Search results for: MSW quantity prediction

Authors: Benbiao Song, Yan Gao, Zhuo Liu

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Geostatistical modeling is the key technic for reservoir characterization, the quality of geological models will influence the prediction of reservoir performance greatly, but few studies have been done to quantify the factors impacting geostatistical reservoir modeling accuracy. In this study, 16 fluvial prototype models have been established to represent different geological complexity, 6 cases range from 16 to 361 wells were defined to reproduce all those 16 prototype models by different methodologies including SIS, object-based and MPFS algorithms accompany with different constraint parameters. Modeling accuracy ratio was defined to quantify the influence of each factor, and ten realizations were averaged to represent each accuracy ratio under the same modeling condition and parameters association. Totally 5760 simulations were done to quantify the relative contribution of each factor to the simulation accuracy, and the results can be used as strategy guide for facies modeling in the similar condition. It is founded that data density, geological trend and geological complexity have great impact on modeling accuracy. Modeling accuracy may up to 90% when channel sand width reaches up to 1.5 times of well space under whatever condition by SIS and MPFS methods. When well density is low, the contribution of geological trend may increase the modeling accuracy from 40% to 70%, while the use of proper variogram may have very limited contribution for SIS method. It can be implied that when well data are dense enough to cover simple geobodies, few efforts were needed to construct an acceptable model, when geobodies are complex with insufficient data group, it is better to construct a set of robust geological trend than rely on a reliable variogram function. For object-based method, the modeling accuracy does not increase obviously as SIS method by the increase of data density, but kept rational appearance when data density is low. MPFS methods have the similar trend with SIS method, but the use of proper geological trend accompany with rational variogram may have better modeling accuracy than MPFS method. It implies that the geological modeling strategy for a real reservoir case needs to be optimized by evaluation of dataset, geological complexity, geological constraint information and the modeling objective.

Keywords: fluvial facies, geostatistics, geological trend, modeling strategy, modeling accuracy, variogram

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Authors: Shiva Mardani, Mehdi Nasr-Esfahani, Majid Olia, Hamid Molahosseini, Hamed Hassanzadeh Khankahdani

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Plant-parasitic nematodes cause serious diseases on plants and effectively reduce food production in quality and quantity worldwide, with at least 17 nematode species in the three important and major genera, including Meloidogyne, Heterodera, and Pratylenchus. Root-knot nematodes (RKN), Meloidogyne spp. with the dominant species, Meloidogynejavanica, are considered as the important plant pathogens of agricultural products globally. The hosts range can be vegetables, bedding plants, grasses, shrubs, numerous weeds, and trees, including forests. In this study, chemical management was carried out on RKN, M. javanica, to investigate the efficacy of Iranian Abamectin insecticide product [acaricide Abamectin (Vermectin® 2% EC, Gyah Corp., Iran)] verses imported normal Abamectin available in the Iran markets [acaricide Abamectin (Vermectin® 1.8% EC, Cropstar Chemical Industry Co., Ltd.)] each of which at the rate of 8 L./ha, on Tomatoes, Solanumlycopersicum L., (No. 29-41, Dutch company Siemens) as a test plant, and the controls (infested to RKN and without any chemical pesticides treatments); and (sterile soil without any RKN and chemical pesticides treatments) at the greenhouse in Isfahan, Iran. The trails were repeated thrice. The results indicated a highly significant reduction in RKN population and an increase in biomass parameters at 1% level of significance, respectively. Relatively similar results were obtained in all the three experiments conducted on tomato root-knot nematodes. The treatments of Gyah-Abamectin (51.6%) and external Abamectin (40.4%) had the highest to least effect on reducing the number of larvae in the soil compared to the infected controls, respectively. Gyah-Abamectin by 44.1% and then external one by 31.9% had the highest effect on reducing the number of larvae and eggs in the root and 31.4% and 24.1% reduction in the number of galls compared to the infected controls, respectively. Based on priority, Gyah-Abamectin (47.4 % ) and external Abamectin (31.1 %) treatments had the highest effect on reducing the number of egg- masses in the root compared to the infected controls, with no significant difference between Gyah-Abamectin and external Abamectin. The highest reproduction of larvae and egg in the root was observed in the infected controls (75.5%) and the lowest in the healthy controls (0.0%). The highest reduction in the larval and egg reproduction in the roots compared to the infected controls was observed in Gyah-Abamectin and the lowest in the external one. Based on preference, Gyah-Abamectin (37.6%) and external Abamectin (26.9%) had the highest effect on the reduction of the larvae and egg reproduction in the root compared to the infected controls, respectively. Regarding growth parameters factors, the lowest stem length was observed in external Abamectin (51.9 cm), with nosignificantly different from Gyah-Abamectin and healthy controls. The highest root fresh weight was recorded in the infected controls (19.81 gr.) and the lowest in the healthy ones (9.81 gr.); the highest root length in the healthy controls (22.4 cm), and the lowest in the infected controls and external Abamectin (12.6 and 11.9 cm), respectively. Conclusively, the results of these three tests on tomato plants revealed that Gyah-Abamectin 2% compared to external Abamectin 1.8% is competitive in the chemical management of the root nematodes of these types of products and is a suitable alternative in this regard.

Keywords: solanum lycopersicum, vermectin, biomass, tomato

Procedia PDF Downloads 79

Authors: Meghdad Payan, Kostas Senetakis, Arman Khoshghalb, Nasser Khalili

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Dynamic properties of soils, especially at the range of very small strains, are of particular interest in geotechnical engineering practice for characterization of the behavior of geo-structures subjected to a variety of stress states. This study reports on the small-strain dynamic properties of sand-silt mixtures with particular emphasis on the effect of non-plastic fines content on the small strain shear modulus (Gmax), Young’s Modulus (Emax), material damping (Ds,min) and Poisson’s Ratio (v). Several clean sands with a wide range of grain size characteristics and particle shape are mixed with variable percentages of a silica non-plastic silt as fines content. Prepared specimens of sand-silt mixtures at different initial void ratios are subjected to sequential torsional and flexural resonant column tests with elastic dynamic properties measured along an isotropic stress path up to 800 kPa. It is shown that while at low percentages of fines content, there is a significant difference between the dynamic properties of the various samples due to the different characteristics of the sand portion of the mixtures, this variance diminishes as the fines content increases and the soil behavior becomes mainly silt-dominant, rendering no significant influence of sand properties on the elastic dynamic parameters. Indeed, beyond a specific portion of fines content, around 20% to 30% typically denoted as threshold fines content, silt is controlling the behavior of the mixture. Using the experimental results, new expressions for the prediction of small-strain dynamic properties of sand-silt mixtures are developed accounting for the percentage of silt and the characteristics of the sand portion. These expressions are general in nature and are capable of evaluating the elastic dynamic properties of sand-silt mixtures with any types of parent sand in the whole range of silt percentage. The inefficiency of skeleton void ratio concept in the estimation of small-strain stiffness of sand-silt mixtures is also illustrated.

