

Abstract:

Urban planning today faces unprecedented challenges as cities strive for sustainability in response to climate change, rapid population growth, and the increasing demand for green infrastructure. In this context, effective leadership becomes as essential as innovative design and technology. Rick Denley’s keynote, Resilient Leadership in Sustainable Urban Planning: Embracing Change to Shape Future Cities, focuses on equipping urban planners, academics, and industry leaders with the leadership tools necessary to guide their teams and projects through complex transitions. His session addresses the essential role of leadership in driving sustainable urban transformations, adapting to changing environmental demands, and fostering collaborative approaches to green infrastructure initiatives. Rick’s keynote is grounded in his Change Growth Formula, a practical framework he has developed over years of leading corporate transformations and advising on resilience and growth. His talk will focus on how urban planning professionals can cultivate adaptability, inspire innovative thinking, and lead their teams to achieve impactful urban projects that prioritize sustainable landscapes, water management, and green spaces. Attendees will gain actionable insights on building a resilient mindset, leveraging collaborative partnerships, and aligning urban planning initiatives with environmental goals. This session is aligned with the conference’s objectives to share interdisciplinary knowledge, explore innovative solutions, and address critical challenges in urban landscape and urban planning. Rick’s approach combines insights from leadership theory with real-world applications in urban planning, making his talk relevant for professionals seeking both inspiration and practical tools to lead sustainable transformations.

Keywords: resilient leadership, change management, collaborative planning, adaptive leadership, community engagement, leadership in urban design

Procedia PDF Downloads 6

Authors: Abeer Rababa'h, Ragad Bsoul, Mohammad Alkhatatbeh, Karem Alzoubi

Abstract:

Introduction: Tobacco use is one of the main risk factors to cardiovascular diseases (CVD) and atherosclerosis in particular. WPS contains several toxic materials such as: nicotine, carcinogens, tar, carbon monoxide and heavy metals. Thus, WPS is considered to be as one of the toxic environmental factors that should be investigated intensively. Therefore, the aim of this study is to investigate the effect of WPS on several cardiovascular biological markers that may cause atherosclerosis in mice. The study also conducted to study the temporal effects of WPS on the atherosclerotic biomarkers upon short (2 weeks) and long-term (8 weeks) exposures. Methods: mice were exposed to WPS and heart homogenates were analyzed to elucidate the effects of WPS on matrix metalloproteinase (MMPs), endothelin-1 (ET-1) and, myeloperoxidase (MPO). Following protein estimation, enzyme-linked immunosorbent assays were done to measure the levels of MMPs (isoforms 1, 3, and 9), MPO, and ET-1 protein expressions. Results: our data showed that acute exposure to WPS significantly enhances the levels of MMP-3, MMP- 9, and MPO expressions (p < 0.05) compared to their corresponding control. However, the body was capable to normalize the level of expressions for such parameters following continuous exposure for 8 weeks (p > 0.05). Additionally, we showed that the level of ET-1 expression was significantly higher upon chronic exposure to WPS compared to both control and acute exposure groups (p < 0.05). Conclusion: Waterpipe exposure has a significant negative effect on atherosclerosis and the enhancement of the atherosclerotic biomarkers expression (MMP-3 and 9, MPO, and ET-1) might represent an early scavenger of compensatory efforts to maintain cardiac function after WP exposure.

Keywords: atherosclerotic biomarkers, cardiovascular disease, matrix metalloproteinase, waterpipe

Procedia PDF Downloads 352

Authors: Mustapha Saidu, Bilyaminu Mohammed

Abstract:

The study was conducted in Udubo Grazing Reserve between July 2019 and October 2019 to assess forage utilization for pasture-based livestock production in reserve. The grazing land was cross-divided into grids, where 15 coordinates were selected as the sample points. Grids of one-kilometer interval were made. The grids were systematically selected 1 grid after 7 grids. 1 × 1-meter quadrat was made at the coordinate of the selected grids for measurement, estimation, and sample collection. The results of the study indicated that Zornia glochidiatah has the highest percent of species composition (42%), while Mitracarpus hirtus has the lowest percent (0.1%). Urochloa mosambicensis has 48 percent of height removed and 27 percent used by weight, Zornia glochidiata 60 percent of height removed and 57 percent used by weight, Alysicapus veginalis has 55 percent of height removed, and 40 percent used by weight, and Cenchrus biflorus has 40 percent of height removed and 28 percent used by weight. The target is 50 percent utilization of forage by weight during a grazing period as well as at the end of the grazing season. The study found that Orochloa mosambicensis, Alysicarpus veginalis, and Cenchrus biflorus had lower percent by weight which is normal, while Zornia glochidiata had a higher percent by weight which is an indication of danger. The study recommends that the identification of key plant species in pasture and rangeland is critical to implementing a successful grazing management plan. There should be collective action and promotion of historically generated grazing knowledge through public and private advocacies.

Keywords: forage, grazing reserve, live stock, pasture, plant species

Procedia PDF Downloads 89

Authors: Sony Baral, Harald Vacik

Abstract:

This study analyzes the sustainability of community forest management in two community forests in Terai and Hills of Nepal, representing four forest types: 1) Shorearobusta, 2) Terai hardwood, 3) Schima-Castanopsis, and 4) other Hills. The sustainability goals for this region include maintaining and enhancing the forest stocks. Considering this, we analysed changes in species composition, stand density, growing stock volume, and growth-to-removal ratio at 3-5 year intervals from 2005-2016 within 109 permanent forest plots (57 in the Terai and 52 in the Hills). To complement inventory data, forest users, forest committee members, and forest officials were consulted. The results indicate that the relative representation of economically valuable tree species has increased. Based on trends in stand density, both forests are being sustainably managed. Pole-sized trees dominated the diameter distribution, however, with a limited number of mature trees and declined regeneration. The forests were over-harvested until 2013 but under-harvested in the recent period in the Hills. In contrast, both forest types were under-harvested throughout the inventory period in the Terai. We found that the ecological dimension of sustainable forest management is strongly achieved while the economic dimension is lacking behind the current potential. Thus, we conclude that maintaining a large number of trees in the forest does not necessarily ensure both ecological and economical sustainability. Instead, priority should be given on a rational estimation of the annual harvest rates to enhance forest resource conditions together with regular benefits to the local communities.

