Search results for: 3D plant data

Authors: Chen Wang, Qiuxiao Chen

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With the advent of the information age and the era of big data, urban planning research is no longer satisfied with the analysis and application of traditional data. Because of the limitations of traditional urban commercial center system research, big data provides new opportunities for urban research. Therefore, based on the quantitative evaluation method of big data, the commercial center system of the main city of Hangzhou is analyzed and evaluated, and the scale and hierarchical structure characteristics of the urban commercial center system are studied. In order to make up for the shortcomings of the existing POI extraction method, it proposes a POI extraction method based on adaptive adjustment of search window, which can accurately and efficiently extract the POI data of commercial business in the main city of Hangzhou. Through the visualization and nuclear density analysis of the extracted Point of Interest (POI) data, the current situation of the commercial center system in the main city of Hangzhou is evaluated. Then it compares with the commercial center system structure of 'Hangzhou City Master Plan (2001-2020)', analyzes the problems existing in the planned urban commercial center system, and provides corresponding suggestions and optimization strategy for the optimization of the planning of Hangzhou commercial center system. Then get the following conclusions: The status quo of the commercial center system in the main city of Hangzhou presents a first-level main center, a two-level main center, three third-level sub-centers, and multiple community-level business centers. Generally speaking, the construction of the main center in the commercial center system is basically up to standard, and there is still a big gap in the construction of the sub-center and the regional-level commercial center, further construction is needed. Therefore, it proposes an optimized hierarchical functional system, organizes commercial centers in an orderly manner; strengthens the central radiation to drive surrounding areas; implements the construction guidance of the center, effectively promotes the development of group formation and further improves the commercial center system structure of the main city of Hangzhou.

Keywords: business center system, business format, main city of Hangzhou, POI extraction method

Procedia PDF Downloads 123

Authors: Blessing Atim Aderibigbe

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A series of amine/ester-linked hybrid compounds containing pharmacophores, such as ursolic acid, oleanolic acid, ferrocene and bisphosphonates, were synthesized in an attempt to develop potent antibacterial and anticancer agents. Their structures were analyzed and confirmed using Nuclear Magnetic Resonance, Fourier Transform Infrared Spectroscopy, and mass spectroscopy. All the synthesized hybrid compounds were evaluated for their antibacterial activities against eleven selected bacterial strains using a serial dilution method. Some of the compounds displayed significant antibacterial activity against most of the bacterial and fungal strains. In addition, the in vitro cytotoxicity of these compounds was also performed against selected cancer cell lines. Some of the compounds were also found to be more active than their parent compounds, revealing the efficacy of designing hybrid molecules using plant-based bioactive agents.

Keywords: ursolic acid, hybrid drugs, oleanolic acid, bisphosphonates

Procedia PDF Downloads 65

Authors: Khamael Abualnaja, Hala M. Abo-Dief

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Silver nanoparticles (AgNPs) are the subject of important recent interest, present in a large range of applications such as electronics, catalysis, chemistry, energy, and medicine. Metallic nanoparticles are traditionally synthesized by wet chemical techniques, where the chemicals used are quite often toxic and flammable. In this work, we describe an effective and environmental-friendly technique of green synthesis of silver nanoparticles. Silver nanoparticles (AgNPs) synthesized using silver nitrate solution and the extract of mint, basil, orange peel and Tangerines peel which used as reducing agents. Silver Nanoparticles were characterized using Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and UV–Vis absorption spectroscopy. SEM analysis showed the average particle size of mint, basil, orange peel, Tangerines peel are 30, 20, 12, 10 nm respectively. This is for the first time that any plant extract was used for the synthesis of nanoparticles.

Keywords: silver nanoparticles, green synthesis, scanning electron microscopy, plants

Procedia PDF Downloads 242

Authors: Thanomsin Chakreeves, Atichat Preittigun, Ajchara Phu-ang

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This paper presents a stakeholder analysis of agricultural drone policies that meet the government's goal of building an agricultural drone ecosystem in Thailand. Firstly, case studies from other countries are reviewed. The stakeholder analysis method and qualitative data from the interviews are then presented including data from the Institute of Innovation and Management, the Office of National Higher Education Science Research and Innovation Policy Council, agricultural entrepreneurs and farmers. Study and interview data are then employed to describe the current ecosystem and to guide the implementation of agricultural drone policies that are suitable for the ecosystem of Thailand. Finally, policy recommendations are then made that the Thai government should adopt in the future.