Keywords: damping ratio, Poisson’s ratio, resonant column, sand-silt mixture, shear modulus, Young’s modulus

Procedia PDF Downloads 240

Authors: Rikke Lybæk, Tyge Kjær

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The Baltic Sea is suffering from nitrogen and phosphorus pollution, which causes eutrophication of the maritime environment and hence threatens the biodiversity of the Baltic Sea area. The intensified quantity of nutrients in the water has created challenges with the growth of seaweed being discarded on beaches around the sea. The cast seaweed has led to odor problems hampering the use of beach areas around the Bay of Køge in Denmark. This is the case in, e.g., Solrød Municipality, where recreational activities have been disrupted when cast seaweed pile up on the beach. Initiatives have, however, been introduced within the municipality to remove the cast seaweed from the beach and utilize it for renewable energy production at the nearby Solrød Biogas Plant, thus being co-digested with animal manure for power and heat production. This paper investigates which type of technology application’s have been applied in the effort to optimize the collection of cast seaweed, and will further reveal, how the seaweed has been pre-treated at the biogas plant to be utilized for energy production the most efficient, hereunder the challenges connected with the content of sand. Heavy metal contents in the seaweed and how it is managed will also be addressed, which is vital as the digestate is utilized as soil fertilizer on nearby farms. Finally, the paper will outline the energy production scheme connected to the use of seaweed as feedstock for biogas production, as well as the amount of nitrogen-rich fertilizer produced. The theoretical approach adopted in the paper relies on the thinking of Circular Bio-Economy, where biological materials are cascaded and re-circulated etc., to increase and extend their value and usability. The data for this research is collected as part of the EU Interreg project “Cluster On Anaerobic digestion, environmental Services, and nuTrients removAL” (COASTAL Biogas), 2014-2020. Data gathering consists of, e.g., interviews with relevant stakeholders connected to seaweed collection and operation of the biogas plant in Solrød Municipality. It further entails studies of progress and evaluation reports from the municipality, analysis of seaweed digestion results from scholars connected to the research, as well as studies of scientific literature to supplement the above. Besides this, observations and photo documentation have been applied in the field. This paper concludes, among others, that the seaweed harvester technology currently adopted is functional in the maritime environment close to the beachfront but inadequate in collecting seaweed directly on the beach. New technology hence needs to be developed to increase the efficiency of seaweed collection. It is further concluded that the amount of sand transported to Solrød Biogas Plant with the seaweed continues to pose challenges. The seaweed is pre-treated for sand in a receiving tank with a strong stirrer, washing off the sand, which ends at the bottom of the tank where collected. The seaweed is then chopped by a macerator and mixed with the other feedstock. The wear down of the receiving tank stirrer and the chopper are, however, significant, and new methods should be adopted.

Keywords: biogas, circular bio-economy, Denmark, maritime technology, cast seaweed, solrød municipality

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Authors: Kottaridi Klimentia, Demopoulos Vasilis, Sidiropoulos Anastasios, Ihara Diego, Nikolaidis Vasileios, Antonopoulos Dimitrios

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Aflatoxins are highly poisonous and carcinogenic compounds produced by species of the genus Aspergillus spp. that can infect a variety of agricultural foods, including dried figs. Biological and environmental factors, such as population, pathogenicity, and aflatoxinogenic capacity of the strains, topography, soil, and climate parameters of the fig orchards, are believed to have a strong effect on aflatoxin levels. Existing methods for aflatoxin detection and measurement, such as high performance liquid chromatography (HPLC), and enzyme-linked immunosorbent assay (ELISA), can provide accurate results, but the procedures are usually time-consuming, sample-destructive, and expensive. Predicting aflatoxin levels prior to crop harvest is useful for minimizing the health and financial impact of a contaminated crop. Consequently, there is interest in developing a tool that predicts aflatoxin levels based on topography and soil analysis data of fig orchards. This paper describes the development of a risk assessment tool for the contamination of aflatoxin on dried figs, based on the location and altitude of the fig orchards, the population of the fungus Aspergillus spp. in the soil, and soil parameters such as pH, saturation percentage (SP), electrical conductivity (EC), organic matter, particle size analysis (sand, silt, clay), the concentration of the exchangeable cations (Ca, Mg, K, Na), extractable P, and trace of elements (B, Fe, Mn, Zn and Cu), by employing machine learning methods. In particular, our proposed method integrates three machine learning techniques, i.e., dimensionality reduction on the original dataset (principal component analysis), metric learning (Mahalanobis metric for clustering), and k-nearest neighbors learning algorithm (KNN), into an enhanced model, with mean performance equal to 85% by terms of the Pearson correlation coefficient (PCC) between observed and predicted values.

Keywords: aflatoxins, Aspergillus spp., dried figs, k-nearest neighbors, machine learning, prediction

Procedia PDF Downloads 165

Authors: Umamaheswari Shanmugam, Silvia Ronchi

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Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that can use the large amount and variety of data generated during healthcare services every day; one of the significant advantages of these new technologies is the ability to get experience and knowledge from real-world use and to improve their performance continuously. Healthcare systems and institutions can significantly benefit because the use of advanced technologies improves the efficiency and efficacy of healthcare. Software-defined as a medical device, is stand-alone software that is intended to be used for patients for one or more of these specific medical intended uses: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, any other health conditions, replacing or modifying any part of a physiological or pathological process–manage the received information from in vitro specimens derived from the human samples (body) and without principal main action of its principal intended use by pharmacological, immunological or metabolic definition. Software qualified as medical devices must comply with the general safety and performance requirements applicable to medical devices. These requirements are necessary to ensure high performance and quality and protect patients' safety. The evolution and the continuous improvement of software used in healthcare must consider the increase in regulatory requirements, which are becoming more complex in each market. The gap between these advanced technologies and the new regulations is the biggest challenge for medical device manufacturers. Regulatory requirements can be considered a market barrier, as they can delay or obstacle the device's approval. Still, they are necessary to ensure performance, quality, and safety. At the same time, they can be a business opportunity if the manufacturer can define the appropriate regulatory strategy in advance. The abstract will provide an overview of the current regulatory framework, the evolution of the international requirements, and the standards applicable to medical device software in the potential market all over the world.

Keywords: artificial intelligence, machine learning, SaMD, regulatory, clinical evaluation, classification, international requirements, MDR, 510k, PMA, IMDRF, cyber security, health care systems

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Authors: Min Wang, Hui Tian

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Health promotion of high school students is essential for the construction of ‘Healthy China’, and increasing high school students’ physical activity is a must for their health promotion. School plays a crucial role in increasing high school students’ physical activity. Therefore, to have a comprehensive command of the school physical activity promotion strategies is of great significance for the health promotion of high school students in China and will shed some light on physical activity promotion worldwide. Literature review and interview survey are the main methods adopted for this research. It has been found that reforms of P.E. classes, improving the overall quality of P.E. teachers, and construction of school fields and facilities are among the major strategies to promote students’ physical activities. Even though it has been stipulated that primary and middle school students should take 3-4 times of P.E. classes per week, the execution is greatly influenced by the exam-oriented educational system. Randomly canceling P.E. classes or taking up the time to study other subjects is common, so it is difficult to guarantee the quantity of P.E. classes. According to national surveys, only 20%-40% of schools have 3-4 times of P.E. classes per week. In order to reduce the hindering effects of the exam-oriented educational system, a physical education test is included in the senior middle school entrance exam. The exam items include 1000m run for boys, 800m run for girls, and the basic skills for basketball/football/volleyball. The scores of the physical education test will greatly influence the admission of senior middle schools. China is now developing the ‘campus football’ policy and has established 20,000 football featured schools by 2017. Especially in these schools, football has become an important part of the students’ P.E. classes and a major means to promote students’ physical activity. As the Winter Olympics will be held in Beijing in 2022, China has promoted the ‘winter sports for all’ movement. The aim is to encourage 300 million people to winter sports, and the high school students are among the most potential participants. The primary and middle schools in Beijing have introduced winter sports to their P.E. curriculum, providing opportunities for the students to experience ice hockey and curling. Some Winter Olympics champions also go to the schools to popularize winter sports among the students. This greatly adds variety to the students’ physical activity regimen at school. In November 2017, seven ministries, including the General Administration of Sport of China and Ministry of Education of the People’s Republic of China, release Youth Sport Promotion Strategy. The strategy stipulates to strengthen the construction of youth sport facilities and implement the cultivation plan for P.E. teachers. It also emphasizes that school sport facilities should be open to students during holidays and vacations for free or at an affordable price. Overall speaking, the Chinese government stresses the importance of youth physical activity promotion and has issued a series of related policies and strategies, but the implementation still needs improvement.

