Search results for: improving extraction

Authors: Boris G. German, Edward Jiménez, Sebastián Espinoza, Andrés G. Chico, Ricardo A. Narváez

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The unique flora and fauna of The Galapagos Islands has leveraged a tourism-driven growth in the islands. Nonetheless, such development is energy-intensive and requires thousands of gallons of diesel each year for thermoelectric electricity generation. The needed transport of fossil fuels from the continent has generated oil spillages and affectations to the fragile ecosystem of the islands. The Zero Fossil Fuels initiative for The Galapagos proposed by the Ecuadorian government as an alternative to reduce the use of fossil fuels in the islands, considers the replacement of diesel in thermoelectric generators, by Jatropha curcas vegetable oil. However, the Jatropha oil supply cannot entirely cover yet the demand for electricity generation in Galapagos. Within this context, the present work aims to provide an optimization model that can be used as a selection criterion for approving new Jatropha Curcas collection points in rural areas of Manabi-Ecuador. For this purpose, existing Jatropha collection points in Manabi were grouped under three regions: north (7 collection points), center (4 collection points) and south (9 collection points). Field work was carried out in every region in order to characterize the collection points, to establish local Jatropha supply and to determine transportation costs. Data collection was complemented using GIS software and an objective function was defined in order to determine the profit associated to Jatropha oil production. The market price of both Jatropha oil and residual cake, were considered for the total revenue; whereas Jatropha price, transportation and oil extraction costs were considered for the total cost. The tonnes of Jatropha fruit and seed, transported from collection points to the extraction plant, were considered as variables. The maximum and minimum amount of the collected Jatropha from each region constrained the optimization problem. The supply chain was optimized using linear programming in order to maximize the profits. Finally, a sensitivity analysis was performed in order to find a profit-based criterion for the acceptance of future collection points in Manabi. The maximum profit reached a value of $ 4,616.93 per year, which represented a total Jatropha collection of 62.3 tonnes Jatropha per year. The northern region of Manabi had the biggest collection share (69%), followed by the southern region (17%). The criteria for accepting new Jatropha collection points in the rural areas of Manabi can be defined by the current maximum profit of the zone and by the variation in the profit when collection points are removed one at a time. The definition of new feasible collection points plays a key role in the supply chain associated to Jatropha oil production. Therefore, a mathematical model that assists decision makers in establishing new collection points while assuring profitability, contributes to guarantee a continued Jatropha oil supply for Galapagos and a sustained economic growth in the rural areas of Ecuador.

Keywords: collection points, Jatropha curcas, linear programming, supply chain

Procedia PDF Downloads 430

Authors: Sawsan Dacrory, Hussein Abou-Yousef, Samir Kamel, Ragab E. Abou-Zeid, Mohamed S. Abdel-Aziz, Mohamed Elbadry

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A considerable amount of lignocellulosic by-product could be obtained from olive pulp during olive oil extraction industry. The major constituents of the olive pulp are husks and seeds. The separation of each portion of olive pulp (seeds and husks) was carried out by water flotation where seeds were sediment in the bottom. Both seeds and husks were dignified by 15% NaOH followed by complete lignin removal by using sodium chlorite in acidic medium. The isolated holocellulose, α-cellulose, hydrogel and CMC which prepared from cellulose of both seeds and husk fractions were characterized by FTIR and SEM. The present study focused on the investigation of the chemical components of the lignocellulosic fraction of olive pulp. Biofunctionlization of hydrogel was achieved through loading of silver nanoparticles AgNPs in to the prepared hydrogel. The antimicrobial activity of the loaded silver hydrogel against G-ve, and G+ve, and candida was demonstrated.

Keywords: cellulose, carboxymethyle cellulose, olive pulp, hydrogel

Procedia PDF Downloads 473

Authors: Lozano Paul

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Coupled Membrane Separation Technology (CMST), including Cross Flow Microfiltration (CFM) and Reverse Osmosis (RO), are used to concentrate microalgae biomass or/and to extract and concentrate water-soluble metabolites produced during micro-algae production cycle, as well as water recycling. Micro-algae biomass was produced using different feeding mixtures of ingredients: pure chemical origin compounds and natural/ecological water-extracted components from available local plants. Micro-algae was grown either in conventional plastic bags (100L/unit) or in small-scale innovative bioreactors (75L). Biomass was concentrated as CFM retentate using a P19-60 ceramic membrane (0.2μm pore size), and water-soluble micro-algae metabolites left in the CFM filtrate were concentrated by RO. Large volumes of water (micro-algae culture media) of were recycled by the CMTS for another biomass production cycle.