Keywords: drone public policy, drone ecosystem, policy development, agricultural drone

Procedia PDF Downloads 132

Authors: M. Ali Mandegari, S. Farzad, J. F. Görgens

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Sugar is one of the main agricultural industries in South Africa and approximately livelihoods of one million South Africans are indirectly dependent on sugar industry which is economically struggling with some problems and should re-invent in order to ensure a long-term sustainability. Second generation bio-refinery is defined as a process to use waste fibrous for the production of bio-fuel, chemicals animal food, and electricity. Bio-ethanol is by far the most widely used bio-fuel for transportation worldwide and many challenges in front of bio-ethanol production were solved. Bio-refinery annexed to the existing sugar mill for production of bio-ethanol and electricity is proposed to sugar industry and is addressed in this study. Since flow-sheet development is the key element of the bio-ethanol process, in this work, a bio-refinery (bio-ethanol and electricity production) annexed to a typical South African sugar mill considering 65ton/h dry sugarcane bagasse and tops/trash as feedstock was simulated. Aspen PlusTM V8.6 was applied as simulator and realistic simulation development approach was followed to reflect the practical behavior of the plant. Latest results of other researches considering pretreatment, hydrolysis, fermentation, enzyme production, bio-ethanol production and other supplementary units such as evaporation, water treatment, boiler, and steam/electricity generation units were adopted to establish a comprehensive bio-refinery simulation. Steam explosion with SO2 was selected for pretreatment due to minimum inhibitor production and simultaneous saccharification and fermentation (SSF) configuration was adopted for enzymatic hydrolysis and fermentation of cellulose and hydrolyze. Bio-ethanol purification was simulated by two distillation columns with side stream and fuel grade bio-ethanol (99.5%) was achieved using molecular sieve in order to minimize the capital and operating costs. Also boiler and steam/power generation were completed using industrial design data. Results indicates 256.6 kg bio ethanol per ton of feedstock and 31 MW surplus power were attained from bio-refinery while the process consumes 3.5, 3.38, and 0.164 (GJ/ton per ton of feedstock) hot utility, cold utility and electricity respectively. Developed simulation is a threshold of variety analyses and developments for further studies.

Keywords: bio-refinery, bagasse, tops, trash, bio-ethanol, electricity

Procedia PDF Downloads 515

Authors: Boudene Maamar, Xu Mai

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Optical Intersatellite Links (OISLs) are wireless communications using optical signals to interconnect satellites. It is expected to be the next generation wireless communication technology according to its inherent characteristics like: an increased bandwidth, a high data rate, a data transmission security, an immunity to interference, and an unregulated spectrum etc. Optical space links are the best choice for the classical communication schemes due to its distinctive properties; high frequency, small antenna diameter and lowest transmitted power, which are critical factors to define a space communication. This paper discusses the development of free space technology and analyses the parameters and factors to establish a reliable intersatellite links using an optical signal to exchange data between satellites.

Keywords: optical intersatellite links, optical wireless communications, free space optical communications, next generation wireless communication

Procedia PDF Downloads 435

Authors: Emi Yuda, Yutaka Yoshida, Junichiro Hayano

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Distinct circadian rhythm of activity, i.e., high activity during the day and deep rest at night are a typical feature of a healthy lifestyle. Exposure to the skylight is thought to be an important factor to increase arousal level and maintain normal circadian rhythm. To examine whether sunshine hours influence the day-night contract of activity, we analyzed the relationship between 24-hour heart rate (HR) and weather data of the recording day. We analyzed data in 36,500 males and 49,854 females of Allostatic State Mapping by Ambulatory ECG Repository (ALLSTAR) database in Japan. Median (IQR) sunshine duration was 5.3 (2.8-7.9) hr. While sunshine hours had only modest effects of increasing 24-hour average HR in either gender (P=0.0282 and 0.0248 for male and female) and no significant effects on nighttime HR in either gender, it increased daytime HR (P = 0.0007 and 0.0015) and day-night HF difference in both genders (P < 0.0001 for both) even after adjusting for the effects of average temperature, atmospheric pressure, and humidity. Our observations support for the hypothesis that longer sunshine hours enhance circadian rhythm of activity.

Keywords: big data, circadian rhythm, heart rate, sunshine

Procedia PDF Downloads 152

Authors: Yassine Bouzouita, Oumaima Belghith, Cyrine Zitoun, Charles Bonneau

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Performance measurement framework (PMF) is an essential tool in any organization to assess the performance of its processes. It guides businesses to stay on track with their objectives and benchmark themselves from the market. With the growing trend of the digital transformation of business processes, led by innovations in artificial intelligence (AI) & Big Data applications, developing a mature system capable of capturing the impact of digital solutions across different industries became a necessity. Based on the conducted research, no such system has been developed in academia nor the industry. In this context, this paper covers a variety of methodologies on performance measurement, overviews the major AI and big data applications in the banking sector, and covers an exhaustive list of relevant metrics. Consequently, this paper is of interest to both researchers and practitioners. From an academic perspective, it offers a comparative analysis of the reviewed performance measurement frameworks. From an industry perspective, it offers exhaustive research, from market leaders, of the major applications of AI and Big Data technologies, across the different departments of an organization. Moreover, it suggests a standardized classification model with a well-defined structure of intelligent digital solutions. The aforementioned classification is mapped to a centralized library that contains an indexed collection of potential metrics for each application. This library is arranged in a manner that facilitates the rapid search and retrieval of relevant metrics. This proposed framework is meant to guide professionals in identifying the most appropriate AI and big data applications that should be adopted. Furthermore, it will help them meet their business objectives through understanding the potential impact of such solutions on the entire organization.