Keywords: China, physical activity, promotion, school

Procedia PDF Downloads 91

Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Siddharth Ahuja, T. M. Muruganandam

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An analytical investigation is performed to study the unsteady response of a one-dimensional, non-linear dynamic shock system to external downstream pressure perturbations in a supersonic flow in a varying area duct. For a given pressure ratio across a wind tunnel, the normal shock's location can be computed as per one-dimensional steady gas dynamics. Similarly, for some other pressure ratio, the location of the normal shock will change accordingly, again computed using one-dimensional gas dynamics. This investigation focuses on the small-time interval between the first steady shock location and the new steady shock location (corresponding to different pressure ratios). In essence, this study aims to shed light on the motion of the shock from one steady location to another steady location. Further, this study aims to create the foundation of the Unsteady Gas Dynamics field enabling further insight in future research work. According to the new pressure ratio, a pressure pulse, generated at the exit of the tunnel which travels and perturbs the shock from its original position, setting it into motion. During such activity, other numerous physical phenomena also happen at the same time. However, three broad phenomena have been focused on, in this study - Traversal of a Wave, Fluid Element Interactions and Wave Interactions. The above mentioned three phenomena create, alter and kill numerous waves for different conditions. The waves which are created by the above-mentioned phenomena eventually interact with the shock and set it into motion. Numerous such interactions with the shock will slowly make it settle into its final position owing to the new pressure ratio across the duct, as estimated by one-dimensional gas dynamics. This analysis will be extremely helpful in the prediction of inlet 'unstart' of the flow in a supersonic engine intake and its prominence with the incoming flow Mach number, incoming flow pressure and the external perturbation pressure is also studied to help design more efficient supersonic intakes for engines like ramjets and scramjets.

Keywords: analytical investigation, compression and expansion waves, fluid element interactions, shock trajectory, supersonic flow, unsteady gas dynamics, varying area duct, wave interactions

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Authors: Luis Reynaldo Mota-Santiago, Angélica Lozano

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Determining appropriate measures to face earthquakesarea challenge for practitioners. In the literature, some analyses consider disaster scenarios, disregarding some important field characteristics. Sometimes, software that allows estimating the number of victims and infrastructure damages is used. Other times historical information of previous events is used, or the scenarios’informationis assumed to be available even if it isnot usual in practice. Humanitarian operations start immediately after an earthquake strikes, and the first hours in relief efforts are important; local efforts are critical to assess the situation and deliver relief supplies to the victims. A preparation action is prepositioning stockpiles, most of them at central warehouses placed away from damage-prone areas, which requires large size facilities and budget. Usually, decisions in the first 12 hours (standard relief time (SRT)) after the disaster are the location of temporary depots and the design of distribution paths. The motivation for this research was the delay in the reaction time of the early relief efforts generating the late arrival of aid to some areas after the Mexico City 7.1 magnitude earthquake in 2017. Hence, a preparation approach for planning the immediate response to earthquake disasters is proposed, intended for local governments, considering their capabilities for planning and for responding during the SRT, in order to reduce the start-up time of immediate response operations in urban areas. The first steps are the generation and analysis of disaster scenarios, which allow estimatethe relief demand before and in the early hours after an earthquake. The scenarios can be based on historical data and/or the seismic hazard analysis of an Atlas of Natural Hazards and Risk as a way to address the limited or null available information.The following steps include the decision processes for: a) locating local depots (places to prepositioning stockpiles)and aid-giving facilities at closer places as possible to risk areas; and b) designing the vehicle paths for aid distribution (from local depots to the aid-giving facilities), which can be used at the beginning of the response actions. This approach allows speeding up the delivery of aid in the early moments of the emergency, which could reduce the suffering of the victims allowing additional time to integrate a broader and more streamlined response (according to new information)from national and international organizations into these efforts. The proposed approachis applied to two case studies in Mexico City. These areas were affectedby the 2017’s earthquake, having limited aid response. The approach generates disaster scenarios in an easy way and plans a faster early response with a short quantity of stockpiles which can be managed in the early hours of the emergency by local governments. Considering long-term storage, the estimated quantities of stockpiles require a limited budget to maintain and a small storage space. These stockpiles are useful also to address a different kind of emergencies in the area.

Keywords: disaster logistics, early response, generation of disaster scenarios, preparation phase

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Authors: Suchithra V., Shreedhanya, Kavya Menon, Vidya Niranjan

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Skin metagenomics has a wide range of applications with direct relevance to the health of the organism. It gives us insight to the diverse community of microorganisms (the microbiome) harbored on the skin. In the recent years, it has become increasingly apparent that the interaction between skin microbiome and the human body plays a prominent role in immune system development, cancer development, disease pathology, and many other biological implications. Next Generation Sequencing has led to faster and better understanding of environmental organisms and their mutual interactions. This project is studying the human skin microbiome of different individuals having varied skin conditions. Bacterial 16S rRNA data of skin microbiome is downloaded from SRA toolkit provided by NCBI to perform metagenomics analysis. Twelve samples are selected with two controls, and 3 different categories, i.e., sex (male/female), skin type (moist/intermittently moist/sebaceous) and occlusion (occluded/intermittently occluded/exposed). Quality of the data is increased using Cutadapt, and its analysis is done using FastQC. USearch, a tool used to analyze an NGS data, provides a suitable platform to obtain taxonomy classification and abundance of bacteria from the metagenome data. The statistical tool used for analyzing the USearch result is METAGENassist. The results revealed that the top three abundant organisms found were: Prevotella, Corynebacterium, and Anaerococcus. Prevotella is known to be an infectious bacterium found on wound, tooth cavity, etc. Corynebacterium and Anaerococcus are opportunist bacteria responsible for skin odor. This result infers that Prevotella thrives easily in sebaceous skin conditions. Therefore it is better to undergo intermittently occluded treatment such as applying ointments, creams, etc. to treat wound for sebaceous skin type. Exposing the wound should be avoided as it leads to an increase in Prevotella abundance. Moist skin type individuals can opt for occluded or intermittently occluded treatment as they have shown to decrease the abundance of bacteria during treatment.

Keywords: bacterial 16S rRNA , next generation sequencing, skin metagenomics, skin microbiome, taxonomy

Procedia PDF Downloads 157

Authors: T. Almutairi, K. Naudi, N. Nairn, X. Ju, B. Eng, J. Whitters, A. Ayoub

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Purpose: At present Cone Beam Computed Tomography (CBCT) imaging does not record dental morphology accurately due to the scattering produced by metallic restorations and the reported magnification. The aim of this pilot study is the development and validation of a new method for the replacement of the distorted dentition of CBCT scans with the dental image captured by the digital intraoral camera. Materials and Method: Six dried skulls with orthodontics brackets on the teeth were used in this study. Three intra-oral markers made of dental stone were constructed which were attached to orthodontics brackets. The skulls were CBCT scanned, and occlusal surface was captured using TRIOS® 3D intraoral scanner. Marker based and surface based registrations were performed to fuse the digital intra-oral scan(IOS) into the CBCT models. This produced a new composite digital model of the skull and dentition. The skulls were scanned again using the commercially accurate Laser Faro® arm to produce the 'gold standard' model for the assessment of the accuracy of the developed method. The accuracy of the method was assessed by measuring the distance between the occlusal surfaces of the new composite model and the 'gold standard' 3D model of the skull and teeth. The procedure was repeated a week apart to measure the reproducibility of the method. Results: The results showed no statistically significant difference between the measurements on the first and second occasions. The absolute mean distance between the new composite model and the laser model ranged between 0.11 mm to 0.20 mm. Conclusion: The dentition of the CBCT can be accurately replaced with the dental image captured by the intra-oral scanner to create a composite model. This method will improve the accuracy of orthognathic surgical prediction planning, with the final goal of the fabrication of a physical occlusal wafer without to guide orthognathic surgery and eliminate the need for dental impression.