Keywords: community forests, diversity, growing stock, forest management, sustainability, nepal

Procedia PDF Downloads 97

Authors: Zhang Pinliang, Chen Chuan, Song Guangming, Wu Qiang, Gong Zizheng, Li Ming

Abstract:

The active removal of space debris and asteroid defense are important issues in human space activities. Both of them need a detumbling process, for almost all space debris and asteroid are in a rotating state, and it`s hard and dangerous to capture or remove a target with a relatively high tumbling rate. So it`s necessary to find a method to reduce the angular rate first. The laser ablation method is an efficient way to tackle this detumbling problem, for it`s a contactless technique and can work at a safe distance. In existing research, a laser rotational control strategy based on the estimation of the instantaneous angular velocity of the target has been presented. But their calculation of control torque produced by a laser, which is very important in detumbling operation, is not accurate enough, for the method they used is only suitable for the plane or regularly shaped target, and they did not consider the influence of irregular shape and the size of the spot. In this paper, based on the triangulation reconstruction of the target surface, we propose a new method to calculate the impulse of the irregularly shaped target under both the covered irradiation and spot irradiation of the laser and verify its accuracy by theoretical formula calculation and impulse measurement experiment. Then we use it to study the process of detumbling cylinder and asteroid by laser. The result shows that the new method is universally practical and has high precision; it will take more than 13.9 hours to stop the rotation of Bennu with 1E+05kJ laser pulse energy; the speed of the detumbling process depends on the distance between the spot and the centroid of the target, which can be found an optimal value in every particular case.

Keywords: detumbling, laser ablation drive, space target, space debris remove

Procedia PDF Downloads 85

Authors: Kornelius Ronald Demu, Dewi Retno Sari Saputro, Purnami Widyaningsih

Abstract:

Human Development Index (HDI) is a standard measurement for a country's human development. Several factors may have influenced it, such as life expectancy, gross domestic product (GDP) based on the province's annual expenditure, the number of poor people, and the percentage of an illiterate people. The scatter plot between HDI and the influenced factors show that the plot does not follow a specific pattern or form. Therefore, the HDI's data in Indonesia can be applied with a nonparametric regression model. The estimation of the regression curve in the nonparametric regression model is flexible because it follows the shape of the data pattern. One of the nonparametric regression's method is a truncated spline. Truncated spline regression is one of the nonparametric approach, which is a modification of the segmented polynomial functions. The estimator of a truncated spline regression model was affected by the selection of the optimal knots point. Knot points is a focus point of spline truncated functions. The optimal knots point was determined by the minimum value of generalized cross validation (GCV). In this article were applied the data of Human Development Index with a truncated spline nonparametric regression model. The results of this research were obtained the best-truncated spline regression model to the HDI's data in Indonesia with the combination of optimal knots point 5-5-5-4. Life expectancy and the percentage of an illiterate people were the significant factors depend to the HDI in Indonesia. The coefficient of determination is 94.54%. This means the regression model is good enough to applied on the data of HDI in Indonesia.

Keywords: generalized cross validation (GCV), Human Development Index (HDI), knots point, nonparametric regression, truncated spline

Procedia PDF Downloads 339

Authors: Nurul Aliaa Idris, David A. Collings

Abstract:

Phi thickenings are specialized secondary cell wall thickenings that are found in the cortex of the roots in a wide range of plant species, including orchids. The role of phi thickenings in the root is still under debate through research have linked environmental conditions, particularly abiotic stresses such as water stress, heavy metal stress and salinity to their induction in the roots. It has also been suggested that phi thickenings may act as a barrier to regulate solute uptake, act as a physical barrier against fungal hyphal penetration due to its resemblance to the Casparian strip and play a mechanical role to support cortical cells. We have investigated phi thickening function in epiphytic orchids of the genus Miltoniopsis through induction experiment against factors such as soil compaction and water stress. The permeability of the phi thickenings in Miltoniopsis was tested through uptake experiments using the fluorescent tracer dyes Calcofluor white, Lucifer yellow and Propidium iodide then viewed with wide-field or confocal microscopy. To test whether phi thickening may prevent fungal colonization in the root cell, fungal re-infection experiment was conducted by inoculating isolated symbiotic fungus to sterile in vitro Miltoniopsis explants. As the movement of fluorescent tracers through the apoplast was not blocked by phi thickenings, and as phi thickenings developed in the roots of sterile cultures in the absence of fungus and did not prevent fungal colonization of cortical cells, the phi thickenings in Miltoniopsis do not function as a barrier. Phi thickenings were found to be absent in roots grown on agar and remained absent when plants were transplanted to moist soil. However, phi thickenings were induced when plants were transplanted to well-drained media, and by the application of water stress in all soils tested. It is likely that phi thickenings stabilize the root cortex during dehydration. Nevertheless, the varied induction responses present in different plant species suggest that the phi thickenings may play several adaptive roles, instead of just one, depending on species.