Keywords: AI and Big Data applications, impact assessment, metrics, performance measurement

Procedia PDF Downloads 182

Authors: Alvaro L. Ronco

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Background and purpose: Although our country is a developing one, it has a typical Western meat-rich dietary style. Based on estimates of heme and nonheme iron contents in representative foods, we carried out the present epidemiologic study, with the aim of accurately analyzing dietary iron and its role on CRC risk. Subjects/methods: Patients (611 CRC incident cases and 2394 controls, all belonging to public hospitals of our capital city) were interviewed through a questionnaire including socio-demographic, reproductive and lifestyle variables, and a food frequency questionnaire of 64 items, which asked about food intake 5 years before the interview. The sample included 1937 men and 1068 women. Controls were matched by sex and age (± 5 years) to cases. Food-derived nutrients were calculated from available databases. Total dietary iron was calculated and classified by heme or nonheme source, following data of specific Dutch and Canadian studies, and additionally adjusted by energy. Odds Ratios (OR) and 95% confidence intervals were calculated through unconditional logistic regression, adjusting for relevant potential confounders (education, body mass index, family history of cancer, energy, infusions, and others). A heme/nonheme (H/NH) ratio was created and the interest variables were categorized into tertiles, for analysis purposes. Results: The following risk estimations correspond to the highest tertiles. Total iron intake showed no association with CRC risk neither among men (OR=0.83, ptrend =.18) nor among women (OR=1.48, ptrend =.09). Heme iron was positively associated among men (OR=1.88, ptrend < .001) and for the overall sample (OR=1.44, ptrend =.002), however, it was not associated among women (OR=0.91, ptrend =.83). Nonheme iron showed an inverse association among men (OR=0.53, ptrend < .001) and the overall sample (OR=0.78, ptrend =.04), but was not associated among women (OR=1.46, ptrend =.14). Regarding H/NH ratio, risks increased only among men (OR=2.12, ptrend < .001) but lacked of association among women (OR=0.81, ptrend =.29). Conclusions. We have observed different types of associations between CRC risk and high dietary heme, nonheme and H/NH iron ratio. Therefore, the source of the available iron might be of importance as a link to colorectal carcinogenesis, perhaps pointing to reconsider the animal/plant proportions of this vital mineral within diet. Nevertheless, the different associations observed for each sex, demand further studies in order to clarify these points.

Keywords: chelation, colorectal cancer, heme, iron, nonheme

Procedia PDF Downloads 155

Authors: Ritu Vashistha, Jitender Kumar

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Clustering using the K-means algorithm is a very common way to understand and analyze the obtained output data. When a similar object is grouped, this is called the basis of Clustering. There is K number of objects and C number of cluster in to single cluster in which k is always supposed to be less than C having each cluster to be its own centroid but the major problem is how is identify the cluster is correct based on the data. Formulation of the cluster is not a regular task for every tuple of row record or entity but it is done by an iterative process. Each and every record, tuple, entity is checked and examined and similarity dissimilarity is examined. So this iterative process seems to be very lengthy and unable to give optimal output for the cluster and time taken to find the cluster. To overcome the drawback challenge, we are proposing a formula to find the clusters at the run time, so this approach can give us optimal results. The proposed approach uses the Euclidian distance formula as well melanosis to find the minimum distance between slots as technically we called clusters and the same approach we have also applied to Ant Colony Optimization(ACO) algorithm, which results in the production of two and multi-dimensional matrix.

Keywords: ant colony optimization, data clustering, centroids, data mining, k-means

Procedia PDF Downloads 115

Authors: Frederico Fialho Teixeira, Islam Mashaly, Maryam Shafiei, Jurij Karlovsek

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The ubiquity of data gathering and smart technologies, advancements in virtual technologies, and the development of the internet of things (IoT) have created urgent demands for the development of frameworks and efficient workflows for data collection, visualisation, and analysis. Digital twin, in different scales of the city into the building, allows for bringing together data from different sources to generate fundamental and illuminating insights for the management of current facilities and the lifecycle of amenities as well as improvement of the performance of current and future designs. Over the past two decades, there has been growing interest in the topic of digital twin and their applications in city and building scales. Most such studies look at the urban environment through a homogeneous or generalist lens and lack specificity in particular characteristics or identities, which define an urban university campus. Bridging this knowledge gap, this paper offers a framework for developing a digital twin for a university campus that, with some modifications, could provide insights for any large-scale digital twin settings like towns and cities. It showcases how currently unused data could be purposefully combined, interpolated and visualised for producing analysis-ready data (such as flood or energy simulations or functional and occupancy maps), highlighting the potential applications of such a framework for campus planning and policymaking. The research integrates campus-level data layers into one spatial information repository and casts light on critical data clusters for the digital twin at the campus level. The paper also seeks to raise insightful and directive questions on how digital twin for campus can be extrapolated to city-scale digital twin. The outcomes of the paper, thus, inform future projects for the development of large-scale digital twin as well as urban and architectural researchers on potential applications of digital twin in future design, management, and sustainable planning, to predict problems, calculate risks, decrease management costs, and improve performance.

