Search results for: food composition data

Authors: Poramatdha Chutimant

Abstract:

The objective of the research was to propose a model of teacher leadership in history instruction for utilization. Everett M. Rogers’ Diffusion of Innovations Theory is applied as theoretical framework. Qualitative method is to be used in the study, and the interview protocol used as an instrument to collect primary data from best practices who awarded by Office of National Education Commission (ONEC). Open-end questions will be used in interview protocol in order to gather the various data. Then, information according to international context of history instruction is the secondary data used to support in the summarizing process (Content Analysis). Dendrogram is a key to interpret and synthesize the primary data. Thus, secondary data comes as the supportive issue in explanation and elaboration. In-depth interview is to be used to collected information from seven experts in educational field. The focal point is to validate a draft model in term of future utilization finally.

Keywords: history study, nationalism, patriotism, responsible citizenship, teacher leadership

Procedia PDF Downloads 280

Authors: Mohammad Anwar, Shah Waliullah

Abstract:

This study investigated panel data regression models. This paper used Bayesian and classical methods to study the impact of institutions on economic growth from data (1990-2014), especially in developing countries. Under the classical and Bayesian methodology, the two-panel data models were estimated, which are common effects and fixed effects. For the Bayesian approach, the prior information is used in this paper, and normal gamma prior is used for the panel data models. The analysis was done through WinBUGS14 software. The estimated results of the study showed that panel data models are valid models in Bayesian methodology. In the Bayesian approach, the effects of all independent variables were positively and significantly affected by the dependent variables. Based on the standard errors of all models, we must say that the fixed effect model is the best model in the Bayesian estimation of panel data models. Also, it was proved that the fixed effect model has the lowest value of standard error, as compared to other models.

Keywords: Bayesian approach, common effect, fixed effect, random effect, Dynamic Random Effect Model

Procedia PDF Downloads 68

Authors: Nuhu Mohammed Gali, Kenichi Matsui

Abstract:

Climate change poses a significant threat to agriculture and food security in Africa. The UNFCC recognized the need to address climate change adaptation in the broader context of sustainable development. African countries have initiated a governance system for adapting and responding to climate change in their Nationally Determined Contributions (NDCs). Despite the implementation limitations, Africa’s adaptation initiatives highlight the need to strengthen and expand adaptation responses. This paper looks at the extent to which South-South cooperation facilitates the implementation of adaptation actions between nations for agriculture and sustainable development. We conducted a literature review and content analysis of reports prepared by international organizations, reflecting the diversity of adaptation activities taking place in Sub-Saharan Africa. Our analysis of the connection between adaptation and nationally determined contributions (NDCs) showed that climate actions are mainstreamed into sustainable development. The NDCs in many countries on climate change adaptation action for agriculture aimed to strengthen the resilience of the poor. We found that climate-smart agriculture is the core of many countries target to end hunger. We revealed that South-South Cooperation, in terms of capacity, technology, and financial support, can help countries to achieve their climate action priorities and the Sustainable Development Goals (SDGs). We found that inadequate policy and regulatory frameworks between countries, differences in development priorities and strategies, poor communication, inadequate coordination, and the lack of local engagement and advocacy are some key barriers to South-South Cooperation in Africa. We recommend a multi-dimensional partnership, provisionoffinancialresources, systemic approach for coordination and engagement to promote and achieve the potential of SSC in Africa.

Keywords: climate change, adaptation, food security, sustainable development goals

Procedia PDF Downloads 129

Authors: Saif Al Ghafri, Thomas Hughes, Armand Karimi, Kumarini Seneviratne, Jordan Oakley, Michael Johns, Eric F. May

Abstract:

Knowledge of the thermophysical properties of complex mixtures at extreme conditions of pressure and temperature have always been essential to the Liquefied Natural Gas (LNG) industry’s evolution because of the tremendous technical challenges present at all stages in the supply chain from production to liquefaction to transport. Each stage is designed using predictions of the mixture’s properties, such as density, viscosity, surface tension, heat capacity and phase behaviour as a function of temperature, pressure, and composition. Unfortunately, currently available models lead to equipment over-designs of 15% or more. To achieve better designs that work more effectively and/or over a wider range of conditions, new fundamental property data are essential, both to resolve discrepancies in our current predictive capabilities and to extend them to the higher-pressure conditions characteristic of many new gas fields. Furthermore, innovative experimental techniques are required to measure different thermophysical properties at high pressures and over a wide range of temperatures, including near the mixture’s critical points where gas and liquid become indistinguishable and most existing predictive fluid property models used breakdown. In this work, we present a wide range of experimental measurements made for different binary and ternary mixtures relevant to LNG processing, with a particular focus on viscosity, surface tension, heat capacity, bubble-points and density. For this purpose, customized and specialized apparatus were designed and validated over the temperature range (200 to 423) K at pressures to 35 MPa. The mixtures studied were (CH4 + C3H8), (CH4 + C3H8 + CO2) and (CH4 + C3H8 + C7H16); in the last of these the heptane contents was up to 10 mol %. Viscosity was measured using a vibrating wire apparatus, while mixture densities were obtained by means of a high-pressure magnetic-suspension densimeter and an isochoric cell apparatus; the latter was also used to determine bubble-points. Surface tensions were measured using the capillary rise method in a visual cell, which also enabled the location of the mixture critical point to be determined from observations of critical opalescence. Mixture heat capacities were measured using a customised high-pressure differential scanning calorimeter (DSC). The combined standard relative uncertainties were less than 0.3% for density, 2% for viscosity, 3% for heat capacity and 3 % for surface tension. The extensive experimental data gathered in this work were compared with a variety of different advanced engineering models frequently used for predicting thermophysical properties of mixtures relevant to LNG processing. In many cases the discrepancies between the predictions of different engineering models for these mixtures was large, and the high quality data allowed erroneous but often widely-used models to be identified. The data enable the development of new or improved models, to be implemented in process simulation software, so that the fluid properties needed for equipment and process design can be predicted reliably. This in turn will enable reduced capital and operational expenditure by the LNG industry. The current work also aided the community of scientists working to advance theoretical descriptions of fluid properties by allowing to identify deficiencies in theoretical descriptions and calculations.

