Search results for: emission factors
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11537

Search results for: emission factors

11297 Internal and External Factors Affecting Teachers’ Adoption of Formative Assessment to Support Learning

Authors: Kemal Izci

Abstract:

Assessment forms an important part of instruction. Assessment that aims to support learning is known as formative assessment and it contributes student’s learning gain and motivation. However, teachers rarely use assessment formatively to aid their students’ learning. Thus, reviewing the factors that limit or support teachers’ practices of formative assessment will be crucial for guiding educators to support prospective teachers in using formative assessment and also eliminate limiting factors to let practicing teachers to engage in formative assessment practices during their instruction. The study, by using teacher’s change environment framework, reviews literature on formative assessment and presents a tentative model that illustrates the factors impacting teachers’ adoption of formative assessment in their teaching. The results showed that there are four main factors consisting personal, contextual, resource-related and external factors that influence teachers’ practices of formative assessment.

Keywords: assessment practices, formative assessment, teacher education, factors for use of formative assessment

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11296 Post Growth Annealing Effect on Deep Level Emission and Raman Spectra of Hydrothermally Grown ZnO Nanorods Assisted by KMnO4

Authors: Ashish Kumar, Tejendra Dixit, I. A. Palani, Vipul Singh

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Zinc oxide, with its interesting properties such as large band gap (3.37eV), high exciton binding energy (60 meV) and intense UV absorption has been studied in literature for various applications viz. optoelectronics, biosensors, UV-photodetectors etc. The performance of ZnO devices is highly influenced by morphologies, size, crystallinity of the ZnO active layer and processing conditions. Recently, our group has shown the influence of the in situ addition of KMnO4 in the precursor solution during the hydrothermal growth of ZnO nanorods (NRs) on their near band edge (NBE) emission. In this paper, we have investigated the effect of post-growth annealing on the variations in NBE and deep level (DL) emissions of as grown ZnO nanorods. These observed results have been explained on the basis of X-ray Diffraction (XRD) and Raman spectroscopic analysis, which clearly show that improved crystalinity and quantum confinement in ZnO nanorods.

Keywords: ZnO, nanorods, hydrothermal, KMnO4

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11295 Computer Modeling and Plant-Wide Dynamic Simulation for Industrial Flare Minimization

Authors: Sujing Wang, Song Wang, Jian Zhang, Qiang Xu

Abstract:

Flaring emissions during abnormal operating conditions such as plant start-ups, shut-downs, and upsets in chemical process industries (CPI) are usually significant. Flare minimization can help to save raw material and energy for CPI plants, and to improve local environmental sustainability. In this paper, a systematic methodology based on plant-wide dynamic simulation is presented for CPI plant flare minimizations under abnormal operating conditions. Since off-specification emission sources are inevitable during abnormal operating conditions, to significantly reduce flaring emission in a CPI plant, they must be either recycled to the upstream process for online reuse, or stored somewhere temporarily for future reprocessing, when the CPI plant manufacturing returns to stable operation. Thus, the off-spec products could be reused instead of being flared. This can be achieved through the identification of viable design and operational strategies during normal and abnormal operations through plant-wide dynamic scheduling, simulation, and optimization. The proposed study includes three stages of simulation works: (i) developing and validating a steady-state model of a CPI plant; (ii) transiting the obtained steady-state plant model to the dynamic modeling environment; and refining and validating the plant dynamic model; and (iii) developing flare minimization strategies for abnormal operating conditions of a CPI plant via a validated plant-wide dynamic model. This cost-effective methodology has two main merits: (i) employing large-scale dynamic modeling and simulations for industrial flare minimization, which involves various unit models for modeling hundreds of CPI plant facilities; (ii) dealing with critical abnormal operating conditions of CPI plants such as plant start-up and shut-down. Two virtual case studies on flare minimizations for start-up operation (over 50% of emission savings) and shut-down operation (over 70% of emission savings) of an ethylene plant have been employed to demonstrate the efficacy of the proposed study.

Keywords: flare minimization, large-scale modeling and simulation, plant shut-down, plant start-up

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11294 Evaluating Emission Reduction Due to a Proposed Light Rail Service: A Micro-Level Analysis

Authors: Saeid Eshghi, Neeraj Saxena, Abdulmajeed Alsultan

Abstract:

Carbon dioxide (CO2) alongside other gas emissions in the atmosphere cause a greenhouse effect, resulting in an increase of the average temperature of the planet. Transportation vehicles are among the main contributors of CO2 emission. Stationary vehicles with initiated motors produce more emissions than mobile ones. Intersections with traffic lights that force the vehicles to become stationary for a period of time produce more CO2 pollution than other parts of the road. This paper focuses on analyzing the CO2 produced by the traffic flow at Anzac Parade Road - Barker Street intersection in Sydney, Australia, before and after the implementation of Light rail transport (LRT). The data are gathered during the construction phase of the LRT by collecting the number of vehicles on each path of the intersection for 15 minutes during the evening rush hour of 1 week (6-7 pm, July 04-31, 2018) and then multiplied by 4 to calculate the flow of vehicles in 1 hour. For analyzing the data, the microscopic simulation software “VISSIM” has been used. Through the analysis, the traffic flow was processed in three stages: before and after implementation of light rail train, and one during the construction phase. Finally, the traffic results were input into another software called “EnViVer”, to calculate the amount of CO2 during 1 h. The results showed that after the implementation of the light rail, CO2 will drop by a minimum of 13%. This finding provides an evidence that light rail is a sustainable mode of transport.