Keywords: digital twin, smart campus, framework, data collection, point cloud

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Authors: Huma Khan, Faiza Akhtar

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The present study investigates the effects of burnout toward job performance and job satisfaction with the moderating role of hope and self-efficacy. Findings from 310 frontline employees of Pakistani commercial banks (Lahore, Karachi & Islamabad) disclosed burnout has negative significant effects on job performance and job satisfaction. Simple random sampling technique was used to collect data and inferential statistics were applied to analyzed the data. However, results disclosed no moderation effect of hope on burnout, job performance or with job satisfaction. Moreover, Data significantly supported the moderation effect of self-efficacy. Study further shed light on the development of psychological capital. Importance of the implication of the current finding is discussed.

Keywords: burnout, hope, job performance, job satisfaction, psychological capital, self-efficacy

Procedia PDF Downloads 124

Authors: Mateus L. O. Freitas, Flávia H. de M. Libório, Letycia L. Ricardo, Patrícia da C. Zonetti, Graciene de S. Bido

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Weeds compete with agricultural crops for resources such as light, water, and nutrients. This competition can cause significant damage to agricultural producers, and, currently, the use of agrochemicals is the most effective method for controlling these undesirable plants. Morning glory (Ipomoea grandifolia [Dammer] O'Donell) is an aggressive weed and significantly reduces agricultural productivity making harvesting difficult, especially mechanical harvesting. The biggest challenge in modern agriculture is to preserve high productivity reducing environmental damage and maintaining soil characteristics. No-till is a sustainable practice that can reduce the use of agrochemicals and environmental impacts due to the presence of plant residues in the soil, which release allelopathic compounds and reduce the incidence or alter the growth and development of crops and weeds. Sorghum (Sorghum bicolor [L.] Moench) is a forage with proven allelopathic activity, mainly for producing sorgholeone. In this context, this research aimed to evaluate the allelopathic action of sorghum fractions using hexane, dichloromethane, butanol, and ethyl acetate on the germination and initial growth of morning glory. The parameters analyzed were the percentage of germination, speed of germination, seedling length, and biomass weight (fresh and dry). The bioassays were performed in Petri dishes, kept in an incubation chamber for 7 days, at 25 °C, with a 12h photoperiod. The experimental design was completely randomized, with five replicates of each treatment. The data were evaluated by analysis of variance, and the averages between each treatment were compared using the Scott Knott test at a 5% significance level. The results indicated that the dichloromethane and ethyl acetate fractions showed bioherbicidal effects, promoting effective reductions on germination and initial growth of the morning glory. It was concluded that allelochemicals were probably extracted in these fractions. These secondary metabolites can reduce the use of agrochemicals and environmental impact, making agricultural production systems more sustainable.

Keywords: allelochemicals, secondary metabolism, sorgoleone, weeds

Procedia PDF Downloads 135

Authors: Moohyun Lee, Soojung Hur, Yongwan Park

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In this paper is proposed a method uses only LIDAR system to classification an obstacle and determine its type by establishing database for classifying obstacles based on LIDAR. The existing LIDAR system, in determining the recognition of obstruction in an autonomous vehicle, has an advantage in terms of accuracy and shorter recognition time. However, it was difficult to determine the type of obstacle and therefore accurate path planning based on the type of obstacle was not possible. In order to overcome this problem, a method of classifying obstacle type based on existing LIDAR and using the width of obstacle materials was proposed. However, width measurement was not sufficient to improve accuracy. In this research, the width data was used to do the first classification; database for LIDAR intensity data by four major obstacle materials on the road were created; comparison is made to the LIDAR intensity data of actual obstacle materials; and determine the obstacle type by finding the one with highest similarity values. An experiment using an actual autonomous vehicle under real environment shows that data declined in quality in comparison to 3D LIDAR and it was possible to classify obstacle materials using 2D LIDAR.

Keywords: obstacle, classification, database, LIDAR, segmentation, intensity

Procedia PDF Downloads 326

Authors: Yogesh Kumar, Adarsh Kumar

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A body farm is a research facility where research is done on forensic investigation and medico-legal disciplines like forensic entomology, forensic pathology, forensic anthropology, forensic archaeology, and related areas of forensic veterinary. All the research is done to collect data on the rate of decomposition (animal and human) and forensically important insects to assist in crime detection. The data collected is used by forensic pathologists, forensic experts, and other experts for the investigation of crime cases and further research. The research work includes different conditions of a dead body like fresh, bloating, decay, dry, and skeleton, and data on local insects which depends on the climatic conditions of the local areas of that country. Therefore, it is the need of time to collect appropriate data in managed conditions with a proper set-up in every country. Hence, it is the duty of the scientific community of every country to establish/propose such facilities for justice and social management. The body farms are also used for training of police, military, investigative dogs, and other agencies. At present, only four countries viz. U.S., Australia, Canada, and Netherlands have body farms and related facilities in organised manner. There is no body farm in Asia also. In India, we have been trying to establish a body farm in A&N Islands that is near Singapore, Malaysia, and some other Asian countries. In view of the above, it becomes imperative to discuss the matter with Asian countries to collect the data on decomposition in a proper manner by establishing a body farm. We can also share the data, knowledge, and expertise to collaborate with one another to make such facilities better and have good scientific relations to promote science and explore ways of investigation at the world level.