Keywords: extraction, membrane process, microalgae, natural compound

Procedia PDF Downloads 277

Authors: Abdulkareem M. Hamid, Yaseen Elhebshi, Adam Daïch

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Luotonins and its derivatives (Isoluotonins) are alkaloids from the aerial parts of Peganum nigellastrum Bunge that display three major skeleton types. Luotonins A, B, and E are pyrroloquinazolinoquinoline alkaloids. A few methods were known for the sysnthesis of Isoluotonin. All luotonins have shown promising cytotoxicities towards selected human cancer cell lines, especially against leukemia P-388 cells. Luotonin A is the most active one, with its activity stemming from topoisomerase I-dependent DNA-cleavage. Such intriguing biological activities and unique structures have led not only to the development of synthetic methods for the efficient synthesis of these compounds, but also to interest in structural modifications for improving the biological properties. Recent progress in the study of luotonins is covered.

Keywords: luotonin A, isoluotonin, pyrroloquiolines, alkaloids

Procedia PDF Downloads 415

Authors: Julia Wicker, Alexander Lang

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The shortage of skilled workers is no longer unique to Europe; Australia now faces similar challenges, particularly in the field of project management. Project managers, essential to the success of a wide range of industries, frequently operate under intense stress and, as a result, may choose to leave their positions before the completion of their projects. This trend poses significant risks to project continuity, budget stability, and the long-term success of organizations. Consequently, it is crucial to explore strategies aimed at improving the retention of project managers, with a specific focus on fostering intrinsic motivation -an essential factor for achieving sustained success and commitment within project-based roles. The aim of this paper is to investigate retention strategies from other industries to identify effective practices that could be adapted to the unique challenges faced by project managers. In particular, the paper draws inspiration from the volunteer sector, an industry also heavily reliant on intrinsic motivation to drive commitment and performance. By examining how the volunteer sector sustains retention through a focus on intrinsic motivation, this paper seeks to highlight potential parallels and offer actionable insights for improving the retention of project managers. The paper includes an overview of the current landscape of retention challenges in project management, highlighting key factors that contribute to early departures and their impacts on organizations. This is followed by an analysis of interviews conducted with both active volunteers and those who have left their roles, leading to the development of a model that categorizes different types of volunteers and explores their behaviours. The model identifies specific reasons for volunteer terminating their assignments and proposes strategies to mitigate these issues. The paper then adapts these volunteer retention strategies to address the challenges faced by project managers, concluding with actionable recommendations for fostering an intrinsically motivated and resilient project management workforce. Ultimately, this research aims to contribute to broader efforts in mitigating skilled workforce shortages by offering sustainable retention strategies.

Keywords: skilled workforce shortages, retention challenges in project management, retention strategies in the volunteering sector, retention strategies for project managers

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Authors: S. M. Abdus Sattar

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Introduction: The objectives of the study are to assess different aspects of the tourism and hospitality industry, analyze its contributions to the Gross Domestic Product of Bangladesh, identify the importance of the tourism and hospitality industry, explore future prospects in the sectors, identify challenges and provide recommendations for the development of these industries. The study explores the significance of the tourism and hospitality industry in economic growth and defines its role. Tourism is one of the fastest-growing industries in the world today. Methodology: The study adopts statistical methods and utilizes both quantitative and qualitative research techniques. Data is collected through surveys, interviews, visitor registration, online platforms and analysis of various tourism-related records. The study focuses on marketing, management, attractions and services in the tourism and hospitality sectors. Result: The tourism and hospitality industry offers great opportunities for emerging economies and developing countries. The industry provides job creation, infrastructure development, cultural assets and environmental conservation, essential skills development, revenue generated, foreign exchange earned, economic growth and reduced poverty and inequality. Discussion: The study focuses on improving infrastructure and service quality in the tourism and hospitality industry to attract tourists. The industry significantly contributes to the Gross Domestic Product of Bangladesh. It highlights how the tourism and hospitality sectors can drive economic development, reduce poverty and promote cultural and environmental conservation. It also explores the challenges and future prospects in the tourism and hospitality sectors. Conclusion and Future Scope: The opportunities for tourism of Bangladesh are agricultural tourism, religious tourism, sports tourism, eco-tourism, educational tourism, rural tourism and cultural tourism. However, there is a lack of research and plans to explore the development of the industry. The tourism and hospitality industry offers numerous opportunities for growth and development. There are job opportunities for travel consultants, tour operators, event planners, hotel managers, travel writers, tourism development officers and airline executives in the future. The study recommends to development of tourism infrastructure, maintaining tourist destinations, railway stations, airports, rest houses, hotels and improving the quality of services.