Keywords: carbon dioxide, emission modeling, light rail, microscopic model, traffic flow

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11293 Factors Affecting Human Resource Managers Information Behavior

Authors: Sevim Oztimurlenk

Abstract:

This is an exploratory study on the information behavior of human resource managers. This study is conducted by using a questionnaire survey and an interview. The data is gathered from 140 HR managers who are members of the People Management Association of Turkey (PERYÖN), and the 15 interviewees were chosen among those 140 survey participants randomly. The goal of this exploratory study is to investigate the impact of some factors (i.e., gender, age, work experience, number of employee reporting, company size, industry type) on HR managers’ information behavior. More specifically, it examines if there is a relationship between those factors and HR managers’ information behavior in terms of what kind of information sources they consult and reviews and whom they prefer to communicate with for information sharing. It also aims to find out additional factors influencing the information behavior of HR managers. The results of the study show that age and industry type are the two factors affecting the information behavior of HR managers, among other factors investigated in terms of information source, use and share. Moreover, personality, technology, education, organizational culture, and culture are the top five factors among the 24 additional factors suggested by HR managers who participated in this study.

Keywords: information behavior, information use, information source, information share, human resource managers

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11292 Assessment of Energy Efficiency and Life Cycle Greenhouse Gas Emission of Wheat Production on Conservation Agriculture to Achieve Soil Carbon Footprint in Bangladesh

Authors: MD Mashiur Rahman, Muhammad Arshadul Haque

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Emerging conservation agriculture (CA) is an option for improving soil health and maintaining environmental sustainability for intensive agriculture, especially in the tropical climate. Three years lengthy research experiment was performed in arid climate from 2018 to 2020 at research field of Bangladesh Agricultural Research Station (RARS)F, Jamalpur (soil texture belongs to Agro-Ecological Zone (AEZ)-8/9, 24˚56'11''N latitude and 89˚55'54''E longitude and an altitude of 16.46m) to evaluate the effect of CA approaches on energy use efficiency and a streamlined life cycle greenhouse gas (GHG) emission of wheat production. For this, the conservation tillage practices (strip tillage (ST) and minimum tillage (MT)) were adopted in comparison to the conventional farmers' tillage (CT), with retained a fixed level (30 cm) of residue retention. This study examined the relationship between energy consumption and life cycle greenhouse gas (GHG) emission of wheat cultivation in Jamalpur region of Bangladesh. Standard energy equivalents megajoules (MJ) were used to measure energy from different inputs and output, similarly, the global warming potential values for the 100-year timescale and a standard unit kilogram of carbon dioxide equivalent (kg CO₂eq) was used to estimate direct and indirect GHG emissions from the use of on-farm and off-farm inputs. Farm efficiency analysis tool (FEAT) was used to analyze GHG emission and its intensity. A non-parametric data envelopment (DEA) analysis was used to estimate the optimum energy requirement of wheat production. The results showed that the treatment combination having MT with optimum energy inputs is the best suit for cost-effective, sustainable CA practice in wheat cultivation without compromising with the yield during the dry season. A total of 22045.86 MJ ha⁻¹, 22158.82 MJ ha⁻¹, and 23656.63 MJ ha⁻¹ input energy for the practice of ST, MT, and CT was used in wheat production, and output energy was calculated as 158657.40 MJ ha⁻¹, 162070.55 MJ ha⁻¹, and 149501.58 MJ ha⁻¹, respectively; where energy use efficiency/net energy ratio was found to be 7.20, 7.31 and 6.32. Among these, MT is the most effective practice option taken into account in the wheat production process. The optimum energy requirement was found to be 18236.71 MJ ha⁻¹ demonstrating for the practice of MT that if recommendations are followed, 18.7% of input energy can be saved. The total greenhouse gas (GHG) emission was calculated to be 2288 kgCO₂eq ha⁻¹, 2293 kgCO₂eq ha⁻¹ and 2331 kgCO₂eq ha⁻¹, where GHG intensity is the ratio of kg CO₂eq emission per MJ of output energy produced was estimated to be 0.014 kg CO₂/MJ, 0.014 kg CO₂/MJ and 0.015 kg CO₂/MJ in wheat production. Therefore, CA approaches ST practice with 30 cm residue retention was the most effective GHG mitigation option when the net life cycle GHG emission was considered in wheat production in the silt clay loam soil of Bangladesh. In conclusion, the CA approaches being implemented for wheat production involving MT practice have the potential to mitigate global warming potential in Bangladesh to achieve soil carbon footprint, where the life cycle assessment approach needs to be applied to a more diverse range of wheat-based cropping systems.