Keywords: body farm, rate of decomposition, forensically important flies, time since death

Procedia PDF Downloads 67

Authors: Tareq Nikzad

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Since the first bank was established in 1933, Afghanistan's banking sector has seen a number of variations but hasn't been able to grow to its full potential because of the civil war. The implementation of dual banks in Afghanistan is investigated in this study in relation to the effects of inflation and interest rates. This research took data from World Bank Data (WBD) over a period of nineteen years. For the banking sector, inflation, which is the general rise in prices of goods and services over time, presents considerable difficulties. The objectives of this research are to analyze the effect of inflation and interest rates on conventional and Islamic banks in Afghanistan, identify potential differences between these two banking models, and provide insights for policymakers and practitioners. A mixed-methods approach is used in the research to analyze quantitative data and qualitatively examine the unique difficulties that banks in Afghanistan's economic atmosphere encounter. The findings contribute to the understanding of the relationship between interest rate, inflation rate, and the performance of both banking systems in Afghanistan. The paper concludes with recommendations for policymakers and banking institutions to enhance the stability and growth of the banking sector in Afghanistan. Interest is described as "a prefixed rate for use or borrowing of money" from an Islamic perspective. This "prefixed rate," known in Islamic economics as "riba," has been described as "something undesirable." Furthermore, by using the time series regression data technique on the annual data from 2003 to 2021, this research examines the effect of CPI inflation rate and interest rate of Banking in Afghanistan.

Keywords: inflation, Islamic banking, conventional banking, interest, Afghanistan, impact

Procedia PDF Downloads 58

Authors: Y. Fekir, K. Mederbal, M. A. Hammadouche, D. Anteur

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The cultural park of the Ahaggar, occupying a large area of Algeria, is characterized by a rich wetlands area to be preserved and managed both in time and space. The management of a large area, by its complexity, needs large amounts of data, which for the most part, are spatially localized (DEM, satellite images and socio-economic information...), where the use of conventional and traditional methods is quite difficult. The remote sensing, by its efficiency in environmental applications, became an indispensable solution for this kind of studies. Remote sensing imaging data have been very useful in the last decade in very interesting applications. They can aid in several domains such as the detection and identification of diverse wetland surface targets, topographical details, and geological features... In this work, we try to extract automatically wetlands area using multispectral remotely sensed data on-board the Earth Observing 1 (EO-1) and Landsat satellite. Both are high-resolution multispectral imager with a 30 m resolution. The instrument images an interesting surface area. We have used images acquired over the several area of interesting in the National Park of Ahaggar in the south of Algeria. An Extraction Algorithm is applied on the several spectral index obtained from combination of different spectral bands to extract wetlands fraction occupation of land use. The obtained results show an accuracy to distinguish wetlands area from the other lad use themes using a fine exploitation on spectral index.

Keywords: multispectral data, EO1, landsat, wetlands, Ahaggar, Algeria

Procedia PDF Downloads 364

Authors: Janne Engblom, Elias Oikarinen

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A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models are dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Arellano-Bover/Blundell-Bond Generalized method of moments (GMM) estimator which is an extension of the Arellano-Bond model where past values and different transformations of past values of the potentially problematic independent variable are used as instruments together with other instrumental variables. The Arellano–Bover/Blundell–Bond estimator augments Arellano–Bond by making an additional assumption that first differences of instrument variables are uncorrelated with the fixed effects. This allows the introduction of more instruments and can dramatically improve efficiency. It builds a system of two equations—the original equation and the transformed one—and is also known as system GMM. In this study, Finnish housing price dynamics were examined empirically by using the Arellano–Bover/Blundell–Bond estimation technique together with ordinary OLS. The aim of the analysis was to provide a comparison between conventional fixed-effects panel data models and dynamic panel data models. The Arellano–Bover/Blundell–Bond estimator is suitable for this analysis for a number of reasons: It is a general estimator designed for situations with 1) a linear functional relationship; 2) one left-hand-side variable that is dynamic, depending on its own past realizations; 3) independent variables that are not strictly exogenous, meaning they are correlated with past and possibly current realizations of the error; 4) fixed individual effects; and 5) heteroskedasticity and autocorrelation within individuals but not across them. Based on data of 14 Finnish cities over 1988-2012 differences of short-run housing price dynamics estimates were considerable when different models and instrumenting were used. Especially, the use of different instrumental variables caused variation of model estimates together with their statistical significance. This was particularly clear when comparing estimates of OLS with different dynamic panel data models. Estimates provided by dynamic panel data models were more in line with theory of housing price dynamics.