Keywords: abiotic stress, Miltoniopsis, orchid, phi thickening

Procedia PDF Downloads 148

Authors: Esther M. Folarin, Evans Osabuohien, Ademola Onabote

Abstract:

Agriculture constitutes an important part of development and poverty mitigation in lower-middle-income countries, like Nigeria. The level of agricultural productivity in the Nigerian economy in line with the level of demand necessary to meet the desired expectation of the Nigerian populace is threatening to meeting the standard of the United Nations (UN) Sustainable Development Goals (SDGs); This includes the SDG-2 (achieve food security through agricultural productivity). The overall objective of the study is to reveal the performance of the interaction variable in the model among other factors that help in the achievement of greater Nigerian agricultural productivity. The study makes use of Wave 4 (2018/2019) of the Living Standard Measurement Studies, Integrated Survey on Agriculture (LSMS-ISA). Qualitative analysis of the information was also used to provide complimentary answers to the quantitative analysis done in the study. The study employed human capital theory and Grossman’s theory of health Demand in explaining the relationships that exist between the variables within the model of the study. The study engages the Instrumental Variable Regression technique in achieving the broad objectives among other techniques for the other specific objectives. The estimation results show that there exists a positive relationship between female healthcare and the level of female agricultural productivity in Nigeria. In conclusion, the study emphasises the need for more provision and empowerment for greater female access to healthcare and educational attainment levels that aids higher female agricultural productivity and consequently an improvement in the total agricultural productivity of the Nigerian economy.

Keywords: agricultural productivity, education, female, healthcare, investment

Procedia PDF Downloads 81

Authors: Jamshed Ahmad, Abdul Wahid Khan, Javed Ali Khan

Abstract:

Managing software quality requirements change management is a difficult task in the field of software engineering. Avoiding incoming changes result in user dissatisfaction while accommodating to many requirement changes may delay product delivery. Poor requirements management is solely considered the primary cause of the software failure. It becomes more challenging in global software outsourcing. Addressing success factors in quality requirement change management is desired today due to the frequent change requests from the end-users. In this research study, success factors are recognized and scrutinized with the help of a systematic literature review (SLR). In total, 16 success factors were identified, which significantly impacted software quality requirement change management. The findings show that Proper Requirement Change Management, Rapid Delivery, Quality Software Product, Access to Market, Project Management, Skills and Methodologies, Low Cost/Effort Estimation, Clear Plan and Road Map, Agile Processes, Low Labor Cost, User Satisfaction, Communication/Close Coordination, Proper Scheduling and Time Constraints, Frequent Technological Changes, Robust Model, Geographical distribution/Cultural differences are the key factors that influence software quality requirement change. The recognized success factors and validated with the help of various research methods, i.e., case studies, interviews, surveys and experiments. These factors are then scrutinized in continents, database, company size and period of time. Based on these findings, requirement change will be implemented in a better way.

Keywords: global software development, requirement engineering, systematic literature review, success factors

Procedia PDF Downloads 197

Authors: Praveen Chandramenon, Andrew Gascoyne, Fideline Tchuenbou-Magaia

Abstract:

Aquaponics offers a simple conclusive solution to the food and environmental crisis of the world. This approach combines the idea of Aquaculture (growing fish) to Hydroponics (growing vegetables and plants in a soilless method). Smart Aquaponics explores the use of smart technology including artificial intelligence and IoT, to assist farmers with better decision making and online monitoring and control of the system. Identification of different growth stages of Swiss Chard plants and predicting its harvest time is found to be important in Aquaponic yield management. This paper brings out the comparative analysis of a standard Aquaponics with a Vermiponics (Aquaponics with worms), which was grown in the controlled environment, by implementing IoT and deep learning-based growth stage segregation and harvest time prediction of Swiss Chards before and after applying an optimal freshwater replenishment. Data collection, Growth stage classification and Harvest Time prediction has been performed with and without water replenishment. The paper discusses the experimental design, IoT and sensor communication with architecture, data collection process, image segmentation, various regression and classification models and error estimation used in the project. The paper concludes with the results comparison, including best models that performs growth stage segregation and harvest time prediction of the Aquaponic and Vermiponic testbed with and without freshwater replenishment.

Keywords: aquaponics, deep learning, internet of things, vermiponics

Procedia PDF Downloads 72

Authors: Saad M. Darwish, Adel A. El-Zoghabi, Moustafa F. Ashry

Abstract:

The popularity of the Internet and the availability of powerful computers and high-speed networks as low-cost commodity components are changing the way we use computers today. These technical opportunities have led to the possibility of using geographically distributed and multi-owner resources to solve large-scale problems in science, engineering, and commerce. Recent research on these topics has led to the emergence of a new paradigm known as Grid computing. To achieve the promising potentials of tremendous distributed resources, effective and efficient load balancing algorithms are fundamentally important. Unfortunately, load balancing algorithms in traditional parallel and distributed systems, which usually run on homogeneous and dedicated resources, cannot work well in the new circumstances. In this paper, the concept of a fast fractal transform in heterogeneous grid computing based on R-tree and the domain-range entropy is proposed to improve fault tolerance and load balancing algorithm by improve connectivity, communication delay, network bandwidth, resource availability, and resource unpredictability. A novel two-dimension figure of merit is suggested to describe the network effects on load balance and fault tolerance estimation. Fault tolerance is enhanced by adaptively decrease replication time and message cost while load balance is enhanced by adaptively decrease mean job response time. Experimental results show that the proposed method yields superior performance over other methods.