Keywords: conservation agriculture and tillage, energy use efficiency, life cycle GHG, Bangladesh

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11291 Assessment of Exhaust Emissions and Fuel Consumption from Means of Transport in Agriculture

Authors: Jerzy Merkisz, Piotr Lijewski, Pawel Fuc, Maciej Siedlecki, Andrzej Ziolkowski, Sylwester Weymann

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The paper discusses the problem of load transport using farm tractors and road tractor units. This type of carriage of goods is often done with farm vehicles. The tests were performed with the PEMS equipment (Portable Emission Measurement System) under actual traffic conditions. The vehicles carried a load of 20000 kg. This research method is one of the most desired because it provides reliable information on the actual vehicle emissions and fuel consumption (carbon balance method). For the tests, a route was selected that simulated a trip from a small town to a food-processing facility located in a city. The analysis of the obtained results gave a clear answer as to what vehicles need to be used for the carriage of this type of cargo in terms of exhaust emissions and fuel consumption.

Keywords: emission, transport, fuel consumption, PEMS

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11290 Marine Fishing and Climate Change: A China’s Perspective on Fisheries Economic Development and Greenhouse Gas Emissions

Authors: Yidan Xu, Pim Martens, Thomas Krafft

Abstract:

Marine fishing, an energy-intensive activity, directly emits greenhouse gases through fuel combustion, making it a significant contributor to oceanic greenhouse gas (GHG) emissions and worsening climate change. China is the world’s second-largest economy and the top emitter of GHG emissions, and it carries a significant energy conservation and emission reduction burden. However, the increasing GHG emissions from marine fishing is an easily overlooked but essential issue in China. This study offers a diverse perspective by integrating the concepts of total carbon emissions, carbon intensity, and per capita carbon emissions as indicators into calculation and discussion. To better understand the GHG emissions-Gross marine fishery product (GFP) relationship and influencing factors in Chinese marine fishing, the relationship between GHG emissions and economic development in marine fishing, a comprehensive framework is developed by combining the environmental Kuznets curve, the Tapio elasticity index, and the decomposition model. Results indicated that (1) The GHG emissions increased from 16.479 to 18.601 million tons in 2001-2020, in which trawlers and gillnetter are the main source in fishing operation. (2) Total carbon emissions (TC) and CI presented the same decline as GHG emissions, while per capita carbon emissions (PC) displayed an uptrend. (32) GHG emissions and gross marine fishery product (GFP) presented an inverted U-shaped relationship in China; the turning point came in the 13th Five-year Plan period (2016-2020). (43) Most provinces strongly decoupled GFP and CI. Still, PC and TC need more effort to decouple. (54) GHG emissions promoted by an industry structure driven, though carbon intensity and industry scale aid in GHG emissions reduced. (5) Compare with TC and PC, CI has been relatively affected by COVID-19 in 2020. The rise in fish and seafood prices during COVID-19 has boosted the GFP.

Keywords: marine fishing economy, greenhouse gas emission, fishery management, green development

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11289 Magnetoelectric Coupling in Hetero-Structured Nano-Composite of BST-BLFM Films

Authors: Navneet Dabra, Jasbir S. HUndal

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Hetero-structured nano-composite thin film of Ba0.5Sr0.5TiO3/Bi0.9La0.1Fe0.9Mn0.1O3 (BST/BLFM) has been prepared by chemical solution deposition method with various BST to BLFM thickness ratios. These films have been deposited over on p-type Si (100) substrate. These samples exhibited low leakage current, large grain size and uniform distribution of particles. The maximum remanent polarization (Pr) was achieved in the heterostructures with thickness ratio of 2.65. The dielectric tenability, electric hysteresis (P-E), ME coupling coefficient, magnetic hysteresis (M-H), ferromagnetic exchange interaction and magnetoelectric measurements were carried out. Field Emission Scanning Electron Microscopy has been employed to investigate the surface morphology of these heterostructured nano-composite films.

Keywords: magnetoelectric, Schottky emission, interface coupling, dielectric tenability, electric hysteresis (P-E), ME coupling coefficient, magnetic hysteresis (M-H)

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11288 Assessing Readiness Model for Business Intelligence Implementation in Organization

Authors: Abdul Razak Rahmat, Azizah Ahmad, Azman Ta’aa

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The deployment of Business Intelligence (BI) for organization at the beginning phase is very crucial. Results from the previous studies found that more than half of the BI project fails to meet the objective even though a lot money are spent. Based on that problem, the readiness level of BI for the organization is important to identify in order to reduce the risk before the actual BI project is implemented. In this paper, rigorous literature review on the aspect success factors such as Critical Success Factors (CSFs), Readiness Factors (RFs), Success Factors (SFs), are discussed by different authors. The paper also adopted a few models from previous study as a guide for the assessment of BI readiness. The expected finding from this research is the Business Intelligent Readiness Model (BiRM) as a guild before implement the BI system.

Keywords: business intelligence readiness model, business intelligence for higher learning, BI readiness factors, BI critical success factors(CSF)

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11287 Modeling Factors Affecting Fertility Transition in Africa: Case of Kenya

Authors: Dennis Okora Amima Ondieki

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Fertility transition has been identified to be affected by numerous factors. This research aimed to investigate the most real factors affecting fertility transition in Kenya. These factors were firstly extracted from the literature convened into demographic features, social, and economic features, social-cultural features, reproductive features and modernization features. All these factors had 23 factors identified for this study. The data for this study was from the Kenya Demographic and Health Surveys (KDHS) conducted in 1999-2003 and 2003-2008/9. The data was continuous, and it involved the mean birth order for the ten periods. Principal component analysis (PCA) was utilized using 23 factors. Principal component analysis conveyed religion, region, education and marital status as the real factors. PC scores were calculated for every point. The identified principal components were utilized as forecasters in the multiple regression model, with the fertility level as the response variable. The four components were found to be affecting fertility transition differently. It was found that fertility is affected positively by factors of region and marital and negatively by factors of religion and education. These four factors can be considered in the planning policy in Kenya and Africa at large.