Keywords: LNG, thermophysical, viscosity, density, surface tension, heat capacity, bubble points, models

Procedia PDF Downloads 274

Authors: Monika Patel, Kazuaki Matsumura

Abstract:

Synthetic hydrogels, with their unique properties such as porosity, strength, and swelling in aqueous environment, are being used in many fields from food additives to regenerative medicines, from diagnostic and pharmaceuticals to drug delivery systems (DDS). But, hydrogels also have some limitations in terms of homogeneity of drug distribution and quantity of loaded drugs. As an alternate, polymeric micelles are extensively used as DDS. With the ease of self-assembly, and distinct stability they remarkably improve the solubility of hydrophobic drugs. However, presently, combinational therapy is the need of time and so are systems which are capable of releasing more than one drug. And it is one of the major challenges towards DDS to control the release of each drug independently, which simple DDS cannot meet. In this work, we present an amphiphilic polypeptide based micelle hydrogel composite to study the dual drug release for wound healing purposes using Amphotericin B (AmpB) and Curcumin as model drugs. Firstly, two differently charged amphiphilic polypeptide chains were prepared namely, poly L-Lysine-b-poly phenyl alanine (PLL-PPA) and poly Glutamic acid-b-poly phenyl alanine (PGA-PPA) through ring opening polymerization of amino acid N-carboxyanhydride. These polymers readily self-assemble to form micelles with hydrophobic PPA block as core and hydrophilic PLL/PGA as shell with an average diameter of about 280nm. The thus formed micelles were loaded with the model drugs. The PLL-PPA micelle was loaded with curcumin and PGA-PPA was loaded with AmpB by dialysis method. Drug loaded micelles showed a slight increase in the mean diameter and were fairly stable in solution and lyophilized forms. For forming the micelles hydrogel composite, the drug loaded micelles were dissolved and were cross linked using genipin. Genipin uses the free –NH2 groups in the PLL-PPA micelles to form a hydrogel network with free PGA-PPA micelles trapped in between the 3D scaffold formed. Different composites were tested by changing the weight ratios of the both micelles and were seen to alter its resulting surface charge from positive to negative with increase in PGA-PPA ratio. The composites with high surface charge showed a burst release of drug in initial phase, were as the composites with relatively low net charge showed a sustained release. Thus the resultant surface charge of the composite can be tuned to tune its drug release profile. Also, while studying the degree of cross linking among the PLL-PPA particles for effect on dual drug release, it was seen that as the degree of crosslinking increases, an increase in the tendency to burst release the drug (AmpB) is seen in PGA-PPA particle, were as on the contrary the PLL-PPA particles showed a slower release of Curcumin with increasing the cross linking density. Thus, two different pharmacokinetic profile of drugs were seen by changing the cross linking degree. In conclusion, a unique charged amphiphilic polypeptide based micelle hydrogel composite for dual drug delivery. This composite can be finely tuned on the basis of need of drug release profiles by changing simple parameters such as composition, cross linking and pH.

Keywords: amphiphilic polypeptide, dual drug release, micelle hydrogel composite, tunable DDS

Procedia PDF Downloads 207

Authors: Sule Yucelbas, Gulay Tezel, Cuneyt Yucelbas, Seral Ozsen

Abstract:

In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other. As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.

Keywords: AIS, ANN, ECG, hybrid classifiers, PSO

Procedia PDF Downloads 442

Authors: Phumelele Kubheka, Pius Owolawi, Gbolahan Aiyetoro

Abstract:

Twitter is one of the most popular social media platforms where users can share their opinions on different subjects. As of 2010, The Twitter platform generates more than 12 Terabytes of data daily, ~ 4.3 petabytes in a single year. For this reason, Twitter is a great source for big mining data. Many industries such as Telecommunication companies can leverage the availability of Twitter data to better understand their markets and make an appropriate business decision. This study performs topic modeling on Twitter data using Latent Dirichlet Allocation (LDA). The obtained results are benchmarked with another topic modeling technique, Latent Semantic Indexing (LSI). The study aims to retrieve topics on a Twitter dataset containing user tweets on South African Telcos. Results from this study show that LSI is much faster than LDA. However, LDA yields better results with higher topic coherence by 8% for the best-performing model represented in Table 1. A higher topic coherence score indicates better performance of the model.