Keywords: tourism, hospitality, employment, economic, development

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Authors: Renzhi Qi, Zhaoping Zhong

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Under the dual pressure of the global energy crisis and environmental pollution, avoiding the consumption of non-renewable fossil fuels based on carbon as the energy carrier and developing and utilizing non-carbon energy carriers are the basic requirements for the future new energy economy. Electrocatalyst for water splitting plays an important role in building sustainable and environmentally friendly energy conversion. The oxygen evolution reaction (OER) is essentially limited by the slow kinetics of multi-step proton-electron transfer, which limits the efficiency and cost of water splitting. In this work, CeO₂@NiCo-NRGO/NF hybrid materials were prepared using nickel foam (NF) and nitrogen-doped reduced graphene oxide (NRGO) as conductive substrates by multi-step hydrothermal method and were used as highly efficient catalysts for OER. The well-connected nanosheet array forms a three-dimensional (3D) network on the substrate, providing a large electrochemical surface area with abundant catalytic active sites. The doping of CeO₂ in NiCo-NRGO/NF electrocatalysts promotes the dispersion of substances and its synergistic effect in promoting the activation of reactants, which is crucial for improving its catalytic performance against OER. The results indicate that CeO₂@NiCo-NRGO/NF only requires a lower overpotential of 250 mV to drive the current density of 10 mA cm-2 for an OER reaction of 1 M KOH, and exhibits excellent stability at this current density for more than 10 hours. The double layer capacitance (Cdl) values show that CeO₂@NiCo-NRGO/NF significantly affects the interfacial conductivity and electrochemically active surface area. The hybrid structure could promote the catalytic performance of oxygen evolution reaction, such as low initial potential, high electrical activity, and excellent long-term durability. The strategy for improving the catalytic activity of NiCo-LDH can be used to develop a variety of other electrocatalysts for water splitting.

Keywords: CeO₂, reduced graphene oxide, NiCo-layered double hydroxide, oxygen evolution reaction

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Authors: Hashem A. Alsamadani

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Identifying the level of job satisfaction has many positive benefits for both the worker and employer. The purpose of the study was to examine the overall level of job satisfaction among English as a Foreign Language (EFL) instructors. During the past years, multiple methods were utilized to collect data to determine the level of job satisfaction among teachers. This study was conducted using survey research method. A questionnaire was coded and analyzed using the SPSS. The findings revealed that the overall level of job satisfaction among EFL instructors is high. The study recommended improving conditions of instructors working at public universities so as to gain a high level of job satisfaction and improve outcomes of the teaching-learning process.

Keywords: job satisfaction, EFL teachers, Saudi Arabia, instruction

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Authors: Saurav Kumar Suman, P. Karthigayani

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In this paper the height of the tree is estimated and forest types is classified from the multi temporal RISAT-1 Horizontal-Horizontal (HH) and Horizontal-Vertical (HV) Polarised Satellite Aperture Radar (SAR) data. The novelty of the proposed project is combined use of the Back-scattering Coefficients (Sigma Naught) and the Coherence. It uses Water Cloud Model (WCM). The approaches use two main steps. (a) Extraction of the different forest parameter data from the Product.xml, BAND-META file and from Grid-xxx.txt file come with the HH & HV polarized data from the ISRO (Indian Space Research Centre). These file contains the required parameter during height estimation. (b) Calculation of the Vegetation and Ground Backscattering, Coherence and other Forest Parameters. (c) Classification of Forest Types using the ENVI 5.0 Tool and ROI (Region of Interest) calculation.

Keywords: RISAT-1, classification, forest, SAR data

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Authors: J. Congalton, K. Logan, B. Crump

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Software is a critical aspect of modern life. However it is costly to develop and industry initiatives have focused on reducing costs and improving the productivity. Increasing, software is being developed in teams, and with greater globalization and migration, the teams are becoming more ethnically diverse. This study investigated whether diversity in terms of ethnicity impacted on the productivity of software development. Project managers of software development teams were interviewed. The study found that while some issues did exist due to language problems, when project managers created an environment of trust and friendliness, diversity made a positive contribution to productivity.

Keywords: diversity, project management, software development, team work

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Authors: Farshideh Einsele, Hassan Foroosh

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In this paper, we present a robust algorithm to recognize extracted text from grocery product images captured by mobile phone cameras. Recognition of such text is challenging since text in grocery product images varies in its size, orientation, style, illumination, and can suffer from perspective distortion. Pre-processing is performed to make the characters scale and rotation invariant. Since text degradations can not be appropriately defined using wellknown geometric transformations such as translation, rotation, affine transformation and shearing, we use the whole character black pixels as our feature vector. Classification is performed with minimum distance classifier using the maximum likelihood criterion, which delivers very promising Character Recognition Rate (CRR) of 89%. We achieve considerably higher Word Recognition Rate (WRR) of 99% when using lower level linguistic knowledge about product words during the recognition process.