Keywords: Grid computing, load balancing, fault tolerance, R-tree, heterogeneous systems

Procedia PDF Downloads 491

Authors: Anna Siegler

Abstract:

Bullying among peers is not uncommon; however, adults can notice only a fragment of the cases of harassment during everyday life. The systemic approaches of bullying investigation put the whole school community in the focus of attention and propose that the solution should emerge from the culture of the school. Bystanders are essential in the prevention and intervention processes as an active agent rather than passive. For combating exclusion, stigmatization and harassment, it is important that the bystanders have to realize they have the power to take action. To prevent the escalation of violence, victims must believe that students and teachers will help them and their environment is able to provide safety. The study based on scientific narrative psychological approach, and focuses on the examination of the different perspectives of students, how peers are mentalizing with each other in case of bullying. The data collection contained responses of students (N = 138) from three schools in Hungary, and from three different area of the country (Budapest, Martfű and Barcs). The test battery include Bullying Prevalence Questionnaire, Interpersonal Reactivity Index and an instruction to get narratives about bullying, which effectiveness was tested during a pilot test. The obtained results are in line with the findings of previous bullying research: the victims are mentalizing less with their peers and experience greater personal distress when they are in identity threatening situations, thus focusing on their own difficulties rather than social signals. This isolation is an adaptive response in short-term although it seems to lead to a deficit in social skills later in life and makes it difficult for students to become socially integrated to society. In addition the results also show that students use more mental state attribution when they report verbal bullying than in case of physical abuse. Those who witness physical harassment also witness concrete answers to the problem from teachers, in contrast verbal abuse often stays without consequences. According to the results students mentalizing more in these stories because they have less normative explanation to what happened. To expanding bullying literature, this research helps to find ways to reduce school violence through community development.

Keywords: bullying, mentalization, narrative, school culture

Procedia PDF Downloads 164

Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

Abstract:

An estimating equation technique is an alternative method of the widely used maximum likelihood methods, which enables us to ease some complexity due to the complex characteristics of time-varying covariates. In the situations, when both the time-varying covariates and left-truncation are considered in the model, the maximum likelihood estimation procedures become much more burdensome and complex. To ease the complexity, in this study, the modified estimating equations those have been given high attention and considerations in many researchers under semiparametric transformation model was proposed. The purpose of this article was to develop the modified estimating equation under flexible and general class of semiparametric transformation models for left-truncated and right censored survival data with time-varying covariates. Besides the commonly applied Cox proportional hazards model, such kind of problems can be also analyzed with a general class of semiparametric transformation models to estimate the effect of treatment given possibly time-varying covariates on the survival time. The consistency and asymptotic properties of the estimators were intuitively derived via the expectation-maximization (EM) algorithm. The characteristics of the estimators in the finite sample performance for the proposed model were illustrated via simulation studies and Stanford heart transplant real data examples. To sum up the study, the bias for covariates has been adjusted by estimating density function for the truncation time variable. Then the effect of possibly time-varying covariates was evaluated in some special semiparametric transformation models.

Keywords: EM algorithm, estimating equation, semiparametric transformation models, time-to-event outcomes, time varying covariate

Procedia PDF Downloads 152

Authors: Tafadzwa Shumba, Rose C. Nyatondo, Regret Sunge

Abstract:

This research analyses the impact of budget deficits on the economic performance of Zimbabwe. The study employs the autoregressive distributed lag (ARDL) confines testing method to co-integration and long-run estimation using time series data from 1980-2018. The Augmented Dick Fuller (ADF) and the Granger approach were used to testing for stationarity and causality among the factors. Co-integration test results affirm a long term association between GDP development rate and descriptive factors. Causality test results show a unidirectional connection between budget shortfall to GDP development and bi-directional causality amid debt and budget deficit. This study also found unidirectional causality from debt to GDP growth rate. ARDL estimates indicate a significantly positive long term and significantly negative short term impact of budget shortfall on GDP. This suggests that budget deficits have a short-run growth retarding effect and a long-run growth-inducing effect. The long-run results follow the Keynesian theory that posits that fiscal deficits result in an increase in GDP growth. Short-run outcomes follow the neoclassical theory. In light of these findings, the government is recommended to minimize financing of recurrent expenditure using a budget deficit. To achieve sustainable growth and development, the government needs to spend an absorbable budget deficit focusing on capital projects such as the development of human capital and infrastructure.

Keywords: ARDL, budget deficit, economic performance, long run

Procedia PDF Downloads 97

Authors: Somaye Khademi, Elahe Zoghi Hoseini, Mostafa Norouzi

Abstract:

Determining the manner of land-use and the spatial structure of cities on the one hand, and the economic value of each piece of land, on the other hand, land-use planning is always considered as the main part of urban planning. In this regard, emphasizing the efficient use of land, the sustainable development approach has presented a new perspective on urban planning and consequently on its most important pillar, i.e. land-use planning. In order to evaluate urban land-use, it has been attempted in this paper to select the most significant indicators affecting urban land-use and matching sustainable development indicators. Due to the significance of preserving ancient monuments and the surroundings as one of the main pillars of achieving sustainability, in this research, sustainability indicators have been selected emphasizing the preservation of ancient monuments and historical observance of the city of Susa as one of the historical cities of Iran. It has also been attempted to integrate these criteria with other land-use sustainability indicators. For this purpose, Kernel Density Estimation (KDE) and the AHP model have been used for providing maps displaying spatial density and combining layers as well as providing final maps respectively. Moreover, the rating of sustainability will be studied in different districts of the city of Shush so as to evaluate the status of land sustainability in different parts of the city. The results of the study show that different neighborhoods of Shush do not have the same sustainability in land-use such that neighborhoods located in the eastern half of the city, i.e. the new neighborhoods, have a higher sustainability than those of the western half. It seems that the allocation of a high percentage of these areas to arid lands and historical areas is one of the main reasons for their sustainability.