Keywords: fertility transition, principal component analysis, Kenya demographic health survey, birth order

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11286 The Carbon Emission Seesaw Effect

Authors: Adel Elomri

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The notion of carbon footprinting is ever more widespread as companies are becoming increasingly aware that tackling carbon emissions and being seen to do so is a key issue to face governments, customers and other stakeholders’ pressures towards delivering environmentally friendly services and activities. In this contest, many firms are taking self-initiatives to reduce their own carbon emissions while some other are constrained to obey to different regulations/policies (e.g. carbon tax or carbon Cap) designed by higher authorities targeting a low-carbon environment. Using buyer-vendor framework, this paper provides some insights on how effective are these self-initiatives and regulatory policies when only concerning firms at the individual level and not the whole supply chain they are part of. We show that when firms individually engage in reducing their direct carbon emissions either under self-initiatives or regulatory policy, an opposite expected outcome resulting in a higher global supply chain emission can occur. This effect is referred to as the carbon seesaw effect. Moreover, we show that coordinating or centralizing the supply chain -contrary to what one may think at first- is not often the appropriate solution to get rid of this effect.

Keywords: carbon emissions, supply chain coordination, EOQ, sustainable operations

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11285 Determinants of Smallholder Farmers' Intention to Adopt Jatropha as Raw Material for Biodiesel Production: A Proposed Model for Nigeria

Authors: Abdulsalam Mas’ud

Abstract:

Though Nigerian Biofuel Policy and Incentive was introduced in 2007, however, little if any is known about the impact of such policy for biodiesel development in Nigeria. It can be argued that lack of raw materials is one of the important factors that hinder the proper implementation of the policy. In line with this argument, this study aims to explore the determinants of smallholder farmers’ intention to adopt Jatropha as raw materials for biodiesel development in northern Nigeria, with Jigawa State as area of study. The determinants proposed for investigation covers personal factors, physical factors, institutional factors, economic factors, risk and uncertainty factors as well as social factors. The validation of the proposed model will have the implication of guiding policymakers towards enhancement of farmers’ participation in the Jatropha project for biodiesel raw materials production. The eventual byproducts of the proposed model validation and implementation will be employment generation, poverty reduction, combating dessert encroachment, economic diversification to renewable energy sources and electricity generation.

Keywords: adoption, biodiesel, factors, jatropha

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11284 Transformation of Positron Emission Tomography Raw Data into Images for Classification Using Convolutional Neural Network

Authors: Paweł Konieczka, Lech Raczyński, Wojciech Wiślicki, Oleksandr Fedoruk, Konrad Klimaszewski, Przemysław Kopka, Wojciech Krzemień, Roman Shopa, Jakub Baran, Aurélien Coussat, Neha Chug, Catalina Curceanu, Eryk Czerwiński, Meysam Dadgar, Kamil Dulski, Aleksander Gajos, Beatrix C. Hiesmayr, Krzysztof Kacprzak, łukasz Kapłon, Grzegorz Korcyl, Tomasz Kozik, Deepak Kumar, Szymon Niedźwiecki, Dominik Panek, Szymon Parzych, Elena Pérez Del Río, Sushil Sharma, Shivani Shivani, Magdalena Skurzok, Ewa łucja Stępień, Faranak Tayefi, Paweł Moskal

Abstract:

This paper develops the transformation of non-image data into 2-dimensional matrices, as a preparation stage for classification based on convolutional neural networks (CNNs). In positron emission tomography (PET) studies, CNN may be applied directly to the reconstructed distribution of radioactive tracers injected into the patient's body, as a pattern recognition tool. Nonetheless, much PET data still exists in non-image format and this fact opens a question on whether they can be used for training CNN. In this contribution, the main focus of this paper is the problem of processing vectors with a small number of features in comparison to the number of pixels in the output images. The proposed methodology was applied to the classification of PET coincidence events.

Keywords: convolutional neural network, kernel principal component analysis, medical imaging, positron emission tomography

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11283 Various Factors Affecting Students Performances In A Saudi Medical School

Authors: Raneem O. Salem, Najwa Al-Mously, Nihal Mohamed Nabil, Abdulmohsen H. Al-Zalabani, Abeer F. Al-Dhawi, Nasser Al-Hamdan

Abstract:

Objective: There are various demographic and educational factors that affect the academic performance of undergraduate medical students. The objective of this study is to identify these factors and correlate them to the GPA of the students. Methods: A cross-sectional study design utilizing grade point averages (GPAs) of two cohorts of students in both levels of the pre-clinical phase. In addition, self-administered questionnaire was used to evaluate the effect of these factors on students with poor and good cumulative GPA. Results: Among the various factors studied, gender, marital status, and the transportation used to reach the faculty significantly affected academic performance of students. Students with a cumulative GPA of 3.0 or greater significantly differed than those with a GPA of less than 3.0 being higher in female students, in married students, and type of transportation used to reach the college. Factors including age, educational factors, and type of transportation used have shown to create a significant difference in GPA between male and females. Conclusion: Factors such as age, gender, marital status, learning resources, study time, and the transportation used have been shown to significantly affect medical student GPA as a whole batch as well as when they are tested for gender.