Keywords: big data, latent Dirichlet allocation, latent semantic indexing, telco, topic modeling, twitter

Procedia PDF Downloads 150

Authors: Ayten Bakhtiyar Khasayeva

Abstract:

Lower Kura depression is a part of the South Caspian Basin (SCB), located between the folded regions of the Greater and Lesser Caucasus. The region is characterized by thick sedimentary cover 22 km (SCB up to 30 km), high sedimentation rate, low geothermal gradient (average value corresponds to 2 °C / 100m). There is Quaternary, Pliocene, Miocene and Oligocene deposits take part in geological structure. Miocene and Oligocene deposits are opened by prospecting and exploratory wells in the areas of Kalamaddin and Garabagli. There are 25 mud volcanoes within the territory of the Lower Kura depression, which are the unique source of information about hydrocarbons contenting great depths. During the wells data research, solid erupted products and mud volcano fluids, and according to the geological and thermal characteristics of the region, it was determined that the main phase of the hydrocarbon generation (MK1-AK2) corresponds to a wide range of depths from 10 to 14 km, which corresponds to the Pliocene-Miocene sediments, and to the "oil and gas windows" according to the intended meaning of R0 ≈ 0,65-0,85%. Fluids of mud volcanoes comprise by the following phases - gas, water. Gas phase consists mainly of methane (99%) of heavy hydrocarbons (С2+ hydrocarbons), CO2, N2, inert components He, Ar. The content of the С2+ hydrocarbons in the gases of mud volcanoes associated with oil deposits is increased. Carbon isotopic composition of methane for the Lower Kura depression varies from -40 ‰ to -60 ‰. Water of mud volcanoes are represented by all four genetic types. However the most typical types of water are HCN type. According to the Mg-Li geothermometer formation of mud waters corresponds to the temperature range from 20 °C to 140 °C (PC2). The solid product emissions of mud volcanoes identified 90 minerals and 30 trace elements. As a result geochemical investigation, thermobaric and geological conditions, zone oil and gas generation - the prospect of the Lower Kura depression is projected to depths greater than 10 km.

Keywords: geology, geochemistry, mud volcanoes, petroleum potential

Procedia PDF Downloads 366

Authors: Yu Zhang, Pedro Desouza

Abstract:

Since big data has become substantially more accessible and manageable due to the development of powerful tools for dealing with unstructured data, people are eager to mine information from social media resources that could not be handled in the past. Sentiment analysis, as a novel branch of text mining, has in the last decade become increasingly important in marketing analysis, customer risk prediction and other fields. Scientists and researchers have undertaken significant work in creating and improving their sentiment models. In this paper, we present a concept of selecting appropriate classifiers based on the features and qualities of data sources by comparing the performances of five classifiers with three popular social media data sources: Twitter, Amazon Customer Reviews, and Movie Reviews. We introduced a couple of innovative models that outperform traditional sentiment classifiers for these data sources, and provide insights on how to further improve the predictive power of sentiment analysis. The modelling and testing work was done in R and Greenplum in-database analytic tools.

Keywords: sentiment analysis, social media, Twitter, Amazon, data mining, machine learning, text mining

Procedia PDF Downloads 353

Authors: Abbas Raza Ali

Abstract:

Big Data technology is gradually becoming a dire need of large enterprises. These enterprises are generating massively large amount of off-line and streaming data in both structured and unstructured formats on daily basis. It is a challenging task to effectively extract useful insights from the large scale datasets, even though sometimes it becomes a technology constraint to manage transactional data history of more than a few months. This paper presents a framework to efficiently manage massively large and complex datasets. The framework has been tested on a communication service provider producing massively large complex streaming data in binary format. The communication industry is bound by the regulators to manage history of their subscribers’ call records where every action of a subscriber generates a record. Also, managing and analyzing transactional data allows service providers to better understand their customers’ behavior, for example, deep packet inspection requires transactional internet usage data to explain internet usage behaviour of the subscribers. However, current relational database systems limit service providers to only maintain history at semantic level which is aggregated at subscriber level. The framework addresses these challenges by leveraging Big Data technology which optimally manages and allows deep analysis of complex datasets. The framework has been applied to offload existing Intelligent Network Mediation and relational Data Warehouse of the service provider on Big Data. The service provider has 50+ million subscriber-base with yearly growth of 7-10%. The end-to-end process takes not more than 10 minutes which involves binary to ASCII decoding of call detail records, stitching of all the interrogations against a call (transformations) and aggregations of all the call records of a subscriber.

Keywords: big data, communication service providers, enterprise data warehouse, stream computing, Telco IN Mediation

Procedia PDF Downloads 175

Authors: Peter M. Maurer Maurer

Abstract:

DGL is a context free grammar-based tool for generating random data. Many types of simulator input data require some computation to be placed in the proper format. For example, it might be necessary to generate ordered triples in which the third element is the sum of the first two elements, or it might be necessary to generate random numbers in some sorted order. Although DGL is universal in computational power, generating these types of data is extremely difficult. To overcome this problem, we have enhanced DGL to include features that permit direct computation within the structure of a context free grammar. The features have been implemented as special types of productions, preserving the context free flavor of DGL specifications.

Keywords: DGL, Enhanced Context Free Grammars, Programming Constructs, Random Data Generation

Procedia PDF Downloads 147

Authors: Ouzayr Rabhi, Ibtissam Arrassen

Abstract:

To provide a complete analysis of the organization and to help decision-making, leaders need to have relevant data; Data Warehouses (DW) are designed to meet such needs. However, designing DW is not trivial and there is no formal method to derive a multidimensional schema from heterogeneous databases. In this article, we present a Model-Driven based approach concerning the design of data warehouses. We describe a multidimensional meta-model and also specify a set of transformations starting from a Unified Modeling Language (UML) metamodel. In this approach, the UML metamodel and the multidimensional one are both considered as a platform-independent model (PIM). The first meta-model is mapped into the second one through transformation rules carried out by the Query View Transformation (QVT) language. This proposal is validated through the application of our approach to generating a multidimensional schema of a Balanced Scorecard (BSC) DW. We are interested in the BSC perspectives, which are highly linked to the vision and the strategies of an organization.

