Search results for: robust estimation

Authors: Mualla McManus, Jenna Luche Thaye

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World Health Organisation International Classification of Disease codes were created to define disease including infections in order to guide and educate diagnosticians. Most infectious diseases such as syphilis are clearly defined by their ICD 10 codes and aid/help to educate the clinicians in syphilis diagnosis and treatment globally. However, current ICD 10 codes for relapsing fever Borreliosis and Lyme disease are less clearly defined and can impede appropriate diagnosis especially if the clinician is not familiar with the symptoms of these infectious diseases. This is despite substantial number of scientific articles published in peer-reviewed journals about relapsing fever and Lyme disease. In the USA there are estimated 380,000 people annually contacting Lyme disease, more cases than breast cancer and 6x HIV/AIDS cases. This represents estimated 0.09% of the USA population. If extrapolated to the global population (7billion), 0.09% equates to 63 million people contracting relapsing fever or Lyme disease. In many regions, the rate of contracting some form of infection from tick bite may be even higher. Without accurate and appropriate diagnostic codes, physicians are impeded in their ability to properly care for their patients, leaving those patients invisible and marginalized within the medical system and to those guiding public policy. This results in great personal hardship, pain, disability, and expense. This unnecessarily burdens health care systems, governments, families, and society as a whole. With accurate diagnostic codes in place, robust data can guide medical and public health research, health policy, track mortality and save health care dollars. Better defined ICD codes are the way forward in educating the diagnosticians about relapsing fever and Lyme diseases.

Keywords: WHO ICD codes, relapsing fever, Lyme diseases, World Health Organisation

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

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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

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Authors: Sani AbdulRahman Bala

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This empirical study delves into the realm of forensic accounting practices within the Nigerian Public Sector, seeking to quantitatively analyze their efficacy in addressing the persistent challenges of fraud and financial irregularities. With a focus on empirical data, this research employs a robust methodology to assess the current state of fraud in the Nigerian Public Sector and evaluate the performance of existing forensic accounting measures. Through quantitative analyses, including statistical models and data-driven insights, the study aims to identify patterns, trends, and correlations associated with fraudulent activities. The research objectives include scrutinizing documented fraud cases, examining the effectiveness of established forensic accounting practices, and proposing data-driven strategies for enhancing fraud detection and prevention. Leveraging quantitative methodologies, the study seeks to measure the impact of technological advancements on forensic accounting accuracy and efficiency. Additionally, the research explores collaborative mechanisms among government agencies, regulatory bodies, and the private sector by quantifying the effects of information sharing on fraud prevention. The empirical findings from this study are expected to provide a nuanced understanding of the challenges and opportunities in combating fraud within the Nigerian Public Sector. The quantitative insights derived from real-world data will contribute to the refinement of forensic accounting strategies, ensuring their effectiveness in addressing the unique complexities of financial irregularities in the public sector. The study's outcomes aim to inform policymakers, practitioners, and stakeholders, fostering evidence-based decision-making and proactive measures for a more resilient and fraud-resistant financial governance system in Nigeria.

Keywords: fraud, financial irregularities, nigerian public sector, quantitative investigation

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Authors: Mustapha Saidu, Bilyaminu Mohammed

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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

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Authors: Sony Baral, Harald Vacik

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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 87

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

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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

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Authors: Elif Tugce Aksun Tumerkan