Keywords: academic performance, educational factors, learning resources, study time, gender, socio-demographic factors

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11282 Quantitative Elemental Analysis of Cyperus rotundus Medicinal Plant by Particle Induced X-Ray Emission and ICP-MS Techniques

Authors: J. Chandrasekhar Rao, B. G. Naidu, G. J. Naga Raju, P. Sarita

Abstract:

Particle Induced X-ray Emission (PIXE) and Inductively Coupled Plasma Mass Spectroscopy (ICP-MS) techniques have been employed in this work to determine the elements present in the root of Cyperus rotundus medicinal plant used in the treatment of rheumatoid arthritis. The elements V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Rb, and Sr were commonly identified and quantified by both PIXE and ICP-MS whereas the elements Li, Be, Al, As, Se, Ag, Cd, Ba, Tl, Pb and U were determined by ICP-MS and Cl, K, Ca, Ti and Br were determined by PIXE. The regional variation of elemental content has also been studied by analyzing the same plant collected from different geographical locations. Information on the elemental content of the medicinal plant would be helpful in correlating its ability in the treatment of rheumatoid arthritis and also in deciding the dosage of this herbal medicine from the metal toxicity point of view. Principal component analysis and cluster analysis were also applied to the data matrix to understand the correlation among the elements.

Keywords: PIXE, CP-MS, elements, Cyperus rotundus, rheumatoid arthritis

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11281 Key Factors of Success and Deterrent of IT Projects, Case study: Islamic Azad University, Zahedan Branch

Authors: Mohammad Reza Abidi, Zahra Nourouz Pour, Mehdi Moudi

Abstract:

In this research, firstly critical success factors and deterrent factors in implementing projects and also the factors those cause information technology productivity (IT) paradox in Islamic Azad University, Zahedan branch examined. Research method of this paper is descriptive. In fact, the researcher by using survey, proposed useful solutions. In this research, subjects’ responders to questionnaires items were based on Likert scale. In the questionnaire, economic, technical, organizational and cultural factors in the university have been assessed in order to obtain the necessary validity. We used masters and technicians of IT department’s advices to realize reliability and consistency. For the reliability test we used Cronbach’s reliability test and validity has been obtained using SPSS software. Because of the research questions and objectives, t-student test is used for hypothesis testing. Finally we analyze the findings, we offer conclusions and suggestions.

Keywords: IT projects, Islamic Azad University, success factors, deterrent factors

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11280 Reducing Energy Consumption and GHG Emission by Integration of Flare Gas with Fuel Gas Network in Refinery

Authors: N. Tahouni, M. Gholami, M. H. Panjeshahi

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Gas flaring is one of the most GHG emitting sources in the oil and gas industries. It is also a major way for wasting such an energy that could be better utilized and even generates revenue. Minimize flaring is an effective approach for reducing GHG emissions and also conserving energy in flaring systems. Integrating waste and flared gases into the fuel gas networks (FGN) of refineries is an efficient tool. A fuel gas network collects fuel gases from various source streams and mixes them in an optimal manner, and supplies them to different fuel sinks such as furnaces, boilers, turbines, etc. In this article we use fuel gas network model proposed by Hasan et al. as a base model and modify some of its features and add constraints on emission pollution by gas flaring to reduce GHG emissions as possible. Results for a refinery case study showed that integration of flare gas stream with waste and natural gas streams to construct an optimal FGN can significantly reduce total annualized cost and flaring emissions.

Keywords: flaring, fuel gas network, GHG emissions, stream

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11279 Impact of Normative Institutional Factors on Sustainability Reporting

Authors: Lina Dagilienė

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The article explores the impact of normative institutional factors on the development of sustainability reporting. The vast majority of research in the scientific literature focuses on mandatory institutional factors, i.e. how public institutions and market regulators affect sustainability reporting. Meanwhile, there is lack of empirical data for the impact of normative institutional factors. The effect of normative factors in this paper is based on the role of non-governmental organizations (NGO) and institutional theory. The case of Global Compact Local Network in the developing country was examined. The research results revealed that in the absence of regulated factors, companies were not active with regard to social disclosures; they presented non-systemized social information of a descriptive nature. Only 10% of sustainability reports were prepared using the GRI methodology. None of the reports were assured by third parties.