Keywords: dynamic model, fixed effects, panel data, price dynamics

Procedia PDF Downloads 1459

Authors: E. Y. Jo, S. M. Park, I. S. Yeo, K. K. Kim, S. J. Park, Y. K. Kim, Y. D. Kim, C. G. Park

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SO3 is created in small quantities during the combustion of fuel that contains sulfur, with the quantity produced a function of the boiler design, fuel sulfur content, excess air level, and the presence of oxidizing agents. Typically, about 1% of the fuel sulfur will be oxidized to SO3, but it can range from 0.5% to 1.5% depending on various factors. Combustion of fuels that contain oxidizing agents, such as certain types of fuel oil or petroleum coke, can result in even higher levels of oxidation. SO3 levels in the flue gas emitted by combustion are very high, which becomes a cause of machinery corrosion or a visible blue plume. Because of that, power plants firing petroleum residues need to installation of SO3 removal system. In this study, SO3 removal system using salt solution was developed and several salts solutions were tested for obtain optimal solution for SO3 removal system. Response surface methodology was used to optimize the operation parameters such as gas-liquid ratio, concentration of salts.

Keywords: flue gas desulfurization, petroleum cokes, Sulfur trioxide, SO3 removal

Procedia PDF Downloads 502

Authors: Aybike Ayfer Karadağ

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Today, the amount of water available is decreasing day by day due to global warming, environmental problems and population increase. To protect water resources, it is necessary to take a lot of measures from the global scale to the local scale. Some of these measures are related to spatial planning studies. In this study, the impact of water process analysis was assessed in the development of spatial planning for water conservation. The study was conducted in the Kovada sub-watershed (Isparta, Turkey). By means of water process analysis, the way to reach underground water of surface water in the study area is mapped. In this context, plant cover, soil and rock permeability were evaluated holistically with geographic information systems technologies. Then, on the map, water permeability is classified and this is spatially expressed. The findings show that the permeability of the water is different in the study case. As a result, the water permeability map needs to be included in the planning for water conservation planning.

Keywords: water, conservation, spatial planning, water process analysis

Procedia PDF Downloads 199

Authors: Amogh Katti, J. Sai Asritha, D. Nivedh, M. Kalyan Srinivas, B. Somnath Chakravarthi

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Today's modern education system uses Learning Management System (LMS) portals for the scoring and grading of student performances, to maintain student records, and teachers are instructed to accept assignments through online submissions of .pdf,.doc,.ppt, etc. There is a risk of data tampering in the traditional portals; we will apply the Blockchain model instead of this traditional model to avoid data tampering and also provide a decentralized mechanism for overall fairness. Blockchain technology is a better and also recommended model because of the following features: consensus mechanism, decentralized system, cryptographic encryption, smart contracts, Ethereum blockchain. The proposed system ensures data integrity and tamper-proof assignment submission and grading, which will be helpful for both students and also educators.

Keywords: education technology, learning management system, decentralized applications, blockchain

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Authors: Ana C. R. P. Ferreira, Adriano H. P. Pereira

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Given the frequent variation of mineral properties throughout the Araxá pyrochlore deposit, even if a good homogenization work has been carried out before feeding the processing plants, an operation with quality and performance’s high variety standard is expected. These results could be improved and standardized if the blend composition parameters that most influence the processing route are determined, and then the types of raw materials are grouped by them, finally presenting a great reference with operational settings for each group. Associating the physical and chemical parameters of a unit operation through benchmarking or even an optimal reference of metallurgical recovery and product quality reflects in the reduction of the production costs, optimization of the mineral resource, and guarantee of greater stability in the subsequent processes of the production chain that uses the mineral of interest. Conducting a comprehensive exploratory data analysis to identify which characteristics of the ore are most relevant to the process route, associated with the use of Machine Learning algorithms for grouping the raw material (ore) and associating these with reference variables in the process’ benchmark is a reasonable alternative for the standardization and improvement of mineral processing units. Clustering methods through Decision Tree and K-Means were employed, associated with algorithms based on the theory of benchmarking, with criteria defined by the process team in order to reference the best adjustments for processing the ore piles of each cluster. A clean user interface was created to obtain the outputs of the created algorithm. The results were measured through the average time of adjustment and stabilization of the process after a new pile of homogenized ore enters the plant, as well as the average time needed to achieve the best processing result. Direct gains from the metallurgical recovery of the process were also measured. The results were promising, with a reduction in the adjustment time and stabilization when starting the processing of a new ore pile, as well as reaching the benchmark. Also noteworthy are the gains in metallurgical recovery, which reflect a significant saving in ore consumption and a consequent reduction in production costs, hence a more rational use of the tailings dams and life optimization of the mineral deposit.