Keywords: camera-based OCR, feature extraction, document, image processing, grocery products

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Authors: Slim Chokri

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Load forecasting is one of the central functions in power systems operations. Electricity cannot be stored, which means that for electric utility, the estimate of the future demand is necessary in managing the production and purchasing in an economically reasonable way. A majority of the recently reported approaches are based on neural network. The attraction of the methods lies in the assumption that neural networks are able to learn properties of the load. However, the development of the methods is not finished, and the lack of comparative results on different model variations is a problem. This paper presents a new approach in order to predict the Tunisia daily peak load. The proposed method employs a computational intelligence scheme based on the Fuzzy neural network (FNN) and support vector regression (SVR). Experimental results obtained indicate that our proposed FNN-SVR technique gives significantly good prediction accuracy compared to some classical techniques.

Keywords: neural network, load forecasting, fuzzy inference, machine learning, fuzzy modeling and rule extraction, support vector regression

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Authors: Namiiro Shirat Umar

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The science of animals and veterinary medicine is a multidisciplinary field dedicated to understanding, managing, and enhancing the health and welfare of animals. This field encompasses a broad spectrum of disciplines, including animal physiology, genetics, nutrition, behavior, and pathology, as well as preventive and therapeutic veterinary care. Veterinary science focuses on diagnosing, treating, and preventing diseases in animals, ensuring their health and well-being. It involves the study of various animal species, from companion animals and livestock to wildlife and exotic species. Through advanced diagnostic techniques, medical treatments, and surgical procedures, veterinarians address a wide range of health issues, from infectious diseases and injuries to chronic conditions and reproductive health. Animal science complements veterinary medicine by providing a deeper understanding of animal biology and behavior, which is essential for effective health management. It includes research on animal breeding, nutrition, and husbandry practices aimed at improving animal productivity and welfare. Incorporating modern technologies and methodologies, such as genomics, bioinformatics, and precision farming, the science of animals and veterinary medicine continually evolves to address emerging challenges. This integrated approach ensures the development of sustainable practices, enhances animal welfare and contributes to public health by monitoring zoonotic diseases and ensuring the safety of animal products. Animal nutrition is a cornerstone of animal and veterinary science, focusing on the dietary needs of animals to promote health, growth, reproduction, and overall well-being. Proper nutrition ensures that animals receive essential nutrients, including macronutrients (carbohydrates, proteins, fats) and micronutrients (vitamins, minerals), tailored to their specific species, life stages, and physiological conditions. By emphasizing a balanced diet, animal nutrition serves as a preventive measure against diseases and enhances recovery from illnesses, reducing the need for pharmaceutical interventions. It addresses key health issues such as metabolic disorders, reproductive inefficiencies, and immune system deficiencies. Moreover, optimized nutrition improves the quality of animal products like meat, milk, and eggs and enhances the sustainability of animal farming by improving feed efficiency and reducing environmental waste. The integration of animal nutrition into veterinary practice necessitates a collaborative approach involving veterinarians, animal nutritionists, and farmers. Advances in nutritional science, such as precision feeding and the use of nutraceuticals, provide innovative solutions to traditional veterinary challenges. Overall, the focus on animal nutrition as a primary aspect of veterinary care leads to more holistic, sustainable, and effective animal health management practices, promoting the welfare and productivity of animals in various settings. This abstract is a trifold in nature as it traverses how education can put more emphasis on animal nutrition as an alternative for improving animal health as an important issue espoused under the discipline of animal and veterinary science; therefore, brief aspects of this paper and they are as follows; animal nutrition, veterinary science and animals.

Keywords: animal nutrition as a way to enhance growth, animal science as a study, veterinary science dealing with health of the animals, animals healthcare dealing with proper sanitation

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Authors: Jerald Ruta, Ricardo Villar, Jojemar Bantugan, Nycel Barbadillo, Jigg Pelayo

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Streams are important in providing water supply for industrial, agricultural and human consumption, In short when there are streams there are lives. Identifying streams are essential since many developed cities are situated in the vicinity of these bodies of water and in flood management, it serves as basin for surface runoff within the area. This study aims to process and generate features from high-resolution digital terrain model (DTM) with 1-meter resolution using Hydrology Tools of ArcGIS. The raster was then filled, processed flow direction and accumulation, then raster calculate and provide stream order, converted to vector, and clearing undesirable features using the ancillary or google earth. In field validation streams were classified whether perennial, intermittent or ephemeral. Results show more than 90% of the extracted feature were accurate in assessment through field validation.