Keywords: institutional theory, normative, sustainability reporting, Global Compact Local Network

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11278 Anemia and Nutritional Status as Dominant Factor of the Event Low Birth Weight in Indonesia: A Systematic Review

Authors: Lisnawati Hutagalung

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Background: Low birth weight (LBW) is one cause of newborn death. Babies with low birth weight tend to have slower cognitive development, growth retardation, more at risk of infectious disease event at risk of death. Objective: Identifying risk factors and dominant factors that influence the incidence of LBW in Indonesia. Method: This research used some database of public health such as Google Scholar, UGM journals, UI journals and UNAND journals in 2012-2015. Data were filtered using keywords ‘Risk Factors’ AND ‘Cause LBW’ with amounts 2757 study. The filtrate obtained 5 public health research that meets the criteria. Results: Risk factors associated with LBW, among other environment factors (exposure to cigarette smoke and residence), social demographics (age and socio-economic) and maternal factors (anemia, placental abnormal, nutritional status of mothers, examinations antenatal, preeclampsia, parity, and complications in pregnancy). Anemia and nutritional status become the dominant factor affecting LBW. Conclusions: The risk factors that affect LBW, most commonly found in the maternal factors. The dominant factors are a big effect on LBW is anemia and nutritional status of the mother during pregnancy.

Keywords: low birth weight, anemia, nutritional status, the dominant factor

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11277 Study on NOₓ Emission Characteristics of Internal Gas Recirculation Technique

Authors: DaeHae Kim, MinJun Kwon, Sewon Kim

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This study is aimed to develop ultra-low NOₓ burner using the internal recirculation of flue gas inside the combustion chamber that utilizes the momentum of intake fuel and air. Detailed experimental investigations are carried out to study these fluid dynamic effects on the emission characteristics of newly developed burner in industrial steam boiler system. Experimental parameters are distance of Venturi tube from burner, Coanda nozzle gap distance, and air sleeve length at various fuel/air ratio and thermal heat load conditions. The results showed that NOₓ concentration decreases as the distance of Venturi tube from burner increases. The CO concentration values at all operating conditions were negligible. In addition, the increase of the Coanda nozzle gap distance decreased the NOₓ concentration. It is experimentally found out that both fuel injection recirculation and air injection recirculation technique was very effective in reducing NOₓ formation.

Keywords: Coanda effect, combustion, burner, low NOₓ

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11276 Concept to Enhance the Project Success and Promote the Implementation of Success Factors in Infrastructure Projects

Authors: A. Elbaz, K. Spang

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Infrastructure projects are often subjected to delays and cost overruns and mistakenly described as unsuccessful projects. These projects have many peculiarities such as public attention, impact on the environment, subjected to special regulations, etc. They also deal with several stakeholders with different motivations and face unique risks. With this in mind we need to reconsider our approach to manage them, define their success factors and implement these success factors. Infrastructure projects are not only lacking a unified meaning of project success or a definition of success factors, but also a clear method to implement these factors. This paper investigates this gap and introduces a concept to implement success factors in an efficient way, taking into consideration the specific characteristics of infrastructure projects. This concept consists of six enablers such as project organization, project team, project management workflow, contract management, communication and knowledge transfer and project documentations. These enablers allow other success factors to be efficiently implemented in projects. In conclusion, this paper provides project managers as well as company managers with a tool to define and implement success factors efficiently in their projects, along with upgrading their assets for the coming projects. This tool consists of processes and validated checklists to ensure the best use of company resources and knowledge. Due to the special features of infrastructure projects this tool will be tested in the German infrastructure market. However, it is meant to be adaptable to other markets and industries.

Keywords: infrastructure projects, operative success factors, project success, success factors, transportation projects

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11275 Enhanced Near-Infrared Upconversion Emission Based Lateral Flow Immunoassay for Background-Free Detection of Avian Influenza Viruses

Authors: Jaeyoung Kim, Heeju Lee, Huijin Jung, Heesoo Pyo, Seungki Kim, Joonseok Lee

Abstract:

Avian influenza viruses (AIV) are the primary cause of highly contagious respiratory diseases caused by type A influenza viruses of the Orthomyxoviridae family. AIV are categorized on the basis of types of surface glycoproteins such as hemagglutinin and neuraminidase. Certain H5 and H7 subtypes of AIV have evolved to the high pathogenic avian influenza (HPAI) virus, which has caused considerable economic loss to the poultry industry and led to severe public health crisis. Several commercial kits have been developed for on-site detection of AIV. However, the sensitivity of these methods is too low to detect low virus concentrations in clinical samples and opaque stool samples. Here, we introduced a background-free near-infrared (NIR)-to-NIR upconversion nanoparticle-based lateral flow immunoassay (NNLFA) platform to yield a sensor that detects AIV within 20 minutes. Ca²⁺ ion in the shell was used to enhance the NIR-to-NIR upconversion photoluminescence (PL) emission as a heterogeneous dopant without inducing significant changes in the morphology and size of the UCNPs. In a mixture of opaque stool samples and gold nanoparticles (GNPs), which are components of commercial AIV LFA, the background signal of the stool samples mask the absorption peak of GNPs. However, UCNPs dispersed in the stool samples still show strong emission centered at 800 nm when excited at 980 nm, which enables the NNLFA platform to detect 10-times lower viral load than a commercial GNP-based AIV LFA. The detection limit of NNLFA for low pathogenic avian influenza (LPAI) H5N2 and HPAI H5N6 viruses was 10² EID₅₀/mL and 10³.⁵ EID₅₀/mL, respectively. Moreover, when opaque brown-colored samples were used as the target analytes, strong NIR emission signal from the test line in NNLFA confirmed the presence of AIV, whereas commercial AIV LFA detected AIV with difficulty. Therefore, we propose that this rapid and background-free NNLFA platform has the potential of detecting AIV in the field, which could effectively prevent the spread of these viruses at an early stage.