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Although seafood is an important part of human diet and categorized highly traded food industry internationally, it is remain overlooked generally in the global food security aspect. Food product authentication is the main interest in the aim of both avoids commercial fraud and to consider the risks that might be harmful to human health safety. In recent years, with increasing consumer demand for regarding food content and it's transparency, there are some instrumental analyses emerging for determining food fraud depend on some analytical methodologies such as proteomic and metabolomics. While, fish and seafood consumed as fresh previously, within advanced technology, processed or packaged seafood consumption have increased. After processing or packaging seafood, morphological identification is impossible when some of the external features have been removed. The main fish and seafood quality-related issues are the authentications of seafood contents such as mislabelling products which may be contaminated and replacement partly or completely, by lower quality or cheaper ones. For all mentioned reasons, truthful consistent and easily applicable analytical methods are needed for assurance the correct labelling and verifying of seafood products. DNA-barcoding methods become popular robust that used in taxonomic research for endangered or cryptic species in recent years; they are used for determining food traceability also. In this review, when comparing the other proteomic and metabolic analysis, DNA-based methods are allowing a chance to identification all type of food even as raw, spiced and processed products. This privilege caused by DNA is a comparatively stable molecule than protein and other molecules. Furthermore showing variations in sequence based on different species and founding in all organisms, make DNA-based analysis more preferable. This review was performed to clarify the main advantages of using DNA-barcoding for determining seafood fraud among other techniques.

Keywords: DNA-barcoding, genetic analysis, food fraud, mislabelling, packaged seafood

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

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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

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Authors: Rui Li, Min Wen, Kim Bang Salling

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For the modern railways, maintenance is critical for ensuring safety, train punctuality and overall capacity utilization. The cost of railway maintenance in Europe is high, on average between 30,000 – 100,000 Euros per kilometer per year. In order to reduce such maintenance expenditures, this paper presents a mixed 0-1 linear mathematical model designed to optimize the predictive railway tamping activities for ballast track in the planning horizon of three to four years. The objective function is to minimize the tamping machine actual costs. The approach of the research is using the simple dynamic model for modelling condition-based tamping process and the solution method for finding optimal condition-based tamping schedule. Seven technical and practical aspects are taken into account to schedule tamping: (1) track degradation of the standard deviation of the longitudinal level over time; (2) track geometrical alignment; (3) track quality thresholds based on the train speed limits; (4) the dependency of the track quality recovery on the track quality after tamping operation; (5) Tamping machine operation practices (6) tamping budgets and (7) differentiating the open track from the station sections. A Danish railway track between Odense and Fredericia with 42.6 km of length is applied for a time period of three and four years in the proposed maintenance model. The generated tamping schedule is reasonable and robust. Based on the result from the Danish railway corridor, the total costs can be reduced significantly (50%) than the previous model which is based on optimizing the number of tamping. The different maintenance strategies have been discussed in the paper. The analysis from the results obtained from the model also shows a longer period of predictive tamping planning has more optimal scheduling of maintenance actions than continuous short term preventive maintenance, namely yearly condition-based planning.

Keywords: integer programming, railway tamping, predictive maintenance model, preventive condition-based maintenance

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

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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

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Authors: Marco Naegele, Klaus Stoppel, Thomas Dekorsy

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Passively Q-switched microchip lasers enable the great potential for sophisticated LiDAR systems due to their compact overall system design, excellent beam quality, and scalable pulse energies. However, many near-infrared solid-state lasers show emitting wavelengths > 1000 nm, which are not compatible with state-of-the-art silicon detectors. Here we demonstrate a passively Q-switched microchip laser operating at 914 nm. The microchip laser consists of a 3 mm long Nd:YVO₄ crystal as a gain medium, while Cr⁴⁺:YAG with an initial transmission of 98% is used as a saturable absorber. Quasi-continuous pumping enables single pulse operation, and low duty cycles ensure low overall heat generation and power consumption. Thus, thermally induced instabilities are minimized, and operation without active cooling is possible while ambient temperature changes are compensated by adjustment of the pump laser current only. Single-emitter diode pumping at 808 nm leads to a compact overall system design and robust setup. Utilization of a microchip cavity approach ensures single-longitudinal mode operation with spectral bandwidths in the picometer regime and results in short laser pulses with pulse durations below 10 ns. Beam quality measurements reveal an almost diffraction-limited beam and enable conclusions concerning the thermal lens, which is essential to stabilize the plane-plane resonator. A 7% output coupler transmissivity is used to generate pulses with energies in the microjoule regime and peak powers of more than 600 W. Long-term pulse duration, pulse energy, central wavelength, and spectral bandwidth measurements emphasize the excellent system stability and facilitate the utilization of this laser in the context of a LiDAR system.