Keywords: orthognathic surgery, superimposition, models, cone beam computed tomography

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Authors: Zahid Khalil, Saad Ul Haque, Asif Khan

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Decision making about identifying suitable sites for any project by considering different parameters is difficult. Using GIS and Multi-Criteria Analysis (MCA) can make it easy for those projects. This technology has proved to be an efficient and adequate in acquiring the desired information. In this study, GIS and MCA were employed to identify the suitable sites for small dams in Dadu Tehsil, Sindh. The GIS software is used to create all the spatial parameters for the analysis. The parameters that derived are slope, drainage density, rainfall, land use / land cover, soil groups, Curve Number (CN) and runoff index with a spatial resolution of 30m. The data used for deriving above layers include 30-meter resolution SRTM DEM, Landsat 8 imagery, and rainfall from National Centre of Environment Prediction (NCEP) and soil data from World Harmonized Soil Data (WHSD). Land use/Land cover map is derived from Landsat 8 using supervised classification. Slope, drainage network and watershed are delineated by terrain processing of DEM. The Soil Conservation Services (SCS) method is implemented to estimate the surface runoff from the rainfall. Prior to this, SCS-CN grid is developed by integrating the soil and land use/land cover raster. These layers with some technical and ecological constraints are assigned weights on the basis of suitability criteria. The pairwise comparison method, also known as Analytical Hierarchy Process (AHP) is taken into account as MCA for assigning weights on each decision element. All the parameters and group of parameters are integrated using weighted overlay in GIS environment to produce suitable sites for the Dams. The resultant layer is then classified into four classes namely, best suitable, suitable, moderate and less suitable. This study reveals a contribution to decision-making about suitable sites analysis for small dams using geospatial data with minimal amount of ground data. This suitability maps can be helpful for water resource management organizations in determination of feasible rainwater harvesting structures (RWH).

Keywords: Remote sensing, GIS, AHP, RWH

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Authors: Carlos Minguez, Christian F. Sagbay, Erika E. Ordoñez

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Guinea pigs (Cavia porcellus) play prominent roles as experimental models for medical research and as pets. However, in developing countries like South America, the Philippines, and sub-Saharan Africa, the meat of guinea pigs is an economic source of animal protein for the poor and malnourished humans because guinea pigs are mainly fed with forage and do not compete directly with human beings for food resources, such as corn or wheat. To achieve efficient production of guinea pigs, it is essential to provide insurance against vitamin C deficiency. The objective of this research was to investigate the effect of the partial replacement of alfalfa with fresh citrus pulp (Citrus sinensis) in a diet of guinea pigs on the growth performance, slaughter traits and mortality during the fattening period (between 20 and 74 days of age). A total of 300 guinea pigs were housed in collective cages of about ten animals (2 x 1 x 0.4 m) and were distributed into two completely randomized groups. Guinea pigs in both groups were fed ad libitum, with a standard commercial pellet diet (10 MJ of digestible energy/kg, 17% crude protein, 11% crude fiber, and 4.5% crude fat). Control group was supplied with fresh alfalfa as forage. In the treatment group, 30% of alfalfa was replaced by fresh citrus pulp. Growth traits, including body weight (BW), average daily gain (ADG), feed intake (FI), and feed conversion ratio (FCR), were measured weekly. On day 74, the animals were slaughtered, and slaughter traits, including live weight at slaughter (LWS), full gastrointestinal tract weight (FGTW), hot carcass weight (with head; HCW), cold carcass weight (with head; CCW), drip loss percentage (DLP) and dressing out carcass yield percentage (DCY), were evaluated. Contrasts between groups were obtained by calculated generalized least squares values. Mortality was evaluated by Fisher's exact test due to low numbers in some cells. In the first week, there were significant differences in the growth traits BW, ADG, FI, and FCR, which were superior in control group. These differences may have been due to the origin of the young guinea pigs, which, before weaning, were all raised without fresh citrus pulp, and they were not familiarized with the new supplement. In the second week, treatment group had significantly increased ADG compared with control group, which may have been the result of a process of compensatory growth. During subsequent weeks, no significant differences were observed between animals raised in the two groups. Neither were any significant differences observed across the total fattening period. No significant differences in slaughter traits or mortality rate were observed between animals from the two groups. In conclusion, although there were no significant differences in growth performance, slaughter traits, or mortality, the use of fresh citrus pulp is recommended. Fresh citrus pulp is a by-product of orange juice industry and it is cheap or free. Forage made with fresh citrus pulp could reduce about of 30 % the quantity of alfalfa in guinea pig for meat and as consequence, reduce the production costs.

Keywords: fresh citrus, growth, Guinea pig, mortality

Procedia PDF Downloads 174

Authors: Faiz N. K. Yusufi, Aquil Ahmed, Jamal Ahmad

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Diabetes in India is growing at an alarming rate and the complications caused by it need to be controlled. Coronary heart disease (CHD) is one of the complications that will be discussed for prediction in this study. India has the second most number of diabetes patients in the world. To the best of our knowledge, there is no CHD risk score for Indian type 2 diabetes patients. Any form of CHD has been taken as the event of interest. A sample of 750 was determined and randomly collected from the Rajiv Gandhi Centre for Diabetes and Endocrinology, J.N.M.C., A.M.U., Aligarh, India. Collected variables include patients data such as sex, age, height, weight, body mass index (BMI), blood sugar fasting (BSF), post prandial sugar (PP), glycosylated haemoglobin (HbA1c), diastolic blood pressure (DBP), systolic blood pressure (SBP), smoking, alcohol habits, total cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), low density lipoprotein (LDL), very low density lipoprotein (VLDL), physical activity, duration of diabetes, diet control, history of antihypertensive drug treatment, family history of diabetes, waist circumference, hip circumference, medications, central obesity and history of CHD. Predictive risk scores of CHD events are designed by cox proportional hazard regression. Model calibration and discrimination is assessed from Hosmer Lemeshow and area under receiver operating characteristic (ROC) curve. Overfitting and underfitting of the model is checked by applying regularization techniques and best method is selected between ridge, lasso and elastic net regression. Youden’s index is used to choose the optimal cut off point from the scores. Five year probability of CHD is predicted by both survival function and Markov chain two state model and the better technique is concluded. The risk scores for CHD developed can be calculated by doctors and patients for self-control of diabetes. Furthermore, the five-year probabilities can be implemented as well to forecast and maintain the condition of patients.