Keywords: data warehouse, meta-model, model-driven architecture, transformation, UML

Procedia PDF Downloads 160

Authors: A. Evcin, N. Çiçek Bezir, R. Duman, N. Duman

Abstract:

Nowadays, a great concern is placed on the harmfulness of ultraviolet radiation (UVR) which attacks human bodies. Nanocarbon materials, such as carbon nanotubes (CNTs), carbon nanofibers (CNFs) and graphene, have been considered promising alternatives to shielding materials because of their excellent electrical conductivities, very high surface areas and low densities. In the present work, carbon nanofibers have been synthesized from solutions of Polyacrylonitrile (PAN)/ N,N-dimethylformamide (DMF) by electrospinning method. The carbon nanofibers have been stabilized by oxidation at 250 °C for 2 h in air and carbonized at 750 °C for 1 h in H2/N2. We present the fabrication and characterization of transparent and ultraviolet (UV) shielding CNF/polymer composites. The content of CNF filler has been varied from 0.2% to 0.6 % by weight. UV Spectroscopy has been performed to study the effect of composition on the transmittance of polymer composites.

Keywords: electrospinning, carbon nanofiber, characterization, composites, nanofiber, ultraviolet radiation

Procedia PDF Downloads 225

Authors: Elham Koohikerade, Silvio Jose Gumiere

Abstract:

In this research, irrigation is highlighted as crucial for improving both the yield and quality of ‎potatoes due to their high sensitivity to soil moisture changes. The study presents a hybrid Long ‎Short-Term Memory (LSTM) model aimed at optimizing irrigation scheduling in potato fields in ‎Quebec City, Canada. This model integrates model-based and satellite-derived datasets to simulate ‎soil moisture content, addressing the limitations of field data. Developed under the guidance of the ‎Food and Agriculture Organization (FAO), the simulation approach compensates for the lack of direct ‎soil sensor data, enhancing the LSTM model's predictions. The model was calibrated using indices ‎like Surface Soil Moisture (SSM), Normalized Vegetation Difference Index (NDVI), Enhanced ‎Vegetation Index (EVI), and Normalized Multi-band Drought Index (NMDI) to effectively forecast ‎soil moisture reductions. Understanding soil moisture and plant development is crucial for assessing ‎drought conditions and determining irrigation needs. This study validated the spectral characteristics ‎of vegetation and soil using ECMWF Reanalysis v5 (ERA5) and Moderate Resolution Imaging ‎Spectrometer (MODIS) data from 2019 to 2023, collected from agricultural areas in Dolbeau and ‎Peribonka, Quebec. Parameters such as surface volumetric soil moisture (0-7 cm), NDVI, EVI, and ‎NMDI were extracted from these images. A regional four-year dataset of soil and vegetation moisture ‎was developed using a machine learning approach combining model-based and satellite-based ‎datasets. The LSTM model predicts soil moisture dynamics hourly across different locations and ‎times, with its accuracy verified through cross-validation and comparison with existing soil moisture ‎datasets. The model effectively captures temporal dynamics, making it valuable for applications ‎requiring soil moisture monitoring over time, such as anomaly detection and memory analysis. By ‎identifying typical peak soil moisture values and observing distribution shapes, irrigation can be ‎scheduled to maintain soil moisture within Volumetric Soil Moisture (VSM) values of 0.25 to 0.30 ‎m²/m², avoiding under and over-watering. The strong correlations between parcels suggest that a ‎uniform irrigation strategy might be effective across multiple parcels, with adjustments based on ‎specific parcel characteristics and historical data trends. The application of the LSTM model to ‎predict soil moisture and vegetation indices yielded mixed results. While the model effectively ‎captures the central tendency and temporal dynamics of soil moisture, it struggles with accurately ‎predicting EVI, NDVI, and NMDI.‎

Keywords: irrigation scheduling, LSTM neural network, remotely sensed indices, soil and vegetation ‎monitoring

Procedia PDF Downloads 42

Authors: Magdalena B. Kaziuk, Waldemar Kosiba

Abstract:

Background: In the XXI century we have to deal with the epidemic of obesity which is important risk factor for the cardiovascular and kidney diseases. Lipo proteins are directly involved in the atherosclerotic process. Non-high-density lipo protein (non-HDL) began following widespread recognition of its superiority over LDL as a measurement of vascular event risk. Non-HDL includes residual risk which persists in patients after achieved recommended level of LDL. Materials and Methods: The study covered 111 patients (52 females, 59 males, age 51,91±14 years), hospitalized on the intern department. Body composition was assessed using the bioimpendance method and anthropometric measurements. Physical activity data were collected during the interview. The nutritional status and the obesity type were determined with the Waist to Height Ratio and the Waist to Hip Ratio. A function of the kidney was evaluated by calculating the estimated glomerular filtration rate (eGFR) using MDRD formula. Non-HDL was calculated as a difference between concentration of the Total and HDL cholesterol. Results: 10% of patients were found to be underweight; 23.9 % had correct body weight; 15,08 % had overweight, while the remaining group had obesity: 51,02 %. People with the android shape have higher non-HDL cholesterol versus with the gynoid shape (p=0.003). The higher was non-HDL, the lower eGFR had studied subjects (p < 0.001). Significant correlation was found between high non-HDL and incorrect dietary habits in patients avoiding eating vegetables, fruits and having low physical activity (p < 0.005). Conclusions: Android type of figure raises the residual risk of the heart disease associated with higher levels of non-HDL. Increasing physical activity in these patients reduces the level of non-HDL. Non-HDL seems to be the best predictor among all cholesterol measures for the cardiovascular events and worsening eGFR.