Keywords: diode-pumping, LiDAR system, microchip laser, Nd:YVO4 laser, passively Q-switched

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Authors: Suresh Hettiarachchi, Conrad Wasko, Ashish Sharma

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The ever changing and expanding urban landscape increases the stress on urban systems to support and maintain safe and functional living spaces. Flooding presents one of the more serious threats to this safety, putting a larger number of people in harm’s way in congested urban settings. Climate change is adding to this stress by creating a dichotomy in the urban flood response. On the one hand, climate change is causing storms to intensify, resulting in more destructive, rarer floods, while on the other hand, longer dry periods are decreasing the severity of more frequent, less intense floods. This variability is creating a need to be more agile and innovative in how we design for and manage urban flooding. Here, we argue that to cope with this challenge climate change brings, we need to move towards urban flood management through resilience rather than flood prevention. We also argue that dealing with the larger variation in flood response to climate change means that we need to look at flooding from all aspects rather than the single-dimensional focus of flood depths and extents. In essence, we need to rethink how we manage flooding in the urban space. This change in our thought process and approach to flood management requires a practical way to assess and quantify resilience that is built into the urban landscape so that informed decision-making can support the required changes in planning and infrastructure design. Towards that end, we propose a Simple Urban Flood Resilience Index (SUFRI) based on a robust definition of resilience as a tool to assess flood resilience. The application of a simple resilience index such as the SUFRI can provide a practical tool that considers urban flood management in a multi-dimensional way and can present solutions that were not previously considered. When such an index is grounded on a clear and relevant definition of resilience, it can be a reliable and defensible way to assess and assist the process of adapting to the increasing challenges in urban flood management with climate change.

Keywords: urban flood resilience, climate change, flood management, flood modelling

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

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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

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

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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

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Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

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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

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

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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

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Authors: Somaye Khademi, Elahe Zoghi Hoseini, Mostafa Norouzi

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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

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

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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

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

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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

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

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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

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Authors: Mengjie Qu, Yi Wang, Jiawei Ding, Siyu Chen, Yanan Di

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Marine ecosystem is facing intensified multiple stresses caused by environmental contaminants from human activities. Xenobiotics, such as benzo(α)pyrene (BaP) have been discharged into marine environment and cause hazardous impacts on both marine organisms and human beings. As a filter-feeder, marine mussels, Mytilus spp., has been extensively used to monitor the marine environment. However, their genomic alterations induced by such xenobiotics are still kept unknown. In the present study, gills, as the first defense barrier in mussels, were selected to evaluate the genetic instability alterations induced by the exposure to BaP both in vivo and in vitro. Both random amplified polymorphic DNA (RAPD) assay and comet assay were applied as the rapid tools to assess the environmental stresses due to their low money- and time-consumption. All mussels were identified to be the single species of Mytilus coruscus before used in BaP exposure at the concentration of 56 μg/l for 1 & 3 days (in vivo exposure) or 1 & 3 hours (in vitro). Both RAPD and comet assay results were showed significantly increased genomic instability with time-specific altering pattern. After the recovery period in 'in vivo' exposure, the genomic status was as same as control condition. However, the relative higher genomic instabilities were still observed in gill cells after the recovery from in vitro exposure condition. Different repair mechanisms or signaling pathway might be involved in the isolated gill cells in the comparison with intact tissues. The study provides the robust and rapid techniques to exam the genomic stability in marine organisms in response to marine environmental changes and provide basic information for further mechanism research in stress responses in marine organisms.