Keywords: digital terrain models, hydrology tools, strahler method, stream classification

Procedia PDF Downloads 267

Authors: Muhammad Jamil, Ning He, Wei Zhao

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Ti-6Al-4V has poor thermal conductivity (6.7W/mK) accumulates shear and friction heat at the tool-chip interface zone. To dissipate the heat generation and friction effect, cryogenic cooling, Minimum quantity lubrication (MQL), nanofluids, hybrid cryogenic-MQL, solid lubricants, etc are applied frequently to underscore their significant effect on improving the machinability of Ti-6Al-4V. Nowadays, hybrid lubri-cooling is getting attention from researchers to explore their effect on machining Ti-6Al-4V.

Keywords: hybrid lubri-cooling, tool wear, surface roughness, minimum quantity lubrication

Procedia PDF Downloads 142

Authors: Nathaniel A. Hoston

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Teacher coaching is necessary for improving student behaviors. While coaching technologies (e.g., bug-in-ear coaching, video-coaching) can assist the coaching process, little is known about the usability of those tools. This study assessed the usability and perceived efficacy of the Behavior Coaching Organizer (BCO) using usability testing methods (i.e., concurrent think-aloud, retrospective probing) in a simulated learning environment. Participants found that the BCO is moderately usable while perceiving the tool as highly effective for addressing concerning student behaviors. Additionally, participants noted a general need for continued coaching support. The results indicate a need for further usability testing with education research.

Keywords: behavioral interventions, Behavior Coaching Organizer, coaching technologies, usability methods

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Authors: Bendjaballah Malek; Makhlouf Mohammed Rabeh; Boukerche Imane; Benhamza Mohammed El Hocine

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In this study, chitosan was derived from Parapenaeus longirostris shrimp shells sourced from a local market in Annaba, eastern Algeria. The extraction process entailed four chemical stages: demineralization, deproteinization, decolorization, and deacetylation. The degree of deacetylation was calculated to be 80.86 %. The extracted chitosan was physically altered to synthesize chitosan beads and characterized via FTIR and XRD analysis. These beads were employed to eliminate cadmium ions from synthetic water. The batch adsorption process was optimized by analyzing the impact of contact time, pH, adsorbent dose, and temperature. The adsorption capacity of and Cd+2 on chitosan beads was found to be 6.83 mg/g and 7.94 mg/g, respectively. The kinetic adsorption of Cd+2 conformed to the pseudo-first-order model, while the isotherm study indicated that the Langmuir Isotherm model well described the adsorption of cadmium . A thermodynamic analysis demonstrated that the adsorption of Cd+2 on chitosan beads is spontaneous and exothermic.

Keywords: Cd, chitosan, chitosanbeds, bioadsorbent

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Authors: Tigist Mekonnen Melesse

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Since rural households are basically entitled to food through own production, improving productivity might lead to enhance the welfare of rural population through higher food availability at the household level and lowering the price of agricultural products. Increasing agricultural productivity through the use of improved technology is one of the desired outcomes from sensible food security and agricultural policy. The ultimate objective of this study was to evaluate the potential impact of improved agricultural technology adoption on smallholders’ crop productivity and welfare. The study is conducted in Ethiopia covering 1500 rural households drawn from four regions and 15 rural villages based on data collected by Ethiopian Rural Household Survey. Endogenous treatment effect model is employed in order to account for the selection bias on adoption decision that is expected from the self-selection of households in technology adoption. The treatment indicator, technology adoption is a binary variable indicating whether the household used improved seeds and chemical fertilizer or not. The outcome variables were cereal crop productivity, measured in real value of production and welfare of households, measured in real per capita consumption expenditure. Results of the analysis indicate that there is positive and significant effect of improved technology use on rural households’ crop productivity and welfare in Ethiopia. Adoption of improved seeds and chemical fertilizer alone will increase the crop productivity by 7.38 and 6.32 percent per year of each. Adoption of such technologies is also found to improve households’ welfare by 1.17 and 0.25 percent per month of each. The combined effect of both technologies when adopted jointly is increasing crop productivity by 5.82 percent and improving welfare by 0.42 percent. Besides, educational level of household head, farm size, labor use, participation in extension program, expenditure for input and number of oxen positively affect crop productivity and household welfare, while large household size negatively affect welfare of households. In our estimation, the average treatment effect of technology adoption (average treatment effect on the treated, ATET) is the same as the average treatment effect (ATE). This implies that the average predicted outcome for the treatment group is similar to the average predicted outcome for the whole population.