Keywords: obesity, non-HDL cholesterol, glomerular filtration rate, lifestyle

Procedia PDF Downloads 373

Authors: Martin Kendra, Jaroslav Mašek, Juraj Čamaj, Martin Búda

Abstract:

The paper deals with possibilities of increase train capacity by using a new type of railway wagon. In the first part is created a mathematical model to calculate the capacity of the train. The model is based on the main limiting parameters of the train - maximum number of axles per train, the maximum gross weight of the train, the maximum length of train and number of TEUs per one wagon. In the second part is the model applied to four different model trains with different composition of the train set and three different average weights of TEU and a train consisting of a new type of wagons. The result is to identify where the carrying capacity of the original trains is higher, respectively less than a capacity of the train consisting of a new type of wagons.

Keywords: loading units, theoretical capacity model, train capacity, wagon for intermodal transport

Procedia PDF Downloads 497

Authors: Butta Singh

Abstract:

This paper presents a chaotic map based approach for secured embedding of patient’s confidential data in electrocardiogram (ECG) signal. The chaotic map generates predefined locations through the use of selective control parameters. The sample value difference method effectually hides the confidential data in ECG sample pairs at these predefined locations. Evaluation of proposed method on all 48 records of MIT-BIH arrhythmia ECG database demonstrates that the embedding does not alter the diagnostic features of cover ECG. The secret data imperceptibility in stego-ECG is evident through various statistical and clinical performance measures. Statistical metrics comprise of Percentage Root Mean Square Difference (PRD) and Peak Signal to Noise Ratio (PSNR). Further, a comparative analysis between proposed method and existing approaches was also performed. The results clearly demonstrated the superiority of proposed method.

Keywords: chaotic maps, ECG steganography, data embedding, electrocardiogram

Procedia PDF Downloads 196

Authors: Chunyue Liu, Hongxing Jiang

Abstract:

Traditional water depth survey of wetland habitats used by waterbirds needs intensive labor, time and money. The optical remote sensing image relies on passive multispectral scanner data has been widely employed to study estimate water depth. This paper presents an innovative method for developing the water depth model based on the characteristics of visible and thermal infrared spectra of Landsat ETM+ image, combing with 441 field water depth data at Etoupao shallow wetland. The wetland is located at Momoge National Nature Reserve of Northeast China, where the largest stopover habitat along the eastern flyway of globally, critically-endangered Siberian Cranes are. The cranes mainly feed on the tubers of emergent aquatic plants such as Scirpus planiculmis and S. nipponicus. The effective water control is a critical step for maintaining the production of tubers and food availability for this crane. The model employing multi-band approach can effectively simulate water depth for this shallow wetland. The model parameters of NDVI and GREEN indicated the vegetation growth and coverage affecting the reflectance from water column change are uneven. Combining with the field-observed water level at the same date of image acquisition, the digital elevation model (DEM) for the underwater terrain was generated. The wetland area and water volume of different water levels were then calculated from the DEM using the function of Area and Volume Statistics under the 3D Analyst of ArcGIS 10.0. The findings provide good references to effectively monitor changes in water level and water demand, develop practical plan for water level regulation and water management, and to create best foraging habitats for the cranes. The methods here can be adopted for the bottom topography simulation and water management in waterbirds’ habitats, especially in the shallow wetlands.

Keywords: remote sensing, water depth reversion, shallow wetland habitat management, siberian crane

Procedia PDF Downloads 253

Authors: Bagher Aziz Kalantari, Javad Rafiei, Mohamad Reza Talei Bavil Olyai

Abstract:

Disclosed is a method of preparing a pigmentary chromium oxide nano particles having 50 percent particle size less than about 100nm. According to the disclosed method, a substantially dry solid composition of potassium dichromate and carbon active is heated in CO2 atmosphere to a temperature of about 600ºc for 1hr. Thereafter, the solid Cr2O3 product was washed twice with distilled water. The other aim of this study is to assess both the colouring performance and the potential of nano-pigments in the ceramic tile decoration. The rationable consists in nano-pigment application in several ceramics, including a comparison of colour performance with conventional micro-pigments.

Keywords: green chromium oxide, nano particles, colour performances, particle size

Procedia PDF Downloads 335

Authors: S. Turkan

Abstract:

In this paper, the Turkey’s Top 500 Industrial Enterprises data in 2014 were analyzed by data envelopment analysis. Data envelopment analysis is used to detect efficient decision-making units such as universities, hospitals, schools etc. by using inputs and outputs. The decision-making units in this study are enterprises. To detect efficient enterprises, some financial ratios are determined as inputs and outputs. For this reason, financial indicators related to productivity of enterprises are considered. The efficient foreign weighted owned capital enterprises are detected via super efficiency model. According to the results, it is said that Mercedes-Benz is the most efficient foreign weighted owned capital enterprise in Turkey.