Keywords: city of Susa, historical heritage, land-use evaluation, urban sustainable development

Procedia PDF Downloads 379

Authors: Robin Singh, Mayank Nautiyal, Priyank Jain, Vatasta Koul, Vaibhav Sharma

Abstract:

The curiosity to investigate the space and its mysteries was dependably the main impetus of human interest, as the particle of livings exists from the "debut de l'Univers" (beginning of the Universe) typified with its few other living things. The sharp drive to uncover the secrets of stars and their unusual deportment was dependably an ignitor of stars investigation. As humankind lives in civilizations and states, stars likewise live in provinces named ‘clusters’. Clusters are separates into 2 composes i.e. open clusters and globular clusters. An open cluster is a gathering of thousand stars that were moulded from a comparable goliath sub-nuclear cloud and for the most part; contain Propulsion I (extremely metal-rich) and Propulsion II (mild metal-rich), where globular clusters are around gathering of more than thirty thousand stars that circles a galactic focus and basically contain Propulsion III (to a great degree metal-poor) stars. Futurology of this paper lies in the spectroscopic investigation of globular clusters like M92 and NGC419 and open clusters like M34 and IC2391 in different color bands by using software like VIREO virtual observatory, Aladin, CMUNIWIN, and MS-Excel. Assessing the outcome Hertzsprung-Russel (HR) diagram with exemplary cosmological models like Einstein model, De Sitter and Planck survey demonstrate for a superior age estimation of respective clusters. Colour-Magnitude Diagram of these clusters was obtained by photometric analysis in g and r bands which further transformed into BV bands which will unravel the idea of stars exhibit in the individual clusters.

Keywords: color magnitude diagram, globular clusters, open clusters, Einstein model

Procedia PDF Downloads 226

Authors: Nina Penkova, Kalin Krumov, Liliana Zashcova, Ivan Kassabov

Abstract:

The insulating glass units (IGU) are widely used in the advanced and renovated buildings in order to reduce the energy for heating and cooling. Rules for the choice of IGU to ensure energy efficiency and thermal comfort in the indoor space are well known. The existing of internal loads - gage or vacuum pressure in the hermetized gas space, requires additional attention at the design of the facades. The internal loads appear at variations of the altitude, meteorological pressure and gas temperature according to the same at the process of sealing. The gas temperature depends on the presence of coatings, coating position in the transparent multi-layer system, IGU geometry and space orientation, its fixing on the facades and varies with the climate conditions. An algorithm for modeling and numerical simulation of thermal fields and internal pressure in the gas cavity at insulating glass units as function of the meteorological conditions is developed. It includes models of the radiation heat transfer in solar and infrared wave length, indoor and outdoor convection heat transfer and free convection in the hermetized gas space, assuming the gas as compressible. The algorithm allows prediction of temperature and pressure stratification in the gas domain of the IGU at different fixing system. The models are validated by comparison of the numerical results with experimental data obtained by Hot-box testing. Numerical calculations and estimation of 3D temperature, fluid flow fields, thermal performances and internal loads at IGU in window system are implemented.

Keywords: insulating glass units, thermal loads, internal pressure, CFD analysis

Procedia PDF Downloads 273

Authors: Meriem Bahij, Ahmed Nafidi, Boujemâa Achchab, Sílvio M. A. Gama, José A. O. Matos

Abstract:

Stochastic modeling concerns the use of probability to model real-world situations in which uncertainty is present. Therefore, the purpose of stochastic modeling is to estimate the probability of outcomes within a forecast, i.e. to be able to predict what conditions or decisions might happen under different situations. In the present study, we present a model of a stochastic diffusion process based on the bi-Weibull distribution function (its trend is proportional to the bi-Weibull probability density function). In general, the Weibull distribution has the ability to assume the characteristics of many different types of distributions. This has made it very popular among engineers and quality practitioners, who have considered it the most commonly used distribution for studying problems such as modeling reliability data, accelerated life testing, and maintainability modeling and analysis. In this work, we start by obtaining the probabilistic characteristics of this model, as the explicit expression of the process, its trends, and its distribution by transforming the diffusion process in a Wiener process as shown in the Ricciaardi theorem. Then, we develop the statistical inference of this model using the maximum likelihood methodology. Finally, we analyse with simulated data the computational problems associated with the parameters, an issue of great importance in its application to real data with the use of the convergence analysis methods. Overall, the use of a stochastic model reflects only a pragmatic decision on the part of the modeler. According to the data that is available and the universe of models known to the modeler, this model represents the best currently available description of the phenomenon under consideration.

Keywords: diffusion process, discrete sampling, likelihood estimation method, simulation, stochastic diffusion process, trends functions, bi-parameters weibull density function

Procedia PDF Downloads 309

Authors: S. K. Thind, Aparjot Kaur

Abstract:

Heat stress is one of the major environmental factors drastically reducing wheat production. Crop heat tolerance can be enhanced by preconditioning of plants by exogenous application of osmoprotectants. Presently, the effect of trehalose pretreatment (at 1 mM, and 1.5 nM) under heat stress of 35±2˚C (moderate) and 40±2˚ (severe) for four and eight hour was conducted in wheat (Tricticum aestivum L.) genotypes viz. HD2967, PBW 175, PBW 343, PBW 621, and PBW 590. Heat stress affects wide spectrum of physiological processes within plants that are irreversibly damaged by stress. Membrane thermal stability (MTS) and cell viability was significantly decreased under heat stress for eight hours. Pretreatment with trehalose improved MTS and cell viability under stress and this effect was more promotory with higher concentration. Thermal stability of photosynthetic apparatus differed markedly between genotypes and Hill reaction activity was recorded more in PBW621 followed by C306 as compared with others. In all genotypes photolysis of water showed decline with increase in temperature stress. Trehalose pretreatment helped in sustaining Hill reaction activity probably by stabilizing the photosynthetic apparatus against heat-induced photo inhibition. Both plant growth and development were affected by temperature in both shoot and root under heat stress. The reduction was compensated partially by trehalose (1.5 mM) application. Adaption to heat stress is associated with the metabolic adjustment which led to accumulation of soluble sugars including non-reducing and reducing for their role in adaptive mechanism. Higher acid invertase activity in shoot of tolerant genotypes appeared to be a characteristic for stress tolerance. As sucrose synthase play central role in sink strength and in studied wheat genotype was positively related to dry matter accumulation. The duration of heat stress for eight hours had more severe effect on these parameters and trehalose application at 1.5 mM ameliorated it to certain extent.