Keywords: Endogenous treatment effect, technologies, productivity, welfare, Ethiopia

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Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: Laurence Craven

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Academic writing is one of the most important class a freshman will take, as it provides the skill needed to formulate an academic essay in any discipline. Written assignments are the most common form of assessment in higher education and thus it is of paramount importance for students to master the skill of academic writing. This presentation aims to give practitioners multiple ways to enhance their academic writing classes using the Blackboard environment, with a view to improving student performance. The presentation will include ways to improve assessment and give corrective feedback. It will also provide ideas on how to increase variety in teaching lessons, assigning homework and on organizing materials.

Keywords: academic writing, assessment, e-learning, technology

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Authors: Haojie Wang, Xun Li, Rui Yin

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In order to solve the memorization overfitting in the meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels, so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to exponential growth of computation, this paper also proposes a key data extraction method, that only extracts part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: data augmentation, mutex task generation, meta-learning, text classification.

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Authors: Palingba Aimé Marie Doilkom, Mahamadou Koïta, Jean-michel Vouillamoz, Angelbert Biaou

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Most African populations rely on groundwater in rural areas for their consumption. Indeed, in the face of climate change and strong demographic growth, groundwater, particularly in the basement, is increasingly in demand. The question of the sustainability of water resources in this type of environment is therefore becoming a major issue. Groundwater recharge can be natural or artificial. Unlike natural recharge, which often results from the natural infiltration of surface water (e.g. a share of rainfall), artificial recharge consists of causing water infiltration through appropriate developments to artificially replenish the water stock of an aquifer. Artificial recharge is, therefore, one of the measures that can be implemented to secure water supply, combat the effects of climate change, and, more generally, contribute to improving the quantitative status of groundwater bodies. It is in this context that the present research is conducted with the aim of developing artificial recharge in order to contribute to the sustainability of basement aquifers in a context of climatic variability and constantly increasing water needs of populations. In order to achieve the expected results, it is therefore important to determine the characteristics of the infiltration basins and to identify the areas suitable for their implementation. The geometry of the aquifer was reproduced, and the hydraulic properties of the aquifer were collected and characterized, including boundary conditions, hydraulic conductivity, effective porosity, recharge, Van Genuchten parameters, and saturation indices. The aquifer of the Sanon experimental site is made up of three layers, namely the saprolite, the fissured horizon, and the healthy basement. Indeed, the saprolite and the fissured medium were considered for the simulations. The first results with FEFLOW model show that the water table reacts continuously for the first 100 days before stabilizing. The hydraulic charge increases by an average of 1 m. The further away from the basin, the less the water table reacts. However, if a variable hydraulic head is imposed on the basins, it can be seen that the response of the water table is not uniform over time. The lower the basin hydraulic head, the less it affects the water table. These simulations must be continued by improving the characteristics of the basins in order to obtain the appropriate characteristics for a good recharge.

Keywords: basement area, FEFLOW, infiltration basin, MAR

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Authors: Achutha Raman

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Today's brave new world features a bonanza of digitally interconnected products, or ‘things,’ that improve convenience, possibilities, and in some cases efficiency for consumers. Nonetheless, even as the market accelerates, this Internet of ‘things’ is subject to substantial leakage of consumer personal data. First defining the fluid concept of ‘things,’ this paper subsequently uses case studies taken from the EU, Asia, and the US, to highlight large gaps and comprehensively evaluate the state of security for consumer ‘things.’ Ultimately, this paper offers several ways of improving the present status quo, and especially focuses on an evaluative approach that augments the standard mechanism of Firmware Over the Air Updates, and ought to be easily implementable.

Keywords: cybersecurity, FOTA, Internet of Things, transnational privacy

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Authors: Xiang Shijie, Zhou Dong, Tian Dan

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This paper focuses on the application of real-time semantic segmentation technology in complex road condition recognition, aiming to address the critical issue of how to improve segmentation accuracy while ensuring real-time performance. Semantic segmentation technology has broad application prospects in fields such as autonomous vehicle navigation and remote sensing image recognition. However, current real-time semantic segmentation networks face significant technical challenges and optimization gaps in balancing speed and accuracy. To tackle this problem, this paper conducts an in-depth study and proposes an innovative Guided Image Reconstruction Module. By resampling high-resolution images into a set of low-resolution images, this module effectively reduces computational complexity, allowing the network to more efficiently extract features within limited resources, thereby improving the performance of real-time segmentation tasks. In addition, a dual-branch network structure is designed in this paper to fully leverage the advantages of different feature layers. A novel Hybrid Attention Mechanism is also introduced, which can dynamically capture multi-scale contextual information and effectively enhance the focus on important features, thus improving the segmentation accuracy of the network in complex road condition. Compared with traditional methods, the proposed model achieves a better balance between accuracy and real-time performance and demonstrates competitive results in road condition segmentation tasks, showcasing its superiority. Experimental results show that this method not only significantly improves segmentation accuracy while maintaining real-time performance, but also remains stable across diverse and complex road conditions, making it highly applicable in practical scenarios. By incorporating the Guided Image Reconstruction Module, dual-branch structure, and Hybrid Attention Mechanism, this paper presents a novel approach to real-time semantic segmentation tasks, which is expected to further advance the development of this field.