Keywords: genotoxic impacts, in vivo/vitro exposure, marine mussels, RAPD and comet assay

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

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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

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Authors: H. Khanfari, M. Johari Fard

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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)

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Authors: Komal Rathore, Aydin Sunol, Gita Iranipour, Luke Mulford

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Advanced wastewater treatment plants have complex biological kinetics, time variant influent flow rates and long processing times. Due to these factors, the modeling and operational control of advanced wastewater treatment plants become complicated. However, development of a robust model for advanced wastewater treatment plants has become necessary in order to increase the efficiency of the plants, reduce energy costs and meet the discharge limits set by the government. A dynamic model was designed using the Envirosim (Canada) platform software called BioWin for several wastewater treatment plants in Hillsborough County, Florida. Proper control strategies for various parameters such as mixed liquor suspended solids, recycle activated sludge and waste activated sludge were developed for models to match the plant performance. The models were tuned using both the influent and effluent data from the plant and their laboratories. The plant SCADA was used to predict the influent wastewater rates and concentration profiles as a function of time. The kinetic parameters were tuned based on sensitivity analysis and trial and error methods. The dynamic models were validated by using experimental data for influent and effluent parameters. The dissolved oxygen measurements were taken to validate the model by coupling them with Computational Fluid Dynamics (CFD) models. The Biowin models were able to exactly mimic the plant performance and predict effluent behavior for extended periods. The models are useful for plant engineers and operators as they can take decisions beforehand by predicting the plant performance with the use of BioWin models. One of the important findings from the model was the effects of recycle and wastage ratios on the mixed liquor suspended solids. The model was also useful in determining the significant kinetic parameters for biological wastewater treatment systems.

Keywords: BioWin, kinetic modeling, flowsheet simulation, dynamic modeling

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Authors: Sylvester S. Horvey, Jones Mensah

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The growing complexities and dynamics in the business environment have led to a new approach to risk management, known as enterprise risk management (ERM). ERM is a system and an approach to managing the risks of an organization in an integrated manner to achieve the corporate goals and strategic objectives. Regardless of the diversities in the business environment, ERM has become an essential factor in managing individual and business risks because ERM is believed to enhance shareholder value and firm growth. Despite the growing number of literature on ERM, the question about what factors drives ERM remains limited. This study provides a comprehensive literature review of the main factors that contribute to ERM implementation. Google Scholar was the leading search engine used to identify empirical literature, and the review spanned between 2000 and 2020. Articles published in Scimago journal ranking and Scopus were examined. Thirteen firm characteristics and sixteen articles were considered for the empirical review. Most empirical studies agreed that firm size, institutional ownership, industry type, auditor type, industrial diversification, earnings volatility, stock price volatility, and internal auditor had a positive relationship with ERM adoption, whereas firm size, institutional ownership, auditor type, and type of industry were mostly seen be statistically significant. Other factors such as financial leverage, profitability, asset opacity, international diversification, and firm complexity revealed an inconclusive result. The growing literature on ERM is not without limitations; hence, this study suggests that further research should examine ERM determinants within a new geographical context while considering a new and robust way of measuring ERM rather than relying on a simple proxy (dummy) for ERM measurement. Other firm characteristics such as organizational culture and context, corporate scandals and losses, and governance could be considered determinants of ERM adoption.

Keywords: enterprise risk management, determinants, ERM adoption, literature review

Procedia PDF Downloads 167

Authors: Aghaei Amirkhizi Navideh, Sadjadi Soodeh Sadat, Moghaddam Banaem Leila, Athari Allaf Mitra, Johari Daha Fariba

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Dendrimers are good candidates for preparing metal nanoparticles because they can structurally and chemically well-defined templates and robust stabilizers. Poly amidoamine (PAMAM) dendrimer-based multifunctional cancer therapeutic conjugates have been designed and synthesized in pharmaceutical industry. In addition, encapsulated nanoparticle surfaces are accessible to substrates so that catalytic reactions can be carried out. For preparation of dendimer-metal nanocomposite, a dendrimer solution containing an average of 55 Yb+3 ions per dendrimer was prepared. Prior to reduction, the pH of this solution was adjusted to 7.5 using NaOH. NaBH4 was used to reduce the dendrimer-encapsulated Yb+3 to the zerovalent metal. The pH of the resulting solution was then adjusted to 3, using HClO4, to decompose excess BH4-. The UV-Vis absorption spectra of the mixture were recorded to ensure the formation of Yb-G5-NH2 complex. High-resolution electron microscopy (HRTEM) and size distribution results provide additional information about dendimer-metal nanocomposite shape, size, and size distribution of the particles. The resulting mixture was irradiated in Tehran Research Reactor 2h and neutron fluxes were 3×1011 n/cm2.Sec and the specific activity was 7MBq. Radiochemical and chemical and radionuclide quality control testes were carried. Gamma Spectroscopy and High-performance Liquid Chromatography HPLC, Thin-Layer Chromatography TLC were recorded. The injection of resulting solution to solid tumor in mice shows that it could be resized the tumor. The studies about solid tumors and nano composites show that ytterbium encapsulated-dendrimer radiopharmaceutical could be introduced as a new therapeutic for the treatment of solid tumors.