Keywords: mineral clustering, machine learning, process optimization, pyrochlore processing

Procedia PDF Downloads 133

Authors: Bai-Chen Xie, Xian-Peng Chen

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China has become the world's largest energy producer and consumer, and its development of renewable energy is of great significance to global energy governance and the fight against climate change. The rapid growth of solar power in China could help achieve its ambitious carbon peak and carbon neutrality targets early. However, the non-technical costs of solar power in China are much higher than at international levels, meaning that inefficiencies are rooted in poor management and improper policy design and that efficiency distortions have become a serious challenge to the sustainable development of the renewable energy industry. Unlike fossil energy generation technologies, the output of solar power is closely related to the volatile solar resource, and the spatial unevenness of solar resource distribution leads to potential efficiency spatial distribution differences. It is necessary to develop an efficiency evaluation method that considers the volatility of solar resources and explores the mechanism of the influence of natural geography and social environment on the spatially varying characteristics of efficiency distribution to uncover the root causes of managing inefficiencies. The study sets solar resources as stochastic inputs, introduces a chance-constrained data envelopment analysis model combined with the directional distance function, and measures the solar resource utilization efficiency of 222 solar power plants in representative photovoltaic bases in northwestern China. By the meta-frontier analysis, we measured the characteristics of different power plant clusters and compared the differences among groups, discussed the mechanism of environmental factors influencing inefficiencies, and performed statistical tests through the system generalized method of moments. Rational localization of power plants is a systematic project that requires careful consideration of the full utilization of solar resources, low transmission costs, and power consumption guarantee. Suitable temperature, precipitation, and wind speed can improve the working performance of photovoltaic modules, reasonable terrain inclination can reduce land cost, and the proximity to cities strongly guarantees the consumption of electricity. The density of electricity demand and high-tech industries is more important than resource abundance because they trigger the clustering of power plants to result in a good demonstration and competitive effect. To ensure renewable energy consumption, increased support for rural grids and encouraging direct trading between generators and neighboring users will provide solutions. The study will provide proposals for improving the full life-cycle operational activities of solar power plants in China to reduce high non-technical costs and improve competitiveness against fossil energy sources.

Keywords: solar power plants, environmental factors, data envelopment analysis, efficiency evaluation

Procedia PDF Downloads 76

Authors: Sheng-Hung Chen, Grace Mmametena Mahlangu, Hui-Cheng Wang

Abstract:

This study aims to explore the trends of the Entrepreneurial Framework Conditions (EFCs) in the five African regions. The Global Entrepreneur Monitor (GEM) is the primary source of data. The data drawn were organized into a panel (2000-2021) and obtained from the National Expert Survey (NES) databases as harmonized by the (GEM). The Methodology used is descriptive and uses mainly charts and tables; this is in line with the approach used by the GEM. The GEM draws its data from the National Expert Survey (NES). The survey by the NES is administered to experts in each country. The GEM collects entrepreneurship data specific to each country. It provides information about entrepreneurial ecosystems and their impact on entrepreneurship. The secondary source is from the literature review. This study focuses on the following GEM indicators: Financing for Entrepreneurs, Government support and Policies, Taxes and Bureaucracy, Government programs, Basic School Entrepreneurial Education and Training, Post school Entrepreneurial Education and Training, R&D Transfer, Commercial And Professional Infrastructure, Internal Market Dynamics, Internal Market Openness, Physical and Service Infrastructure, and Cultural And Social Norms, based on GEM Report 2020/21. The limitation of the study is the lack of updated data from some countries. Countries have to fund their own regional studies; African countries do not regularly participate due to a lack of resources.

Keywords: trend analysis, entrepreneurial framework conditions (EFCs), African region, government programs

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Authors: Herminio Martínez-García, Juan Gámiz, Yolanda Bolea, Antoni Grau

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This article presents an interactive system for data acquisition in vehicle testing according to the test process defined in automotive directive 2004/104/EC. The project has been designed and developed by authors for the Spanish company Applus-LGAI. The developed project will result in a new process, which will involve the creation of braking cycle test defined in the aforementioned automotive directive. It will also allow the analysis of new vehicle features that was not feasible, allowing an increasing interaction with the vehicle. Potential users of this system in the short term will be vehicle manufacturers and in a medium term the system can be extended to testing other automotive components and EMC tests.

Keywords: automotive process, data acquisition system, electromagnetic compatibility (EMC) testing, European Directive 2004/104/EC

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Authors: Jaqueline Maria Ribeiro Vieira

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Different strategies and tools are available at the oil and gas industry for detecting and analyzing tension and possible fractures in borehole walls. Most of these techniques are based on manual observation of the captured borehole images. While this strategy may be possible and convenient with small images and few data, it may become difficult and suitable to errors when big databases of images must be treated. While the patterns may differ among the image area, depending on many characteristics (drilling strategy, rock components, rock strength, etc.). Previously we developed and proposed a novel strategy capable of detecting patterns at borehole images that may point to regions that have tension and breakout characteristics, based on segmented images. In this work we propose the inclusion of data-mining classification strategies in order to create a knowledge database of the segmented curves. These classifiers allow that, after some time using and manually pointing parts of borehole images that correspond to tension regions and breakout areas, the system will indicate and suggest automatically new candidate regions, with higher accuracy. We suggest the use of different classifiers methods, in order to achieve different knowledge data set configurations.