Keywords: coronary heart disease, cox proportional hazard regression, ROC curve, type 2 diabetes Mellitus

Procedia PDF Downloads 206

Authors: Olalekan Lawrence Ojo

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Designing microwave terrestrial propagation networks requires a thorough evaluation of the severity of multipath fading, especially at frequencies below 10 GHz. In nations like Nigeria, without a large enough databases to support the existing empirical models, the mistakes in the prediction technique intended for the evaluation may be severe. The need for higher bandwidth for various satellite applications makes the investigation of the effects of radio refractivity, fading due to multipath, and Geoclimatic factors on satellite propagation links more important. One of the key elements to take into account for the best functioning of microwave frequencies is the clear air effects. This work has taken into account the geographical distribution of radio refractivity and fades depth over a number of stations in Nigeria. Data from five locations in Nigeria—Akure, Enugu, Jos, Minna, and Sokoto—based on five-year (2017–2021) measurement methods of atmospheric pressure, relative, and humidity temperature—at two levels (ground surface and 100 m heights)—are studied to deduced their effects on signals propagated through a µwave communication links. The assessments included considerations for µwave communication systems as well as the impacts of the dry and wet components of radio refractivity, the effects of the fade depth at various frequencies, and a 20 km link distance. The results demonstrate that the percentage occurrence of the dry terms dominated the radio refractivity constituent at the surface level, contributing a minimum of about 78% and a maximum of about 92%, while at heights of 100 meters, the percentage occurrence of the dry terms dominated the radio refractivity constituent, contributing a minimum of about 79% and a maximum of about 92%. The spatial distribution reveals that, regardless of height, the country's tropical rainforest (TRF) and freshwater swampy mangrove (FWSM) regions reported the greatest values of radio refractivity. The statistical estimate shows that fading values can differ by as much as 1.5 dB, especially near the TRF and FWSM coastlines, even during clear air conditions. The current findings will be helpful for budgeting Earth-space microwave links, particularly for the rollout of Nigeria's 5G and 6G projected microcellular networks.

Keywords: fade depth, geoclimatic factor, refractivity, refractivity gradient

Procedia PDF Downloads 60

Authors: Alireza Monzavi Chaleshtari, Maryam Aliakbari

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Objective: The aim of this study was to investigate the prediction of child attachment style based on a positive and safe combination parenting method mediated by maternal attachment styles in children with attention deficit hyperactivity disorder. Method: The design of the present study was descriptive of correlation and structural equations and applied in terms of purpose. The population of this study includes all children with attention deficit hyperactivity disorder living in Chaharmahal and Bakhtiari province and their mothers. The sample size of the above study includes 165children with attention deficit hyperactivity disorder in Chaharmahal and Bakhtiari province with their mothers, who were selected by purposive sampling method based on the inclusion criteria. The obtained data were analyzed in two sections of descriptive and inferential statistics. In the descriptive statistics section, statistical indices of mean, standard deviation, frequency distribution table and graph were used. In the inferential section, according to the nature of the hypotheses and objectives of the research, the data were analyzed using Pearson correlation coefficient tests, Bootstrap test and structural equation model. findings:The results of structural equation modeling showed that the research models fit and showed a positive and safe combination parenting style mediated by the mother attachment style has an indirect effect on the child attachment style. Also, a positive and safe combined parenting style has a direct relationship with child attachment style, and She has a mother attachment style. Conclusion:The results and findings of the present study show that there is a significant relationship between positive and safe combination parenting methods and attachment styles of children with attention deficit hyperactivity disorder with maternal attachment style mediation. Therefore, it can be expected that parents using a positive and safe combination232 parenting method can effectively lead to secure attachment in children with attention deficit hyperactivity disorder.

Keywords: child attachment style, positive and safe parenting, maternal attachment style, ADHD

Procedia PDF Downloads 45

Authors: Abdel Rahman Khider Hassan

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This paper describes a multi-criteria geospatial model for prediction of landslide hazard zonation (LHZ) for Lake Naivasha catchment (Kenya), based on spatial analysis of integrated datasets of location intrinsic parameters (slope stability factors) and external landslides triggering factors (natural and man-made factors). The intrinsic dataset included: lithology, geometry of slope (slope inclination, aspect, elevation, and curvature) and land use/land cover. The landslides triggering factors included: rainfall as the climatic factor, in addition to the destructive effects reflected by proximity of roads and drainage network to areas that are susceptible to landslides. No published study on landslides has been obtained for this area. Thus, digital datasets of the above spatial parameters were conveniently acquired, stored, manipulated and analyzed in a Geographical Information System (GIS) using a multi-criteria grid overlay technique (in ArcGIS 10.2.2 environment). Deduction of landslide hazard zonation is done by applying weights based on relative contribution of each parameter to the slope instability, and finally, the weighted parameters grids were overlaid together to generate a map of the potential landslide hazard zonation (LHZ) for the lake catchment. From the total surface of 3200 km² of the lake catchment, most of the region (78.7 %; 2518.4 km²) is susceptible to moderate landslide hazards, whilst about 13% (416 km²) is occurring under high hazards. Only 1.0% (32 km²) of the catchment is displaying very high landslide hazards, and the remaining area (7.3 %; 233.6 km²) displays low probability of landslide hazards. This result confirms the importance of steep slope angles, lithology, vegetation land cover and slope orientation (aspect) as the major determining factors of slope failures. The information provided by the produced map of landslide hazard zonation (LHZ) could lay the basis for decision making as well as mitigation and applications in avoiding potential losses caused by landslides in the Lake Naivasha catchment in the Kenya Highlands.

Keywords: decision making, geospatial, landslide, multi-criteria, Naivasha

Procedia PDF Downloads 185

Authors: Remo Waser, Simon Maranda, Anastasia Stamatiou, Ludger J. Fischer, Joerg Worlitschek

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In latent heat storage, a phase change material (PCM) is used to store thermal energy. The heat transfer rate during solidification is limited and considered as a key challenge in the development of latent heat storages. Thus, finned heat exchangers (HEX) are often utilized to increase the heat transfer rate of the storage system. In this study, a new modeling approach to calculating the heat transfer rate in latent thermal energy storages with complex HEX geometries is presented. This model allows for an optimization of the HEX design in terms of costs and thermal performance of the system. Modeling solidification processes requires the calculation of time-dependent heat conduction with moving boundaries. Commonly used computational fluid dynamic (CFD) methods enable the analysis of the heat transfer in complex HEX geometries. If applied to the entire storage, the drawback of this approach is the high computational effort due to small time steps and fine computational grids required for accurate solutions. An alternative to describe the process of solidification is the so-called temperature-based approach. In order to minimize the computational effort, a quasi-stationary assumption can be applied. This approach provides highly accurate predictions for tube heat exchangers. However, it shows unsatisfactory results for more complex geometries such as finned tube heat exchangers. The presented simulation model uses a temporal and spatial discretization of heat exchanger tube. The spatial discretization is based on the smallest possible symmetric segment of the HEX. The heat flow in each segment is calculated using finite volume method. Since the heat transfer fluid temperature can be derived using energy conservation equations, the boundary conditions at the inner tube wall is dynamically updated for each time step and segment. The model allows a prediction of the thermal performance of latent thermal energy storage systems using complex HEX geometries with considerably low computational effort.