Keywords: avian influenza viruses, lateral flow immunoassay on-site detection, upconversion nanoparticles

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11274 Electron-Ion Recombination for Photoionized and Collisionally Ionized Plasmas

Authors: Shahin A. Abdel-Naby, Asad T. Hassan

Abstract:

Astrophysical plasma environments can be classified into collisionally ionized (CP) and photoionizedplasmas (PP). In the PP, ionization is caused by an external radiation field, while it is caused by electron collision in the CP. Accurate and reliable laboratory astrophysical data for electron-ion recombination is needed for plasma modeling for low and high-temperatures. Dielectronic recombination (DR) is the dominant recombination process for the CP for most of the ions. When a free electron is captured by an ion with simultaneous excitation of its core, a doubly-exited intermediate state may be formed. The doubly excited state relaxes either by electron emission (autoionization) or by radiative decay (photon emission). DR process takes place when the relaxation occurs to a bound state by a photon emission. DR calculations at low-temperatures are problematic and challenging since small uncertaintiesin the low-energy DR resonance positions can produce huge uncertainties in DR rate coefficients.DR rate coefficients for N²⁺ and O³⁺ ions are calculated using state-of-the-art multi-configurationBreit-Pauli atomic structure AUTOSTRUCTURE collisional package within the generalized collisional-radiative framework. Level-resolved calculations for RR and DR rate coefficients from the ground and metastable initial states are produced in an intermediate coupling scheme associated withn = 0 and n = 1 core-excitations. DR cross sections for these ions are convoluted with the experimental electron-cooler temperatures to produce DR rate coefficients. Good agreements are foundbetween these rate coefficients and theexperimental measurements performed at CRYRING heavy-ionstorage ring for both ions.

Keywords: atomic data, atomic process, electron-ion collision, plasmas

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11273 Prediction of Bubbly Plume Characteristics Using the Self-Similarity Model

Authors: Li Chen, Alex Skvortsov, Chris Norwood

Abstract:

Gas releasing into water can be found in for many industrial situations. This process results in the formation of bubbles and acoustic emission which depends upon the bubble characteristics. If the bubble creation rates (bubble volume flow rate) are of interest, an inverse method has to be used based on the measurement of acoustic emission. However, there will be sound attenuation through the bubbly plume which will influence the measurement and should be taken into consideration in the model. The sound transmission through the bubbly plume depends on the characteristics of the bubbly plume, such as the shape and the bubble distributions. In this study, the bubbly plume shape is modelled using a self-similarity model, which has been normally applied for a single phase buoyant plume. The prediction is compared with the experimental data. It has been found the model can be applied to a buoyant plume of gas-liquid mixture. The influence of the gas flow rate and discharge nozzle size is studied.

Keywords: bubbly plume, buoyant plume, bubble acoustics, self-similarity model

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11272 Effect of Fuel Injection Discharge Curve and Injection Pressure on Upgrading Power and Combustion Parameters in HD Diesel Engine with CFD Simulation

Authors: Saeed Chamehsara, Seyed Mostafa Mirsalim, Mehdi Tajdari

Abstract:

In this study, the effect of fuel injection discharge curve and injection pressure simultaneously for upgrading power of heavy duty diesel engine by simulation of combustion process in AVL-Fire software are discussed. Hence, the fuel injection discharge curve was changed from semi-triangular to rectangular which is usual in common rail fuel injection system. Injection pressure with respect to amount of injected fuel and nozzle hole diameter are changed. Injection pressure is calculated by an experimental equation which is for heavy duty diesel engines with common rail fuel injection system. Upgrading power for 1000 and 2000 bar injection pressure are discussed. For 1000 bar injection pressure with 188 mg injected fuel and 3 mm nozzle hole diameter in compare with first state which is semi-triangular discharge curve with 139 mg injected fuel and 3 mm nozzle hole diameter, upgrading power is about 19% whereas the special change has not been observed in cylinder pressure. On the other hand, both the NOX emission and the Soot emission decreased about 30% and 6% respectively. Compared with first state, for 2000 bar injection pressure that injected fuel and nozzle diameter are 196 mg and 2.6 mm respectively, upgrading power is about 22% whereas cylinder pressure has been fixed and NOX emission and the Soot emissions are decreased 36% and 20%, respectively.

Keywords: CFD simulation, HD diesel engine, upgrading power, injection pressure, fuel injection discharge curve, combustion process

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11271 A Fluorescent Polymeric Boron Sensor

Authors: Soner Cubuk, Mirgul Kosif, M. Vezir Kahraman, Ece Kok Yetimoglu

Abstract:

Boron is an essential trace element for the completion of the life circle for organisms. Suitable methods for the determination of boron have been proposed, including acid - base titrimetric, inductively coupled plasma emission spectroscopy flame atomic absorption and spectrophotometric. However, the above methods have some disadvantages such as long analysis times, requirement of corrosive media such as concentrated sulphuric acid and multi-step sample preparation requirements and time-consuming procedures. In this study, a selective and reusable fluorescent sensor for boron based on glycosyloxyethyl methacrylate was prepared by photopolymerization. The response characteristics such as response time, pH, linear range, limit of detection were systematically investigated. The excitation/emission maxima of the membrane were at 378/423 nm, respectively. The approximate response time was measured as 50 sec. In addition, sensor had a very low limit of detection which was 0.3 ppb. The sensor was successfully used for the determination of boron in water samples with satisfactory results.