Keywords: data envelopment analysis, super efficiency, logistic regression, financial ratios

Procedia PDF Downloads 324

Authors: William Ramirez-Benavides

Abstract:

The mite Varroa destructor Anderson & Trueman (Mesostigmata: Varroidae), is an exclusive hematophagous parasite of the Apis honey bees (Apidae: Hymenoptera). The early phoretic female mites have multiple small inactivated oocytes. Consequently, for the initial growth and vitellogenesis of the oocytes, the mother mite must feed on the hemolymph of the host, as a unique food source, by taking intermittently variable number of blood meals: 1. During the phoretic phase, to initiate vitellogenesis of the terminal oocyte, 2. From a freshly capped bee cell with a bee larva, up to the apolysis stage, to complete vitellogenesis and embryogenesis of the terminal oocyte, and 3. From all pupal stages, up to the imago stage, to induce oogenesis and vitellogenesis of the would-be nonembryonic female eggs. Additionally, oogenesis and vitellogenesis expressions in Varroa destructor and other Varroidae varies according to environmental conditions, e.g., chemical attractions produced by the adult bee and larvae, race of bees, sex of the larva, developmental period of the bee larva, food quality and quantity, and superparasitism (several cofoundressess). Also, the feeding stimuli obtained from the host hemolymph, indirectly regulate the reproductive physiology of the mite, by inducing different vitellogenin expressions, the production of a male egg first in the sequence followed by vitellogenesis of the would-be female eggs during the pupal stages. Furthermore, the different uptakes of hemolymph from the host, also indirectly induce the production of the male egg first in the sequence, local mate competition (LMC) and variable adaptive female sex ratios in the broods, especially when superparasitism occurs. Consequently, reproduction in Varroa destructor, and probably in other Varroidae, depends exclusively on feeding in the hemolymph of the bee host, even during the phoretic phase, the prepupal stages and during the pupal stages; and that, the feeding factors are common syndromes in other Varroidae.

Keywords: oogenesis, sex determination, varroa destructor, vitellogenesis

Procedia PDF Downloads 17

Authors: Hyun-Woo Cho

Abstract:

The real-time fault monitoring and diagnosis of large scale production processes is helpful and necessary in order to operate industrial process safely and efficiently producing good final product quality. Unusual and abnormal events of the process may have a serious impact on the process such as malfunctions or breakdowns. This work try to utilize process measurement data obtained in an on-line basis for the safe and some fault-free operation of industrial processes. To this end, this work evaluated the proposed intelligent process data monitoring framework based on a simulation process. The monitoring scheme extracts the fault pattern in the reduced space for the reliable data representation. Moreover, this work shows the results of using linear and nonlinear techniques for the monitoring purpose. It has shown that the nonlinear technique produced more reliable monitoring results and outperforms linear methods. The adoption of the qualitative monitoring model helps to reduce the sensitivity of the fault pattern to noise.

Keywords: process data, data mining, process operation, real-time monitoring

Procedia PDF Downloads 640

Authors: Sitira Williams, Georgina Cherry, Andrea Wright, Kevin Wells, Taran Rai, Richard Brown, Travis Street, Alasdair Cook

Abstract:

Social media sources (50) were identified, keywords defined by veterinarians and organised into 6 topics known to be indicative of feline pruritus: body areas, behaviors, symptoms, diagnosis, and treatments. These were augmented using academic literature, a cat owner survey, synonyms, and Google Trends. The content was collected using a social intelligence solution, with keywords tagged and filtered. Data were aggregated and de-duplicated. SL content matching body areas, behaviors and symptoms were reviewed manually, and posts were marked relevant if: posted by a pet owner, identifying an itchy cat and not duplicated. A sub-set of 493 posts published from 2009-2022 was used for reflexive thematic analysis in NVIVO (Burlington, MA) to identify themes. Five themes were identified: allergy, pruritus, additional behaviors, unusual or undesirable behaviors, diagnosis, and treatment. Most (258) posts reported the cat was excessively licking, itching, and scratching. The majority were indoor cats and were less playful and friendly when itchy. Half of these posts did not indicate a known cause of pruritus. Bald spots and scabs (123) were reported, often causing swelling and fur loss, and 56 reported bumps, lumps, and dry patches. Other impacts on the cat’s quality of life were ear mites, cat self-trauma and stress. Seven posts reported their cats’ symptoms caused them ongoing anxiety and depression. Cats with food allergies to poultry (often chicken and beef) causing bald spots featured in 23 posts. Veterinarians advised switching to a raw food diet and/or changing their bowls. Some cats got worse after switching, leaving owners’ needs unmet. Allergic reactions to flea bites causing excessive itching, red spots, scabs, and fur loss were reported in 13 posts. Some (3) posts indicated allergic reactions to medication. Cats with seasonal and skin allergies, causing sneezing, scratching, headshaking, watery eyes, and nasal discharge, were reported 17 times. Eighty-five posts identified additional behaviors. Of these, 13 reported their cat’s burst pimple or insect bite. Common behaviors were headshaking, rubbing, pawing at their ears, and aggressively chewing. In some cases, bites or pimples triggered previously unseen itchiness, making the cat irritable. Twenty-four reported their cat had anxiety: overgrooming, itching, losing fur, hiding, freaking out, breathing quickly, sleeplessness, hissing and vocalising. Most reported these cats as having itchy skin, fleas, and bumps. Cats were commonly diagnosed with an ear infection, ringworm, acne, or kidney disease. Acne was diagnosed in cats with an allergy flare-up or overgrooming. Ear infections were diagnosed in itchy cats with mites or other parasites. Of the treatments mentioned, steroids were most frequently used, then anti-parasitics, including flea treatments and oral medication (steroids, antibiotics). Forty-six posts reported distress following poor outcomes after medication or additional vet consultations. SL provides veterinarians with unique insights. Verbatim comments highlight the detrimental effects of pruritus on pets and owner quality of life. This study demonstrates the need for veterinarians to communicate management and treatment options more effectively to relieve owner frustrations. Data analysis could be scaled up using machine learning for topic modeling.