Keywords: hybrid attention mechanism, image reconstruction, real-time, road status recognition

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Authors: Emily Saurman, David Lyle

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In Australia, a well serviced rural town might have a psychiatrist visit once-a-month with more frequent visits from a psychiatric nurse, but many have no resident access to mental health specialists. Access to specialist care, would not only reduce patient distress and benefit outcomes, but facilitate the effective use of limited resources. The Mental Health Emergency Care-Rural Access Program (MHEC-RAP) was developed to improve access to specialist emergency mental health care in rural and remote communities using telehealth technologies. However, there has been no current benchmark to gauge program efficiency or capacity; to determine whether the program activity is justifiably sufficient. The evaluation of MHEC-RAP used multiple methods and applied a modified theory of access to assess the program and its aim of improved access to emergency mental health care. This was the first evaluation of a telepsychiatry service to include a time and motion study design examining program time expenditure, efficiency, and capacity. The time and motion study analysis was combined with an observational study of the program structure and function to assess the balance between program responsiveness and efficiency. Previous program studies have demonstrated that MHEC-RAP has improved access and is used and effective. The findings from the time and motion study suggest that MHEC-RAP has the capacity to manage increased activity within the current model structure without loss to responsiveness or efficiency in the provision of care. Enhancing program responsiveness and efficiency will also support a claim of the program’s value for money. MHEC-RAP is a practical telehealth solution for improving access to specialist emergency mental health care. The findings from this evaluation have already attracted the attention of other regions in Australia interested in implementing emergency telepsychiatry programs and are now informing the progressive establishment of mental health resource centres in rural New South Wales. Like MHEC-RAP, these centres will provide rapid, safe, and contextually relevant assessments and advice to support local health professionals to manage mental health emergencies in the smaller rural emergency departments. Sharing the application of this methodology and research activity may help to improve access to and future evaluations of telehealth and telepsychiatry services for others around the globe.

Keywords: access, emergency, mental health, rural, time and motion

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Authors: Subodh Chandra Shakya, Rajendra Sapkota, Aakash Tamang, Shushant Pudasaini, Sujan Adhikari, Sajjan Adhikari

Abstract:

Lots of efforts have been made in order to measure the semantic similarity between the text corpora in the documents. Techniques have been evolved to measure the similarity of two documents. One such state-of-art technique in the field of Natural Language Processing (NLP) is word to vector models, which converts the words into their word-embedding and measures the similarity between the vectors. We found this to be quite useful for the task of resume ranking. So, this research paper is the implementation of the word2vec model along with other Natural Language Processing techniques in order to rank the resumes for the particular job description so as to automate the process of hiring. The research paper proposes the system and the findings that were made during the process of building the system.

Keywords: chunking, document similarity, information extraction, natural language processing, word2vec, word embedding

Procedia PDF Downloads 157

Authors: Emiliano Castillo

Abstract:

The aim of this research is to analyze the origins, the development and possible outcomes of the environmental conflict between grassroots organizations, indigenous communities, Kinder Morgan Corporation, and the Canadian government over the Trans Mountain pipeline expansion in Burnaby, British Columbia, Canada. Building on the political ecology and the environmental justice theoretical framework, this research examines the impacts and risks of tar sands extraction, production, and transportation on climate change, public health, the environment, and indigenous people´s rights over their lands. This study is relevant to the environmental justice and political ecology literature because it discusses the unequal distribution of environmental costs and economic benefits of tar sands development; and focuses on the competing interests, needs, values, and claims of the actors involved in the conflict. Furthermore, it will shed light on the context, conditions, and processes that lead to the organization and mobilization of a grassroots movement- comprised of indigenous communities, citizens, scientists, and non-governmental organizations- that draw significant media attention by opposing the Trans Mountain pipeline expansion. Similarly, the research will explain the differences and dynamics within the grassroots movement. This research seeks to address the global context of the conflict by studying the links between the decline of conventional oil production, the rise of unconventional fossil fuels (e.g. tar sands), climate change, and the struggles of low-income, ethnic, and racial minorities over the territorial expansion of extractive industries. Data will be collected from legislative documents, policy and technical reports, scientific journals, newspapers articles, participant observation, and semi-structured interviews with representatives and members of the grassroots organizations, indigenous communities, and Burnaby citizens that oppose the Trans Mountain pipeline. These interviews will focus on their perceptions of the risks of the Trans Mountain pipeline expansion; the roots of the anti-tar sands movement; the differences and dynamics within the movement; and the strategies to defend the livelihoods of local communities and the environment against tar sands development. This research will contribute to the understanding of the underlying causes of the environmental conflict between the Canadian government, Kinder Morgan, and grassroots organizations over tar sands extraction, production, and transportation in Burnaby, British Columbia, Canada. Moreover, this work will elucidate the transformations of society-nature relationships brought by tar sands development. Research findings will provide scientific information about how the resistance movement in British Columbia can challenge the dominant narrative on tar sands, exert greater influence in environmental politics, and efficiently defend Indigenous people´s rights to lands. Furthermore, this research will shed light into how grassroots movements can contribute towards the building of more inclusive and sustainable societies.