Keywords: heat stress, Triticum aestivum, trehalose, membrane thermal stability, triphenyl tetrazolium chloride, reduction test, growth, sugar metabolism

Procedia PDF Downloads 326

Authors: Claudineia Brazil, Elison Eduardo Jardim Bierhals, Luciane Teresa Salvi, Rafael Haag

Abstract:

Renewable energy sources are dependent on climatic variability, so for adequate energy planning, observations of the meteorological variables are required, preferably representing long-period series. Despite the scientific and technological advances that meteorological measurement systems have undergone in the last decades, there is still a considerable lack of meteorological observations that form series of long periods. The reanalysis is a system of assimilation of data prepared using general atmospheric circulation models, based on the combination of data collected at surface stations, ocean buoys, satellites and radiosondes, allowing the production of long period data, for a wide gamma. The third generation of reanalysis data emerged in 2010, among them is the Climate Forecast System Reanalysis (CFSR) developed by the National Centers for Environmental Prediction (NCEP), these data have a spatial resolution of 0.50 x 0.50. In order to overcome these difficulties, it aims to evaluate the performance of solar radiation estimation through alternative data bases, such as data from Reanalysis and from meteorological satellites that satisfactorily meet the absence of observations of solar radiation at global and/or regional level. The results of the analysis of the solar radiation data indicated that the reanalysis data of the CFSR model presented a good performance in relation to the observed data, with determination coefficient around 0.90. Therefore, it is concluded that these data have the potential to be used as an alternative source in locations with no seasons or long series of solar radiation, important for the evaluation of solar energy potential.

Keywords: climate, reanalysis, renewable energy, solar radiation

Procedia PDF Downloads 209

Authors: H. Khanfari, M. Johari Fard

Abstract:

Dealing with carbonate reservoirs can be mind-boggling for the reservoir engineers due to various digenetic processes that cause a variety of properties through the reservoir. A good estimation of the reservoir heterogeneity which is defined as the quality of variation in rock properties with location in a reservoir or formation, can better help modeling the reservoir and thus can offer better understanding of the behavior of that reservoir. Most of reservoirs are heterogeneous formations whose mineralogy, organic content, natural fractures, and other properties vary from place to place. Over years, reservoir engineers have tried to establish methods to describe the heterogeneity, because heterogeneity is important in modeling the reservoir flow and in well testing. Geological methods are used to describe the variations in the rock properties because of the similarities of environments in which different beds have deposited in. To illustrate the heterogeneity of a reservoir vertically, two methods are generally used in petroleum work: Dykstra-Parsons permeability variations (V) and Lorenz coefficient (L) that are reviewed briefly in this paper. The concept of Lorenz is based on statistics and has been used in petroleum from that point of view. In this paper, we correlated the statistical-based Lorenz method to a petroleum concept, i.e. Kozeny-Carman equation and derived the straight line plot of Lorenz graph for a homogeneous system. Finally, we applied the two methods on a heterogeneous field in South Iran and discussed each, separately, with numbers and figures. As expected, these methods show great departure from homogeneity. Therefore, for future investment, the reservoir needs to be treated carefully.

Keywords: carbonate reservoirs, heterogeneity, homogeneous system, Dykstra-Parsons permeability variations (V), Lorenz coefficient (L)

Procedia PDF Downloads 221

Authors: Adebowale T. Odeyemi, Oluwafemi A. Ajenifuja

Abstract:

The leachate samples collected from Erifun dumpsite along Federal Polythenic road, Ado-Ekiti, Ekiti State, were subjected to bacteriological and mineral analyses. The bacteriological estimation and isolation were done using serial dilution and pour plating techniques. Antibiotic susceptibility test was done using agar disc diffusion technique. Atomic Absorption Spectophotometry method was used to analyze the heavy metal contents in the leachate samples. The bacterial and coliform counts ranged from 4.2 × 105 CFU/ml to 2.97 × 106 CFU/ml and 5.0 × 104 CFU/ml to 2.45 x 106 CFU/ml, respectively. The isolated bacteria and percentage of occurrence include Bacillus cereus (22%), Enterobacter aerogenes (18%), Staphylococcus aureus (16%), Proteus vulgaris (14%), Escherichia coli (14%), Bacillus licheniformis (12%) and Klebsiella aerogenes (4%). The mineral value ranged as follow; iron (21.30mg/L - 25.60mg/L), zinc (1.80mg/L - 5.60mg/L), copper (1.00mg/L - 2.60mg/L), chromium (0.50mg/L - 1.30mg/L), candium (0.20mg/L - 1.30mg/L), nickel (0.20mg/L - 0.80mg/L), lead (0.05mg/L-0.30mg/L), cobalt (0.03mg/L - 0.30mg/L) and in all samples manganese was not detected. The entire organisms isolated exhibited a high level of resistance to most of the antibiotics used. There is an urgent need for awareness to be created about the present situation of the leachate in Erifun, on the need for treatment of the nearby stream and other water sources before they can be used for drinking and other domestic use. In conclusion, a good method of waste disposal is required in those communities to prevent leachate formation, percolation, and runoff into water bodies during the raining season.