Keywords: modelling of solidification, finned tube heat exchanger, latent thermal energy storage

Procedia PDF Downloads 253

Authors: Alessandra Turini Bolsoni-Silva, Sonia Regina Loureiro

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It is important to evaluate such variables simultaneously and differentiating types of behavior problems: internalizing, externalizing and with comorbidity of internalizing and externalizing. The objective was to compare, correlate and predict teacher educational practices (educational social skills and negative practices) and children's behaviors (social skills and behavior problems) of children with internalizing, externalizing and combined internalizing and externalizing problems, controlling variables of child (gender and education). A total of 262 children were eligible to compose the participants, considering preschool age from 3 to 5 years old (n = 109) and school age from 6 to 11 (n = 153) years old, and their teachers who were distributed, in designs case-control, non-clinical, with internalizing, externalizing problems and internalizing and externalizing comorbidity, using the Teacher's Report Form (TRF) as a criterion. The instruments were applied with the teachers, after consent from the parents/guardians: a) Teacher’s Report Form (TRF); b) Educational Social Skills Interview Guide for Teachers (RE-HSE-Pr); (c) Socially Skilled Response Questionnaire – Teachers (QRSH-Pr). The data were treated by univariate and multivariate analyses, proceeding with comparisons, correlations and predictions regarding the outcomes of children with and without behavioral problems, considering the types of problems. As main results stand out: (a) group comparison studies: in the Inter group there is emphasis on behavior problems in affection interactions, which does not happen in the other groups; as for positive practices, they discriminate against groups with externalizing and combined problems and not in internalizing ones, positive educational practices – hse are more frequent in the G-Exter and G-Inter+Exter groups; negative practices differed only in the G-Exter and G-Inter+Exter groups; b) correlation studies: it can be seen that the Inter+Exter group presents a greater number of correlations in the relationship between behavioral problems/complaints and negative practices and between children's social skills and positive practices/contexts; c) prediction studies: children's social skills predict internalizing, externalizing and combined problems; it is also verified that the negative practices are in the multivariate model for the externalizing and combined ones. This investigation collaborates in the identification of risk and protective factors for specific problems, helping in interventions for different problems.

Keywords: development, educational practices, social skills, behavior problems, teacher

Procedia PDF Downloads 63

Authors: Mohammed Al Sulaimani, Hamad Al Manhi

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With the development of Remote Sensing technology, the resolution of optical Remote Sensing images has greatly improved, and images have become largely available. Numerous detectors have been developed for detecting different types of objects. In the past few years, Remote Sensing has benefited a lot from deep learning, particularly Deep Convolution Neural Networks (CNNs). Deep learning holds great promise to fulfill the challenging needs of Remote Sensing and solving various problems within different fields and applications. The use of Unmanned Aerial Systems in acquiring Aerial Photos has become highly used and preferred by most organizations to support their activities because of their high resolution and accuracy, which make the identification and detection of very small features much easier than Satellite Images. And this has opened an extreme era of Deep Learning in different applications not only in feature extraction and prediction but also in analysis. This work addresses the capacity of Machine Learning and Deep Learning in detecting and extracting Oil Leaks from Flowlines (Onshore) using High-Resolution Aerial Photos which have been acquired by UAS fixed with RGB Sensor to support early detection of these leaks and prevent the company from the leak’s losses and the most important thing environmental damage. Here, there are two different approaches and different methods of DL have been demonstrated. The first approach focuses on detecting the Oil Leaks from the RAW Aerial Photos (not processed) using a Deep Learning called Single Shoot Detector (SSD). The model draws bounding boxes around the leaks, and the results were extremely good. The second approach focuses on detecting the Oil Leaks from the Ortho-mosaiced Images (Georeferenced Images) by developing three Deep Learning Models using (MaskRCNN, U-Net and PSP-Net Classifier). Then, post-processing is performed to combine the results of these three Deep Learning Models to achieve a better detection result and improved accuracy. Although there is a relatively small amount of datasets available for training purposes, the Trained DL Models have shown good results in extracting the extent of the Oil Leaks and obtaining excellent and accurate detection.

Keywords: GIS, remote sensing, oil leak detection, machine learning, aerial photos, unmanned aerial systems

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Authors: B. M. Vishal, Monamie Basu, Gopinath M., Rose Havilah Pulla

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Though there are several methods of synthesizing silver nano particles, Green synthesis always has its own dignity. Ranging from the cost-effectiveness to the ease of synthesis, the process is simplified in the best possible way and is one of the most explored topics. This study of extracting secondary metabolites from Perilla frutescens and using them for therapeutic additives has its own significance. Unlike the other researches that have been done so far, this study aims to synthesize Silver nano particles from Perilla frutescens using three available forms of the plant: leaves, seed, and commercial leaf extract powder. Perilla frutescens, commonly known as 'Beefsteak Plant', is a perennial plant and belongs to the mint family. The plant has two varieties classed within itself. They are frutescens crispa and frutescens frutescens. The species, frutescens crispa (commonly known as 'Shisho' in Japanese), is generally used for edible purposes. Its leaves occur in two forms, varying on the colors. It is found in two different colors of red with purple streaks and green with crinkly pattern on it. This species is aromatic due to the presence of two major compounds: polyphenols and perillaldehyde. The red (purple streak) variety of this plant is due to the presence of a pigment, Perilla anthocyanin. The species, frutescens frutescens (commonly known as 'Egoma' in Japanese), is the main source for perilla oil. This species is also aromatic, but in this case, the major compound which gives the aroma is Perilla ketone or egoma ketone. Shisho grows short as compared with Wild Sesame and both produce seeds. The seeds of Wild Sesame are large and soft whereas that of Shisho is small and hard. The seeds have a large proportion of lipids, ranging about 38-45 percent. Excluding those, the seeds have a large quantity of Omega-3 fatty acids, linoleic acid, and an Omega-6 fatty acid. Other than these, Perilla leaf extract has gold and silver nano particles in it. The yield comparison in all the cases have been done, and the process’ optimal conditions were modified, keeping in mind the efficiencies. The characterization of secondary metabolites includes GC-MS and FTIR which can be used to identify the components of purpose that actually helps in synthesizing silver nano particles. The analysis of silver was done through a series of characterization tests that include XRD, UV-Vis, EDAX, and SEM. After the synthesis, for being used as therapeutic additives, the toxin analysis was done, and the results were tabulated. The synthesis of silver nano particles was done in a series of multiple cycles of extraction from leaves, seeds and commercially purchased leaf extract. The yield and efficiency comparison were done to bring out the best and the cheapest possible way of synthesizing silver nano particles using Perilla frutescens. The synthesized nano particles can be used in therapeutic drugs, which has a wide range of application from burn treatment to cancer treatment. This will, in turn, replace the traditional processes of synthesizing nano particles, as this method will prove effective in terms of cost and the environmental implications.

Keywords: nanoparticles, green synthesis, Perilla frutescens, characterisation, toxin analysis

Procedia PDF Downloads 216

Authors: Nicola Menga, Giuseppe Carbone

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Although contact mechanics has been widely focused on the study of contacts between half-space, it has been recently pointed out that in presence of finite thickness elastic layers the results of the contact problem show significant difference in terms of the main contact quantities (e.g. contact area, penetration, mean pressure, etc.). Actually, there exist a wide range of industrial application demanding for this kind of studies, such as seals leakage prediction or pressure-sensitive coatings for electrical applications. In this work, we focus on the contact between a rigid profile and an elastic layer of thickness h confined under two different configurations: rigid constrain and applied uniform pressure. The elastic problem at hand has been formalized following Green’s function method and then numerically solved by means of a matrix inversion. We study different contact conditions, both considering and neglecting adhesive interactions at the interface. This leads to different solution techniques: Adhesive contacts equilibrium solution is found, in term of contact area for given penetration, making stationary the total free energy of the system; whereas, adhesiveless contacts are addressed defining an equilibrium criterion, again on the contact area, relying on the fracture mechanics stress intensity factor KI. In particular, we make the KI vanish at the edges of the contact area, as peculiar for adhesiveless elastic contacts. The results are obtained in terms of contact area, penetration, and mean pressure for both adhesive and adhesiveless contact conditions. As expected, in the case of a uniform applied pressure the slab turns out much more compliant than the rigidly constrained one. Indeed, we have observed that the peak value of the contact pressure, for both the adhesive and adhesiveless condition, is much higher for the rigidly constrained configuration than in the case of applied uniform pressure. Furthermore, we observed that, for little contact area, both systems behave the same and the pull-off occurs at approximately the same contact area and mean contact pressure. This is an expected result since in this condition the ratio between the layers thickness and the contact area is very high and both layer configurations recover the half-space behavior where the pull-off occurrence is mainly controlled by the adhesive interactions, which are kept constant among the cases.