Keywords: environmental conflict, environmental justice, extractive industry, indigenous communities, political ecology, tar sands

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Authors: Elvira S. Castillo, Surupa Shaw

Abstract:

This paper explores advanced applications of fluid mechanics in the context of sustainable energy. By examining the integration of fluid dynamics with renewable energy technologies, the research uncovers previously underutilized strategies for improving efficiency. Through theoretical analyses, the study demonstrates how fluid mechanics can be harnessed to optimize renewable energy systems. The findings contribute to expanding knowledge in sustainable energy by offering practical insights and methodologies for future research and technological advancements to address global energy challenges.

Keywords: fluid mechanics, sustainable energy, energy efficiency, green energy

Procedia PDF Downloads 48

Authors: Lana Migla

Abstract:

Phase change materials (PCMs) have an important role in improving the efficiency of thermal heat storage. As these materials are characterized by low thermal conductivity, it is necessary to develop heat transfer techniques to improve their thermophysical properties. This scientific article focuses on the geometrical configurations of encapsulated PCM containers and the impact of designs to improve the performance of the solar thermal cooling system. The literature review showed that in-depth research is being conducted on different methods of improving the efficiency of PCM heat transfer, which is the main design task for the containers. Techniques such as microencapsulated PCMs, adding fins and different combinations of fins and nanoparticles are used. The use of graphite, metal foam and doping of high photothermal materials is also being studied. To determine most efficient container configuration, the article looks at different designs of PCM containers with fins for the storage tank. This paper experimentally investigates the effect of the encapsulation design on the performance of a lab-scale thermal energy storage tank. The development of optimized energy storage with integrated phase change material containers reduces auxiliary heater energy consumption, increases the COP of the solar cooling system, and reduces the environmental impact of the cooling system. The review shows that in the cylindrical construction, the ratio between the radius of shell and tube is significant, which means this ratio is the main issue to enhance transfer efficiency and to increase the value of stored heat. Therefore, three cylindrical tube containers with different radiuses 20mm, 35mm, 50mm filled with commercial phase change material were tested. The results show that using a smaller radius achieved a higher power, leading to a reduction in the charging and discharging time. The three fins were added to the selected cylindrical tube to determine their effects on heat exchanging efficiency. The observed optimized performance given by the fin’s arrangement achieved a 40% reduction of PCM's melting time compared to the heat exchanging without fins. The exact dimensions of the PCM containers and fins placements will be presented on-site.

Keywords: energy performance, PCM containers, solar thermal cooling, storage tank

Procedia PDF Downloads 138

Authors: M. A. El-Khateeb

Abstract:

The growth of the olive oil production in Saudi Arabia peculiarly in Al Jouf region in recent years has been accompanied by an increase in the discharge of associated processing waste. Olive mill waste is produced throughout the extraction of oil from the olive fruit using the traditional mill and press process. Deterioration of the environment due to olive mill disposal wastes is a serious problem. When olive mill waste disposed into the soil, it affects soil quality, soil micro flora, and also toxic to plants. The aim of this work is to isolate microorganism (bacterial or fungal strains) from OMW capable of degrading phenols. Olive mill wastewater, olive mill waste and soil (beside oil production mill) contaminated with olive waste were used for isolation of phenol tolerant microorganisms. Four strains (two fungal and two bacterial) were isolated from olive mill waste. The isolated strains were Candida tropicalis and Phanerochaete chrysosporium (fungal strains) and Bacillus sp. and Rhodococcus sp. (bacterial strains). These strains were able to degrade phenols and could be used for bioremediation of olive mill waste.

Keywords: bioremediation, bacteria, fungi, Sakaka

Procedia PDF Downloads 360