Keywords: antibiotic susceptibility, dumpsite, bacteriological analysis, heavy metal

Procedia PDF Downloads 142

Authors: Sakshi Chopra, Harsimarpreet Kaur, Ashima Nehra

Abstract:

Objectives: Malingering is fabricating or exaggerating the symptoms of mental or physical disorders for a variety of secondary gains or motives, which may include financial compensation; avoiding work; getting lighter criminal sentences; or simply to attract attention or sympathy. Malingering is different from somatization disorder and factitious disorder. The prevalence of malingering is unknown and difficult to determine. In an estimated study in forensic population, it can reach up to 17% cases. But the accuracy of such estimates is questionable as successful malingerers are not detected and thus, not included. Methods: The case study of a 58 years old, right handed, graduate, pre-morbidly working in a national company with reported history of stroke leading to head injury; cerebral infarction/facial palsy and dementia. He was referred for disability certification so that his job position can be transferred to his son as he could not work anymore. A series of Neuropsychological tests were administered. Results: With a mental age of < 2.5 years; social adaptive functioning was overall < 20 showing profound Mental Retardation, less than 1 year social age in abilities of self-help, eating, dressing, locomotion, occupation, communication, self-direction, and socialization; severely impaired verbal and performance ability, 96% impairment in Activities of Daily Living, with an indication of very severe depression. With inconsistent and fluctuating medical findings and problem descriptions to different health professionals forming the board for his disability, it was concluded that this patient was malingering. Conclusions: Even though it can be easily defined, malingering can be very challenging to diagnosis. Cases of malingering impose a substantial economic burden on the health care system and false attribution of malingering imposes a substantial burden of suffering on a significant proportion of the patient population. Timely, tactful diagnosis and management can help ease this patient burden on the healthcare system. Malingering can be detected by only trained mental health professionals in the clinical setting.

Keywords: disability, India, malingering, neuropsychological assessment

Procedia PDF Downloads 419

Authors: Jiajun Lu, Yun Ma

Abstract:

As a member of the tertiary industry, tourism is an important driving factor for urban economic development. As a well-known tourist city in China, according to statistics, the added value of tourism and related industries in 2022 will reach 106.326 billion yuan, a year-on-year increase of 1.2%, accounting for 3.7% of the city's GDP. However, the overall tourism development level of Chongqing is seriously unbalanced, and the tourism strength of the main urban area is much higher than that of the southeast Chongqing, northeast Chongqing and the surrounding city tourism area, and the overall tourism strength of the other three regions is relatively balanced. Based on the estimation of tourism development level and the geographic detector method, this paper finds that the important factors affecting the tourism development level of non-main urban areas in Chongqing are A-level tourist attractions. Through GIS geospatial analysis technology and SPSS data correlation research method, the spatial distribution characteristics and influencing factors of A-level tourist attractions in Chongqing were quantitatively analyzed by using data such as geospatial data cloud, relevant documents of Chongqing Municipal Commission of Culture and Tourism Development, planning cloud, and relevant statistical yearbooks. The results show that: (1) The spatial distribution of tourist attractions in non-main urban areas of Chongqing is agglomeration and uneven. (2) The spatial distribution of A-level tourist attractions in non-main urban areas of Chongqing is affected by ecological factors, and the degree of influence is in the order of water factors> topographic factors > green space factors.

Keywords: tourist attractions, geographic detectors, quantitative research, ecological factors, GIS technology, SPSS analysis

Procedia PDF Downloads 15

Authors: Min Woo Park, Jin Do Chung, Kyu Yeol Kim, Byoung Uk Im, Jang Woo Kim, Hae Yeul Ryu

Abstract:

Nine representative species of trees among all the street trees were selected to estimate the absorption amount of carbon dioxide emitted from street trees in Seoul calculating the biomass, amount of carbon saved, and annual absorption amount of carbon dioxide in each of the species. Planting distance of street trees in Seoul was 1,851,180 m, the number of planting lines was 1,287, the number of planted trees was 284,498 and 46 species of trees were planted as of 2013. According to the result of plugging the quantity of species of street trees in Seoul on the absorption amount of each of the species, 120,097 ton of biomass, 60,049.8 ton of amount of carbon saved, and 11,294 t CO2/year of annual absorption amount of carbon dioxide were calculated. Street ratio mentioned on the road statistics in Seoul in 2022 is 23.13%. If the street trees are assumed to be increased in the same rate, the number of street trees in Seoul was calculated to be 294,823. The planting distance was estimated to be 1,918,360 m, and the annual absorption amount of carbon dioxide was measured to be 11,704 t CO2/year. Plans for improving the annual absorption amount of carbon dioxide from street trees were established based on the expected amount of absorption. First of all, it is to improve the annual absorption amount of carbon dioxide by increasing the number of planted street trees after adjusting the planting distance of street trees. If adjusting the current planting distance to 6 m, it was turned out that 12,692.7 t CO2/year was absorbed on an annual basis. Secondly, it is to change the species of trees to tulip trees that represent high absorption rate. If increasing the proportion of tulip trees to 30% up to 2022, the annual absorption rate of carbon dioxide was calculated to be 17804.4 t CO2/year.