Keywords: boron, fluorescence, photopolymerization, polymeric sensor

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11270 Combustion Characteristics and Pollutant Emissions in Gasoline/Ethanol Mixed Fuels

Authors: Shin Woo Kim, Eui Ju Lee

Abstract:

The recent development of biofuel production technology facilitates the use of bioethanol and biodiesel on automobile. Bioethanol, especially, can be used as a fuel for gasoline vehicles because the addition of ethanol has been known to increase octane number and reduce soot emissions. However, the wide application of biofuel has been still limited because of lack of detailed combustion properties such as auto-ignition temperature and pollutant emissions such as NOx and soot, which has been concerned mainly on the vehicle fire safety and environmental safety. In this study, the combustion characteristics of gasoline/ethanol fuel were investigated both numerically and experimentally. For auto-ignition temperature and NOx emission, the numerical simulation was performed on the well-stirred reactor (WSR) to simulate the homogeneous gasoline engine and to clarify the effect of ethanol addition in the gasoline fuel. Also, the response surface method (RSM) was introduced as a design of experiment (DOE), which enables the various combustion properties to be predicted and optimized systematically with respect to three independent variables, i.e., ethanol mole fraction, equivalence ratio and residence time. The results of stoichiometric gasoline surrogate show that the auto-ignition temperature increases but NOx yields decrease with increasing ethanol mole fraction. This implies that the bioethanol added gasoline is an eco-friendly fuel on engine running condition. However, unburned hydrocarbon is increased dramatically with increasing ethanol content, which results from the incomplete combustion and hence needs to adjust combustion itself rather than an after-treatment system. RSM results analyzed with three independent variables predict the auto-ignition temperature accurately. However, NOx emission had a big difference between the calculated values and the predicted values using conventional RSM because NOx emission varies very steeply and hence the obtained second order polynomial cannot follow the rates. To relax the increasing rate of dependent variable, NOx emission is taken as common logarithms and worked again with RSM. NOx emission predicted through logarithm transformation is in a fairly good agreement with the experimental results. For more tangible understanding of gasoline/ethanol fuel on pollutant emissions, experimental measurements of combustion products were performed in gasoline/ethanol pool fires, which is widely used as a fire source of laboratory scale experiments. Three measurement methods were introduced to clarify the pollutant emissions, i.e., various gas concentrations including NOx, gravimetric soot filter sampling for elements analysis and pyrolysis, thermophoretic soot sampling with transmission electron microscopy (TEM). Soot yield by gravimetric sampling was decreased dramatically as ethanol was added, but NOx emission was almost comparable regardless of ethanol mole fraction. The morphology of the soot particle was investigated to address the degree of soot maturing. The incipient soot such as a liquid like PAHs was observed clearly on the soot of higher ethanol containing gasoline, and the soot might be matured under the undiluted gasoline fuel.

Keywords: gasoline/ethanol fuel, NOx, pool fire, soot, well-stirred reactor (WSR)

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11269 Input Data Balancing in a Neural Network PM-10 Forecasting System

Authors: Suk-Hyun Yu, Heeyong Kwon

Abstract:

Recently PM-10 has become a social and global issue. It is one of major air pollutants which affect human health. Therefore, it needs to be forecasted rapidly and precisely. However, PM-10 comes from various emission sources, and its level of concentration is largely dependent on meteorological and geographical factors of local and global region, so the forecasting of PM-10 concentration is very difficult. Neural network model can be used in the case. But, there are few cases of high concentration PM-10. It makes the learning of the neural network model difficult. In this paper, we suggest a simple input balancing method when the data distribution is uneven. It is based on the probability of appearance of the data. Experimental results show that the input balancing makes the neural networks’ learning easy and improves the forecasting rates.

Keywords: artificial intelligence, air quality prediction, neural networks, pattern recognition, PM-10

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11268 Research on the Public Policy of Vehicle Restriction under Traffic Control

Authors: Wang Qian, Bian Cheng Xiang

Abstract:

In recent years, with the improvement of China's urbanization level, the number of urban motor vehicles has grown rapidly. As residents' daily commuting necessities, cars cause a lot of exhaust emissions and urban traffic congestion. In the "Fourteenth Five Year Plan" of China, it is proposed to strive to reach the peak of carbon dioxide emissions by 2030 and achieve carbon neutrality by 2060. Urban transport accounts for a high proportion of carbon emission sources. It is an important driving force for the realization of China's carbon peak strategy. Some cities have introduced and implemented the policy of "car restriction" to solve related urban problems by reducing the use of cars. This paper analyzes the implementation of the "automobile restriction" policy, evaluates the relevant effects of the automobile restriction policy, and discusses how to better optimize the "automobile restriction" policy in the process of urban governance.

Keywords: carbon emission, traffic jams, vehicle restrictions, evaluate

Procedia PDF Downloads 126