Keywords: content analysis, feline, itch, pruritus, social media, thematic analysis, veterinary dermatology

Procedia PDF Downloads 191

Authors: A. K. Singh, Chhotu Ram

Abstract:

The present work relates to the corrosivity of distillery effluent and corrosion performance of mild steel and stainless steels SS304L, SS316L, and 2205. The report presents the results and conclusions drawn on the basis of (i) electrochemical polarization tests performed in distillery effluent and laboratory prepared solutions having composition similar to that of the effluent (ii) the surface examination by scanning electron microscope (SEM) of the corroded steel samples. It is observed that pH and presence of chloride, phosphate, calcium, nitrite and nitrate in distillery effluent enhance corrosion, whereas presence of sulphate and potassium inhibits corrosion. Among the materials tested, mild steel is observed to experience maximum corrosion followed by stainless steels SS304L, SS316L, and 2205.

Keywords: corrosion, distillery effluent, electrochemical polarization, steel

Procedia PDF Downloads 409

Authors: Chebouti-meziou Nadjiba1, And Chebouti Yahia2:

Abstract:

the cultivation of Pistachios Pistacia vera of rare plants in Algeria and this point to see the lack of knowledge of techniques, which resulted in the proliferation of the tree to obtain a limited benefit does not exceed 0.75 tons / hectare, in addition to the enemy that lead to poor product on the one hand, one of which buds into wood and fruit Chaetoptelius vestitus. Since the tree is the raw sound production, while 25 kg of infected tree produces about 15 kg of any shortage of fact that this insect Chaetoptelius vestitus spend the amount of trouble going in the summer the young twigs of the trees into a sound the product by20% and due to the composition by the problem of spending in the newly formed branches, which lead to this loss in yield

Keywords: chaetoptelius vestitus, pistacia vera, spending, return, poor product.

Procedia PDF Downloads 69

Authors: Vipan Kumar Sohpal, Rajesh K Sharma

Abstract:

Diminishing of conventional fuels and hysterical vehicles emission leads to deterioration of the environment, which emphasize the research to work on biofuels. Biofuels from different sources attract the attention of research due to low emission and biodegradability. Emission of carbon monoxide, carbon dioxide and H-C reduced drastically using Biofuels (B-20) combustion. Contrary to the conventional fuel, engine emission results indicated that nitrous oxide emission is higher in Biofuels. So this paper examines and compares the nitrogen oxide emission of Jatropha Curcus (JCO) B-20% blends with the vegetable oil. In addition to that computational analysis of crude non edible oil performed to assess the impact of composition on emission quality. In conclusion, JCO have the potential feedstock for the biodiesel production after the genetic modification in the plant.

Keywords: jatropha curcus, computational analysis, emissions, NOx biofuels

Procedia PDF Downloads 587

Authors: Ayla Roberta Galaco, Juliana Fonseca De Lima, Osvaldo Antonio Serra

Abstract:

Coordination polymers, also known as metal-organic frameworks (MOFs) or lanthanoide organic frameworks (LOFs) have been reported due of their promising applications in gas storage, separation, catalysis, luminescence, magnetism, drug delivery, and so on. As a type of organic–inorganic hybrid materials, the properties of coordination polymers could be chosen by deliberately selecting the organic and inorganic components. LOFs have received considerable attention because of their properties such as porosity, luminescence, and magnetism. Methods such as solvothermal synthesis are important as a strategy to control the structural and morphological properties as well as the composition of the target compounds. In this work the first solvothermal synthesis was employed to obtain the compound [Y0.4,Yb0.4,Er0.2(dmf)(for)(H2O)(tft)], by using terephthalic acid (tft) and oxalic acid, decomposed in formate (for), as ligands; Yttrium, Ytterbium and, Erbium as metal centers, in DMF and water for 4 days under 160 °C. The semi-rigid terephthalic acid (dicarboxylic) coordinates with Ln3+ ions and also is possible to form a polyfunctional bridge. On the other hand, oxalate anion has no high-energy vibrational groups, which benefits the excitation of Yb3+ in upconversion process. It was observed that the compounds with water molecules in the coordination sphere of the lanthanoide ions cause lower crystalline properties and change the structure of the LOF (1D, 2D, 3D). In the FTIR, the bands at 1589 and 1500 cm-1 correspond to the asymmetric stretching vibration of –COO. The band at 1383 cm-1 is assigned to the symmetric stretching vibration of –COO. Single crystal X-ray diffraction study reveals an infinite 3D coordination framework that crystalizes in space group P21/c. The other three products, [TR(chel)(ofd)0,5(H2O)2], where TR= Eu3+, Y3, and Yb3+/Er3+ were obtained by using 1, 2-phenylenedioxydiacetic acid (ofd) and chelidonic acid (chel) as organic ligands. Thermal analysis shows that the lanthanoide organic frameworks do not collapse at temperatures below 250 °C. By the polycrystalline X-ray diffraction patterns (PXRD) it was observed that the compounds with Eu3+, Y3+, and Yb3+/Er3+ ions are isostructural. From PXRD patterns, high crystallinity can be noticed for the complexes. The final products were characterized by single X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), energy dispersive spectroscopy (EDS) and thermogravimetric analysis (TGA). The X-ray diffraction (XRD) is an effective method to investigate crystalline properties of synthesized materials. The solid crystal obtained in the synthesis show peaks at 2θ < 10°, indicating the MOF formation. The chemical composition of LOFs was also confirmed by EDS.