Keywords: image segmentation, oil well visualization, classifiers, data-mining, visual computer

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Authors: Chidiebere C. Agoha, Armstong C. Awuzie, Chukwuebuka N. Onwubuariri, Joy O. Njoku

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Spatial analysis is a field of study that utilizes geographic or spatial information to understand and analyze patterns, relationships, and trends in data. It is characterized by the use of geographic or spatial information, which allows for the analysis of data in the context of its location and surroundings. It is different from non-spatial or aspatial techniques, which do not consider the geographic context and may not provide as complete of an understanding of the data. Spatial analysis is applied in a variety of fields, which includes urban planning, environmental science, geosciences, epidemiology, marketing, to gain insights and make decisions about complex spatial problems. This review paper explores definitions of spatial analysis from various sources, including examples of its application and different analysis techniques such as Buffer analysis, interpolation, and Kernel density analysis (multi-distance spatial cluster analysis). It also contrasts spatial analysis with non-spatial analysis.

Keywords: aspatial technique, buffer analysis, epidemiology, interpolation

Procedia PDF Downloads 297

Authors: S. N. C. M. Dias, Niels Schuetze, Franz Lennartz

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The current focus in irrigated agriculture will move from maximizing crop production per unit area towards maximizing the crop production per unit amount of water (water productivity) used. At the same time, inadequate water supply or deficit irrigation will be the only solution to cope with water scarcity in the near future. Soil matric potential based irrigation plays an important role in such deficit irrigated agriculture to grow any crop including rice. Rice as the staple food for more than half of the world population, grows mainly under flooded conditions. It requires more water compared to other upland cereals. A major amount of this water is used in the land preparation and is lost at field level due to evaporation, deep percolation, and seepage. A field experimental study was conducted in the experimental premises of rice research and development institute of Sri Lanka in Kurunegala district to estimate the water productivity of rice under deficit irrigation. This paper presents the feasibility of improving current irrigation management in rice cultivation under water scarce conditions. The experiment was laid out in a randomized complete block design with four different irrigation treatments with three replicates. Irrigation treatments were based on soil matric potential threshold values. Treatment W0 was maintained between 60-80mbars. W1 was maintained between 80-100mbars. Other two dry treatments W2 and W3 were maintained at 100-120 mbar and 120 -140 mbar respectively. The sprinkler system was used to irrigate each plot individually upon reaching the maximum threshold value in respective treatment. Treatments were imposed two weeks after seed establishment and continued until two weeks before physiological maturity. Fertilizer applications, weed management, and other management practices were carried out per the local recommendations. Weekly plant growth measurements, daily climate parameters, soil parameters, soil tension values, and water content were measured throughout the growing period. Highest plant growth and grain yield (5.61t/ha) were observed in treatment W2 followed by W0, W1, and W3 in comparison to the reference yield (5.23t/ha) of flooded rice grown in the study area. Water productivity was highest in W3. Concerning the irrigation water savings, grain yield, and water productivity together, W2 showed the better performance. Rice grown under unsaturated conditions (W2) shows better performance compared to the continuously saturated conditions(W0). In conclusion, soil matric potential based irrigation is a promising practice in irrigation management in rice. Higher irrigation water savings can be achieved in this method. This strategy can be applied to a wide range of locations under different climates and soils. In future studies, higher soil matric potential values can be applied to evaluate the maximum possible values for rice to get higher water savings at minimum yield losses.

Keywords: irrigation, matric potential, rice, water scarcity

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Authors: Julian David Hunt, Andreas Nascimento

Abstract:

Green hydrogen is the most environmental, renewable alternative to produce hydrogen. However, an important challenge to make hydrogen a competitive energy carrier is a constant supply of renewable energy, such as solar, wind and hydropower. Given that the electricity generation potential of these sources vary seasonally and interannually, this paper proposes installing an electrolysis hydrogen production plant in a ship and move the ship to the locations where electricity is cheap, or where the seasonal potential for renewable generation is high. An example of electrolysis ship application is to produce green hydrogen with hydropower from the North region of Brazil and then sail to the Northeast region of Brazil and generate hydrogen using excess electricity from offshore wind power. The electrolysis ship concept is interesting because it has the flexibility to produce green hydrogen using the cheapest renewable electricity available in the market.

Keywords: green hydrogen, electrolysis ship, renewable energies, seasonal variations

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Authors: Thanh Noi Phan, Martin Kappas, Jan Degener

Abstract:

The currently launched Sentinel 2 (S2) satellite (June, 2015) bring a great potential and opportunities for land use/cover map applications, due to its fine spatial resolution multispectral as well as high temporal resolutions. So far, there are handful studies using S2 real data for land cover classification. Especially in northern Vietnam, to our best knowledge, there exist no studies using S2 data for land cover map application. The aim of this study is to provide the preliminary result of land cover classification using Sentinel -2 data with a rising state – of – art classifier, Random Forest. A case study with heterogeneous land use/cover in the eastern of Hanoi Capital – Vietnam was chosen for this study. All 10 spectral bands of 10 and 20 m pixel size of S2 images were used, the 10 m bands were resampled to 20 m. Among several classified algorithms, supervised Random Forest classifier (RF) was applied because it was reported as one of the most accuracy methods of satellite image classification. The results showed that the red-edge and shortwave infrared (SWIR) bands play an important role in land cover classified results. A very high overall accuracy above 90% of classification results was achieved.

Keywords: classify algorithm, classification, land cover, random forest, sentinel 2, Vietnam

Procedia PDF Downloads 362