Keywords: contact mechanics, adhesion, friction, thick layer

Procedia PDF Downloads 491

Authors: Ippei Torii, Kaoruko Ohtani, Takahito Niwa, Naohiro Ishii

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This paper shows developing an objectivity index using the measurement of subtle eyeball movement to diagnose autism. The developmentally disabled assessment varies, and the diagnosis depends on the subjective judgment of professionals. Therefore, a supplementary inspection method that will enable anyone to obtain the same quantitative judgment is needed. The diagnosis are made based on a comparison of the time of gazing an object in the conventional autistic study, but the results do not match. First, we divided the pupil into four parts from the center using measurements of subtle eyeball movement and comparing the number of pixels in the overlapping parts based on an afterimage. Then we developed the objective evaluation indicator to judge non-autistic and autistic people more clearly than conventional methods by analyzing the differences of subtle eyeball movements between the right and left eyes. Even when a person gazes at one point and his/her eyeballs always stay fixed at that point, their eyes perform subtle fixating movements (ie. tremors, drifting, microsaccades) to keep the retinal image clear. Particularly, the microsaccades link with nerves and reflect the mechanism that process the sight in a brain. We converted the differences between these movements into numbers. The process of the conversion is as followed: 1) Select the pixel indicating the subject's pupil from images of captured frames. 2) Set up a reference image, known as an afterimage, from the pixel indicating the subject's pupil. 3) Divide the pupil of the subject into four from the center in the acquired frame image. 4) Select the pixel in each divided part and count the number of the pixels of the overlapping part with the present pixel based on the afterimage. 5) Process the images with precision in 24 - 30fps from a camera and convert the amount of change in the pixels of the subtle movements of the right and left eyeballs in to numbers. The difference in the area of the amount of change occurs by measuring the difference between the afterimage in consecutive frames and the present frame. We set the amount of change to the quantity of the subtle eyeball movements. This method made it possible to detect a change of the eyeball vibration in numerical value. By comparing the numerical value between the right and left eyes, we found that there is a difference in how much they move. We compared the difference in these movements between non-autistc and autistic people and analyzed the result. Our research subjects consists of 8 children and 10 adults with autism, and 6 children and 18 adults with no disability. We measured the values through pasuit movements and fixations. We converted the difference in subtle movements between the right and left eyes into a graph and define it in multidimensional measure. Then we set the identification border with density function of the distribution, cumulative frequency function, and ROC curve. With this, we established an objective index to determine autism, normal, false positive, and false negative.

Keywords: subtle eyeball movement, autism, microsaccade, pursuit eye movements, ROC curve

Procedia PDF Downloads 267

Authors: Mathias Cehlin, Arman Ameen, Ulf Larsson, Taghi Karimipanah

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The indoor environmental quality (IEQ) is increasingly recognized as a significant factor influencing the overall level of building occupants’ health, comfort and productivity. An air-conditioning and ventilation system is normally used to create and maintain good thermal comfort and indoor air quality. Providing occupant thermal comfort and well-being with minimized use of energy is the main purpose of heating, ventilating and air conditioning system. Among different types of ventilation systems, the most widely known and used ventilation systems are mixing ventilation (MV) and displacement ventilation (DV). Impinging jet ventilation (IJV) is a promising ventilation strategy developed in the beginning of 2000s. IJV has the advantage of supplying air downwards close to the floor with high momentum and thereby delivering fresh air further out in the room compare to DV. Operating in cooling mode, IJV systems can have higher ventilation effectiveness and heat removal effectiveness compared to MV, and therefore a higher energy efficiency. However, how is the performance of IJV when operating in heating mode? This paper presents the function of IJV in a typical office room for winter conditions (heating mode). In this paper, a validated CFD model, which uses the v2-f model is used for the prediction of air flow pattern, thermal comfort and air change effectiveness. The office room under consideration has the dimensions 4.2×3.6×2.5m, which can be designed like a single-person or two-person office. A number of important factors influencing in the room with IJV are studied. The considered parameters are: heating demand, number of occupants and supplied air conditions. A total of 6 simulation cases are carried out to investigate the effects of the considered parameters. Heat load in the room is contributed by occupants, computer and lighting. The model consists of one external wall including a window. The interaction effects of heat sources, supply air flow and down draught from the window result in a complex flow phenomenon. Preliminary results indicate that IJV can be used for heating of a typical office room. The IEQ seems to be suitable in the occupied region for the studied cases.

Keywords: computation fluid dynamics, impinging jet ventilation, indoor environmental quality, ventilation strategy

Procedia PDF Downloads 162

Authors: Abdulkadir Sarauta

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Almost every type of industrial process involves the release of trace quantity of toxic organic and inorganic compound that up in receiving water bodies, this study was aimed at assessing the Persistent Organic Pollutant Level in Challawa River Basin of Kano State, Nigeria. And the research formed the basis of identifying the presence of PCBs and PAHs in receiving water bodies in the study area, assessing the PCBs and PAHs concentration in receiving water body of Challawa system, evaluate the concentration level of PCBs and PAHs in fishes in the study area, determine the concentration level of PCBs and PAHs in crops irrigated in the study area as well as compare the concentration of PCBs and PAHs with the acceptable limit set by Nigerian, EU, U.S and WHO standard. Data were collected using reconnaissance survey, site inspection, field survey, laboratory experiment as well as secondary data source. A total of 78 samples were collected through stratified systematic random sampling (i.e., 26 samples for each of water, crops and fish) three sampling points were chosen and designated A, B and C along the stretch of the river (i.e. up, middle, and downstream) from Yan Danko Bridge to Tambirawa bridge. The result shows that the Polychlorinated biphenyls (PCBs) was not detected while, polycyclic aromatic hydrocarbons (PAHs) was detected in the whole samples analysed at the trench of Challawa River basin in order to assess the contribution of human activities to global environmental pollution. The total concentrations of ΣPAH and ΣPCB ranges between 0.001 to 0.087mg/l and 0.00 to 0.00mg/l of water samples While, crops samples ranges between 2.0ppb to 8.1ppb and fish samples ranges from 2.0 to 6.7ppb.The whole samples are polluted because most of the parameters analyzed exceed the threshold limits set by WHO, Nigerian, U.S and EU standard. The analytical results revealed that some chemicals are present in water, crops and fishes are significantly very high at Zamawa village which is very close to Challawa industrial estate and also is main effluent discharge point and drinking water around study area is not potable for consumption. Analysis of Variance was obtained by Bartlett’s test performance. There is only significant difference in water because the P < 0.05 level of significant, But there is no difference in crops concentration they have the same performance, likes wise in the fishes. It is said to be of concern to health hazard which will increase incidence of tumor related diseases such as skin, lungs, bladder, gastrointestinal cancer, this show there is high failure of pollution abatement measures in the area. In conclusion, it can be said that industrial activities and effluent has impact on Challawa River basin and its environs especially those that are living in the immediate surroundings. Arising from the findings of this research some recommendations were made the industries should treat their liquid properly by installing modern treatment plants.