Keywords: isostructural, lanthanoids, lanthanoids organic frameworks (LOFs), metal organic frameworks (MOFs), thermogravimetry, X-Ray diffraction

Procedia PDF Downloads 260

Authors: Saha Naseri

Abstract:

Introduction/Objective: Son preference, a preference for sons over daughters, is a practice deeply-rooted in gender inequality that is widespread in many societies and across different religions and cultures. In this study, we are aiming to study the effects of son preference on fertility outcomes (birth interval and current contraceptive use) in Afghanistan, where have been perceived with high rates of son preference. The objectives of the study are to examine the association between the sex of the previous child and the duration of the subsequent birth interval and to evaluate the effect of son preference on current contraceptive use. Methodology: Afghanistan Demographic and Health Survey (DHS) (2015) was used to study the impact of son preference on fertility outcomes among married women. The data collected from 28,661 on currently-married women, aged between 15 and 49 years who have at least one child, have used to conduct this quantitative study. Outcomes of interest are birth interval and current contraceptive use. Simple and multiple regression analysis have been conducted to assess the effect of son preference on these fertility outcomes. Results: The present study has highlighted that son preference somehow exists among married women in Afghanistan. It is indicated that the sex of the first birth is significantly associated with the succeeding birth interval. Having a female child as the first baby was associated with a shorter average succeeding birth interval by 1.8 months compared to a baby boy (p-value = 0.000). For the second model, the results identified that women who desire for more sons have 7% higher odds to be current contraceptive user compared to those who have no preference (p-value = 0.03). The latter results do not indicate the son preference. However, one limitation for this result was the timeliness of the questions asked since contraceptive use in the current time was asked along with a question on ‘future’ desired sex composition. Moreover, women may have just given birth and want to reach a certain time span of birth interval before planning for another child, even if it was a boy, which might have affected the results. Conclusion: Overall, this study has demonstrated that there is a positive relationship between son preference and one main fertility behaviors, birth interval. The second fertility outcome, current contraceptive use, was not a good indicator to measure son preference. Based on the finding, recommendations will be made for appropriate interventions addressing gender norms and related fertility decisions.

Keywords: Afghanistan, birth interval, contraceptive, son preference

Procedia PDF Downloads 173

Authors: Soumitri Bag Majumder, Anindita Chaudhuri

Abstract:

This exploratory study delves into the perception of job dignity among delivery agents in Kolkata, focusing on both food and grocery delivery sectors. The rapid expansion of online delivery platforms in India has led to a significant rise in the delivery service industry. Despite its growth, there is a dearth of research addressing the multifaceted challenges faced by delivery agents. This study aims to bridge this gap by shedding light on their experiences. The study’s objectives include exploring the lived experiences of delivery agents, their work-life balance, and their perception of job dignity. Using a qualitative research approach, the study will conduct semi-structured in-depth interviews with a purposive sample of 10 participants from each sector, consisting of individuals with lower socio-economic backgrounds aged between 18 and 35 years. The Three-Layer Coding framework proposed by Charmaz will guide the data analysis process, encompassing open coding, axial coding, and selective coding. Through this method, the study seeks to uncover emergent themes and patterns that illuminate the participants’ perspectives on job dignity, recognition, and the challenges they encounter. By uncovering their perceptions of job dignity and the challenges they face, the research aims to contribute to the well-being of these workers and inform relevant stakeholders for a more equitable work environment.

Keywords: delivery agents, equitable work environment, perception of job dignity, work-life balance

Procedia PDF Downloads 64

Authors: Srinivas Peri, Siva Abhishek Sirivella, Tejaswini Kallakuri, Uzair Ahmad

Abstract:

Effective traffic management and infrastructure planning are crucial for the development of smart cities and intelligent transportation systems. This study addresses the challenge of data scarcity by generating realistic synthetic traffic data using the PeMS-Bay dataset, improving the accuracy and reliability of predictive modeling. Advanced synthetic data generation techniques, including TimeGAN, GaussianCopula, and PAR Synthesizer, are employed to produce synthetic data that replicates the statistical and structural characteristics of real-world traffic. Future integration of Spatial-Temporal Generative Adversarial Networks (ST-GAN) is planned to capture both spatial and temporal correlations, further improving data quality and realism. The performance of each synthetic data generation model is evaluated against real-world data to identify the best models for accurately replicating traffic patterns. Long Short-Term Memory (LSTM) networks are utilized to model and predict complex temporal dependencies within traffic patterns. This comprehensive approach aims to pinpoint areas with low vehicle counts, uncover underlying traffic issues, and inform targeted infrastructure interventions. By combining GAN-based synthetic data generation with LSTM-based traffic modeling, this study supports data-driven decision-making that enhances urban mobility, safety, and the overall efficiency of city planning initiatives.

Keywords: GAN, long short-term memory, synthetic data generation, traffic management

Procedia PDF Downloads 28