Keywords: nano-radio pharmaceutical, ytterbium, PAMAM, dendrimers

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Authors: Richard O’Riordan, Saritha Unnikrishnan

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Autonomous Vehicles (AVs) are incorporating an increasing number of ADAS features, including automated lane-keeping systems. In recent years, many research papers into lane detection algorithms have been published, varying from computer vision techniques to deep learning methods. The transition from lower levels of autonomy defined in the SAE framework and the progression to higher autonomy levels requires increasingly complex models and algorithms that must be highly reliable in their operation and functionality capacities. Furthermore, these algorithms have no room for error when operating at high levels of autonomy. Although the current research details existing computer vision and deep learning algorithms and their methodologies and individual results, the research also details challenges faced by the algorithms and the resources needed to operate, along with shortcomings experienced during their detection of lanes in certain weather and lighting conditions. This paper will explore these shortcomings and attempt to implement a lane detection algorithm that could be used to achieve improvements in AV lane detection systems. This paper uses a pre-trained LaneNet model to detect lane or non-lane pixels using binary segmentation as the base detection method using an existing dataset BDD100k followed by a custom dataset generated locally. The selected roads will be modern well-laid roads with up-to-date infrastructure and lane markings, while the second road network will be an older road with infrastructure and lane markings reflecting the road network's age. The performance of the proposed method will be evaluated on the custom dataset to compare its performance to the BDD100k dataset. In summary, this paper will use Transfer Learning to provide a fast and robust lane detection algorithm that can handle various road conditions and provide accurate lane detection.

Keywords: ADAS, autonomous vehicles, deep learning, LaneNet, lane detection

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Authors: Adebowale T. Odeyemi, Oluwafemi A. Ajenifuja

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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

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Authors: Ayman M. Mansour, Bilal Hawashin, Hesham Alsalem

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Faster delivery of laboratory test results is one of the most noticeable signs of good laboratory service and is often used as a key performance indicator of laboratory performance. Despite the availability of technology, the delivery time of clinical laboratory test results continues to be a cause of customer dissatisfaction which makes patients feel frustrated and they became careless to get their laboratory test results. The Medical Clinical Laboratory test results are highly sensitive and could harm patients especially with the severe case if they deliver in wrong time. Such results affect the treatment done by physicians if arrived at correct time efforts should, therefore, be made to ensure faster delivery of lab test results by utilizing new trusted, Robust and fast system. In this paper, we proposed a distributed Multi-Agent System to enhance and faster the process of laboratory test results delivery using SMS. The developed system relies on SMS messages because of the wide availability of GSM network comparing to the other network. The software provides the capability of knowledge sharing between different units and different laboratory medical centers. The system was built using java programming. To implement the proposed system we had many possible techniques. One of these is to use the peer-to-peer (P2P) model, where all the peers are treated equally and the service is distributed among all the peers of the network. However, for the pure P2P model, it is difficult to maintain the coherence of the network, discover new peers and ensure security. Also, security is a quite important issue since each node is allowed to join the network without any control mechanism. We thus take the hybrid P2P model, a model between the Client/Server model and the pure P2P model using GSM technology through SMS messages. This model satisfies our need. A GUI has been developed to provide the laboratory staff with the simple and easy way to interact with the system. This system provides quick response rate and the decision is faster than the manual methods. This will save patients life.

Keywords: multi-agent system, delivery process, GSM technology, clinical laboratory results

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

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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 355