Keywords: absorption of carbon dioxide, source of absorbing carbon dioxide, trees in city, improving species

Procedia PDF Downloads 362

Authors: Takhul Bakhtiar

Abstract:

In South Sulawesi Province, there is an active Walanae Fault causing this area to frequently experience earthquakes. This study aims to determine the level of seismicity of the earthquake in order to obtain the potential for earthquakes in the future. The estimation of the potential for earthquakes is then made a scenario model determine the estimated level of shocks as an effort to mitigate earthquake disasters in the region. The method used in this study is the Gutenberg Richter Method through the statistical likelihood approach. This study used earthquake data in the South Sulawesi region in 1972 - 2022. The research location is located at the coordinates of 3.5° – 5.5° South Latitude and 119.5° – 120.5° East Longitude and divided into two segments, namely the northern segment at the coordinates of 3.5° – 4.5° South Latitude and 119,5° – 120,5° East Longitude then the southern segment with coordinates of 4.5° – 5.5° South Latitude and 119,5° – 120.5° East Longitude. This study uses earthquake parameters with a magnitude > 1 and a depth < 50 km. The results of the analysis show that the potential for earthquakes in the next ten years with a magnitude of M = 7 in the northern segment is estimated at 98.81% with an estimated shock level of VI-VII MMI around the cities of Pare-Pare, Barru, Pinrang and Soppeng then IV - V MMI in the cities of Bulukumba, Selayar, Makassar and Gowa. In the southern segment, the potential for earthquakes in the next ten years with a magnitude of M = 7 is estimated at 32.89% with an estimated VI-VII MMI shock level in the cities of Bulukumba, Selayar, Makassar and Gowa, then III-IV MMI around the cities of Pare-Pare, Barru, Pinrang and Soppeng.

Keywords: Gutenberg Richter, likelihood method, seismicity, shakemap and MMI scale

Procedia PDF Downloads 120

Authors: Rakesh Kumar, A. K. Ghosh

Abstract:

The paper presents the modeling of linear and nonlinear longitudinal aerodynamics using real flight data of Hansa-3 aircraft gathered at low and high angles of attack. The Neural-Gauss-Newton (NGN) method has been applied to model the linear and nonlinear longitudinal dynamics and estimate parameters from flight data. Unsteady aerodynamics due to flow separation at high angles of attack near stall has been included in the aerodynamic model using Kirchhoff’s quasi-steady stall model. NGN method is an algorithm that utilizes Feed Forward Neural Network (FFNN) and Gauss-Newton optimization to estimate the parameters and it does not require any a priori postulation of mathematical model or solving of equations of motion. NGN method was validated on real flight data generated at moderate angles of attack before application to the data at high angles of attack. The estimates obtained from compatible flight data using NGN method were validated by comparing with wind tunnel values and the maximum likelihood estimates. Validation was also carried out by comparing the response of measured motion variables with the response generated by using estimates a different control input. Next, NGN method was applied to real flight data generated by executing a well-designed quasi-steady stall maneuver. The results obtained in terms of stall characteristics and aerodynamic parameters were encouraging and reasonably accurate to establish NGN as a method for modeling nonlinear aerodynamics from real flight data at high angles of attack.

Keywords: parameter estimation, NGN method, linear and nonlinear, aerodynamic modeling

Procedia PDF Downloads 445

Authors: Anwaar Ahmed, Muhammad Bilal Khurshid, Samuel Labi

Abstract:

The effect of trucks on the level of service is determined by considering passenger car equivalents (PCE) of trucks. The current version of Highway Capacity Manual (HCM) uses a single PCE value for all tucks combined. However, the composition of truck traffic varies from location to location; therefore a single PCE-value for all trucks may not correctly represent the impact of truck traffic at specific locations. Consequently, present study developed separate PCE values for single-unit and combination trucks to replace the single value provided in the HCM on different freeways. Site specific PCE values, were developed using concept of spatial lagging headways (the distance from the rear bumper of a leading vehicle to the rear bumper of the following vehicle) measured from field traffic data. The study used data from four locations on a single urban freeway and three different rural freeways in Indiana. Three-stage-least-squares (3SLS) regression techniques were used to generate models that predicted lagging headways for passenger cars, single unit trucks (SUT), and combination trucks (CT). The estimated PCE values for single-unit and combination truck for basic urban freeways (level terrain) were: 1.35 and 1.60, respectively. For rural freeways the estimated PCE values for single-unit and combination truck were: 1.30 and 1.45, respectively. As expected, traffic variables such as vehicle flow rates and speed have significant impacts on vehicle headways. Study results revealed that the use of separate PCE values for different truck classes can have significant influence on the LOS estimation.

Keywords: level of service, capacity analysis, lagging headway, trucks

Procedia PDF Downloads 356

Authors: Mehrnoosh Abouzari, Shahrokh Shahraei

Abstract:

With the development of artificial intelligence in the present age, intelligent machines and systems have proven their actual and potential capabilities and are mindful of increasing their presence in various fields of human life in the fields of industry, financial transactions, marketing, manufacturing, service affairs, politics, economics and various branches of the humanities .Therefore, despite the conservatism and prudence of law enforcement, the traces of artificial intelligence can be seen in various areas of law. Including judicial robotics capability estimation, intelligent judicial decision making system, intelligent defender and attorney strategy adjustment, dissemination and regulation of different and scattered laws in each case to achieve judicial coherence and reduce opinion, reduce prolonged hearing and discontent compared to the current legal system with designing rule-based systems, case-based, knowledge-based systems, etc. are efforts to apply AI in law. In this article, we will identify the ways in which AI is applied in its laws and regulations, identify the dominant concerns in this area and outline the relationship between these two areas in order to answer the question of how artificial intelligence can be used in different areas of law and what the implications of this application will be. The authors believe that the use of artificial intelligence in the three areas of legislative, judiciary and executive power can be very effective in governments' decisions and smart governance, and helping to reach smart communities across human and geographical boundaries that humanity's long-held dream of achieving is a global village free of violence and personalization and human error. Therefore, in this article, we are going to analyze the dimensions of how to use artificial intelligence in the three legislative, judicial and executive branches of government in order to realize its application.

Keywords: artificial intelligence, law, intelligent system, judge

Procedia PDF Downloads 119