Keywords: Challawa River Basin, organic, persistent, pollutant

Procedia PDF Downloads 562

Authors: S. K. Verma, S. L. Sinha, D. K. Chandraker

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The Advanced Heavy Water Reactor (AHWR) is a vertical pressure tube type, heavy water moderated and boiling light water cooled natural circulation based reactor. The fuel bundle of AHWR contains 54 fuel rods arranged in three concentric rings of 12, 18 and 24 fuel rods. This fuel bundle is divided into a number of imaginary interacting flow passage called subchannels. Single phase flow condition exists in reactor rod bundle during startup condition and up to certain length of rod bundle when it is operating at full power. Prediction of the thermal margin of the reactor during startup condition has necessitated the determination of the turbulent mixing rate of coolant amongst these subchannels. Thus, it is vital to evaluate turbulent mixing between subchannels of AHWR rod bundle. With the remarkable progress in the computer processing power, the computational fluid dynamics (CFD) methodology can be useful for investigating the thermal–hydraulic characteristics phenomena in the nuclear fuel assembly. The present report covers the results of simulation of pressure drop, velocity variation and turbulence intensity on single rod bundle with 54 rods in circular arrays. In this investigation, 54-rod assemblies are simulated with ANSYS Fluent 15 using steady simulations with an ANSYS Workbench meshing. The simulations have been carried out with water for Reynolds number 9861.83. The rod bundle has a mean flow area of 4853.0584 mm2 in the bare region with the hydraulic diameter of 8.105 mm. In present investigation, a benchmark k-ε model has been used as a turbulence model and the symmetry condition is set as boundary conditions. Simulation are carried out to determine the turbulent mixing rate in the simulated subchannels of the reactor. The size of rod and the pitch in the test has been same as that of actual rod bundle in the prototype. Water has been used as the working fluid and the turbulent mixing tests have been carried out at atmospheric condition without heat addition. The mean velocity in the subchannel has been varied from 0-1.2 m/s. The flow conditions are found to be closer to the actual reactor condition.

Keywords: AHWR, CFD, single-phase turbulent mixing rate, thermal–hydraulic

Procedia PDF Downloads 305

Authors: M. Cabrera, W. Tizani, J. Ninic, F. Wang

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Open section beam to concrete-filled tubular column structures has been increasingly utilized in construction over the past few decades due to their enhanced structural performance, as well as economic and architectural advantages. However, the use of this configuration in construction is limited due to the difficulties in connecting the structural members as there is no access to the inner part of the tube to install standard bolts. Blind-bolted systems are a relatively new approach to overcome this limitation as they only require access to one side of the tubular section to tighten the bolt. The performance of these connections in concrete-filled steel tubular sections remains uncharacterized due to the complex interactions between concrete, bolt, and steel section. Over the last years, research in structural performance has moved to a more sophisticated and efficient approach consisting of machine learning algorithms to generate metamodels. This method reduces the need for developing complex, and computationally expensive finite element models, optimizing the search for desirable design variables. Metamodels generated by a data fusion approach use numerical and experimental results by combining multiple models to capture the dependency between the simulation design variables and connection performance, learning the relations between different design parameters and predicting a given output. Fully characterizing this connection will transform high-rise and multistorey construction by means of the introduction of design guidance for moment-resisting blind-bolted connections, which is currently unavailable. This paper presents a review of the steps taken to develop metamodels generated by means of artificial neural network algorithms which predict the connection stress and stiffness based on the design parameters when using Extended Hollo-Bolt blind bolts. It also provides consideration of the failure modes and mechanisms that contribute to the deformability as well as the feasibility of achieving blind-bolted rigid connections when using the blind fastener.

Keywords: blind-bolted connections, concrete-filled tubular structures, finite element analysis, metamodeling

Procedia PDF Downloads 145

Authors: Altayeb Abdalla Ahmed

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Skeletal phenotype is a product of a balanced interaction between genetics and environmental factors throughout different life stages. Therefore, interlimb proportions are variable between populations. Although interlimb proportion indices have been used in anthropology in assessing the influence of various environmental factors on limbs, an extensive literature review revealed that there is a paucity of published research assessing interlimb part correlations and possibility of reconstruction. Hence, this study aims to assess the relationships between upper and lower limb parts and develop regression formulae to reconstruct the parts from one another. The left upper arm length, ulnar length, wrist breadth, hand length, hand breadth, tibial length, bimalleolar breadth, foot length, and foot breadth of 376 right-handed subjects, comprising 187 males and 189 females (aged 25-35 years), were measured. Initially, the data were analyzed using basic univariate analysis and independent t-tests; then sex-specific simple and multiple linear regression models were used to estimate upper limb parts from lower limb parts and vice-versa. The results of this study indicated significant sexual dimorphism for all variables. The results indicated a significant correlation between the upper and lower limbs parts (p < 0.01). Linear and multiple (stepwise) regression equations were developed to reconstruct the limb parts in the presence of a single or multiple dimension(s) from the other limb. Multiple stepwise regression equations generated better reconstructions than simple equations. These results are significant in forensics as it can aid in identification of multiple isolated limb parts particularly during mass disasters and criminal dismemberment. Although a DNA analysis is the most reliable tool for identification, its usage has multiple limitations in undeveloped countries, e.g., cost, facility availability, and trained personnel. Furthermore, it has important implication in plastic and orthopedic reconstructive surgeries. This study is the only reported study assessing the correlation and prediction capabilities between many of the upper and lower dimensions. The present study demonstrates a significant correlation between the interlimb parts in both sexes, which indicates a possibility to reconstruction using regression equations.

Keywords: anthropometry, correlation, limb, Sudanese

Procedia PDF Downloads 281

Authors: Rida Wanbha Nongbri, Sabuj Kumar Mandal

Abstract:

The Sustainable Development Goals (SDGs) for 2016-2030 were adopted in response to Millennium Development Goals (MDGs) which focused on access to sustainable water and sanitations. For over a decade, water has been a significant subject that is explored in various facets of life. Our day-to-day life is significantly impacted by water poverty at the socio-economic level. Reducing water poverty is an important policy challenge, particularly in emerging economies like India, owing to its population growth, huge variation in topology and climatic factors. To design appropriate water policies and its effectiveness, a proper measurement of water poverty is essential. In this backdrop, this study uses the Alkire Foster (AF) methodology to estimate a multidimensional water poverty index for India at the household level. The methodology captures several attributes to understand the complex issues related to households’ water deprivation. The study employs two rounds of Indian Human Development Survey data (IHDS 2005 and 2012) which focuses on 4 dimensions of water poverty including water access, water quantity, water quality, and water capacity, and seven indicators capturing these four dimensions. In order to quantify water deprivation at the household level, an AF dual cut-off counting method is applied and Multidimensional Water Poverty Index (MWPI) is calculated as the product of Headcount Ratio (Incidence) and average share of weighted dimension (Intensity). The results identify deprivation across all dimensions at the country level and show that a large proportion of household in India is deprived of quality water and suffers from water access in both 2005 and 2012 survey rounds. The comparison between the rural and urban households shows that higher ratio of the rural households are multidimensionally water poor as compared to their urban counterparts. Among the four dimensions of water poverty, water quality is found to be the most significant one for both rural and urban households. In 2005 round, almost 99.3% of households are water poor for at least one of the four dimensions, and among the water poor households, the intensity of water poverty is 54.7%. These values do not change significantly in 2012 round, but we could observe significance differences across the dimensions. States like Bihar, Tamil Nadu, and Andhra Pradesh are ranked the most in terms of MWPI, whereas Sikkim, Arunachal Pradesh and Chandigarh are ranked the lowest in 2005 round. Similarly, in 2012 round, Bihar, Uttar Pradesh and Orissa rank the highest in terms of MWPI, whereas Goa, Nagaland and Arunachal Pradesh rank the lowest. The policy implications of this study can be multifaceted. It can urge the policy makers to focus either on the impoverished households with lower intensity levels of water poverty to minimize total number of water poor households or can focus on those household with high intensity of water poverty to achieve an overall reduction in MWPI.

Keywords: .alkire-foster (AF) methodology, deprivation, dual cut-off, multidimensional water poverty index (MWPI)

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