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702 Risk and Vulnerability Assessment of Agriculture on Climate Change: Bangnampriao District, Thailand
Authors: Charuvan Kasemsap
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This research was studied in Bangnampriao District, Chachernsao Province, Thailand. The primary data relating to flooding, drought, and saline intrusion problem on agriculture were collected by surveying, focus group, and in-depth interview with agricultural officers, technical officers of irrigation department, and local government leader of Bangnampriao District. The likelihood and consequence of risk were determined the risk index by risk assessment matrix. In addition, the risk index and the total coping capacity scores were investigated the vulnerability index by vulnerability matrix. It was found that the high-risk drought and saline intrusion was dramatically along Bang Pakong River owing to the end destination of Chao Phraya Irrigation system of Central Thailand. This leads yearly the damage of rice paddy, mango tree, orchard, and fish pond. Therefore, some agriculture avoids rice growing during January to May, and also pumps fresh water from a canal into individual storage pond. However, Bangnampriao District will be strongly affected by the impacts of climate change. Monthly precipitations are expected to decrease in number; dry seasons are expected to be more in number and longer in duration. Thus, the risk and vulnerability of agriculture are also increasing. Adaptation strategies need to be put in place in order to enhance the resilience of the agriculture.Keywords: agriculture, bangnampriao, climate change, risk assessment
Procedia PDF Downloads 425701 Performance Comparison of Situation-Aware Models for Activating Robot Vacuum Cleaner in a Smart Home
Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu
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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.Keywords: situation-awareness, smart home, IoT, machine learning, classifier
Procedia PDF Downloads 413700 Fruit Identification System in Sweet Orange Citrus (L.) Osbeck Using Thermal Imaging and Fuzzy
Authors: Ingrid Argote, John Archila, Marcelo Becker
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In agriculture, intelligent systems applications have generated great advances in automating some of the processes in the production chain. In order to improve the efficiency of those systems is proposed a vision system to estimate the amount of fruits in sweet orange trees. This work presents a system proposal using capture of thermal images and fuzzy logic. A bibliographical review has been done to analyze the state-of-the-art of the different systems used in fruit recognition, and also the different applications of thermography in agricultural systems. The algorithm developed for this project uses the metrics of the fuzzines parameter to the contrast improvement and segmentation of the image, for the counting algorith m was used the Hough transform. In order to validate the proposed algorithm was created a bank of images of sweet orange Citrus (L.) Osbeck acquired in the Maringá Farm. The tests with the algorithm Indicated that the variation of the tree branch temperature and the fruit is not very high, Which makes the process of image segmentation using this differentiates, This Increases the amount of false positives in the fruit counting algorithm. Recognition of fruits isolated with the proposed algorithm present an overall accuracy of 90.5 % and grouped fruits. The accuracy was 81.3 %. The experiments show the need for a more suitable hardware to have a better recognition of small temperature changes in the image.Keywords: Agricultural systems, Citrus, Fuzzy logic, Thermal images.
Procedia PDF Downloads 225699 The Agency of Award Systems in Architecture: The Case of Cyprus
Authors: Christakis Chatzichristou, Elias Kranos
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Architectural awards, especially if they are given by the state, recognize excellence in the field and, at the same time, strongly contribute to the making of the architectural culture of a place. The present research looks at the houses that have been awarded through such a system in Cyprus in order to discuss the values promoted, directly or not, by such a setup which is quite similar to other prestigious award systems such as the Mies van de Rohe Prize in Europe. In fact, many of the projects signed out through the state award system end up being selected to represent the country for the European awards. The residential architecture encouraged by such systems is quite interesting in that the most public of institutions influence how the most private unit of society is architecturally accommodated. The methodology uses both qualitative as well as quantitative research tools in order to analyze: the official state call for entries to the competition; the final report of the evaluation committee; the spatial characteristics of the houses through the Space Syntax methodology; the statements of the architects regarding their intentions and the final outcome; the feelings of the owners and users of the houses regarding the design process as well as the degree of satisfaction regarding the final product. The above-mentioned analyses allow for a more thorough discussion regarding not only the values promoted explicitly by the system through the brief that describes what the evaluation committee is looking for but also the values that are actually being promoted indirectly through the results of the actual evaluation itself. The findings suggest that: the strong emphasis in brief on bioclimatic design and issues of sustainability weakens significantly, if at all present, in the actual selection process; continuous improvement seems to be fuzzily used as a concept; most of the houses tend to have a similar spatial genotype; most of the houses have similar aesthetic qualities; discrepancies between the proposed lifestyle through the design and the actual use of the spaces do not seem to be acknowledged in the evaluation as an issue; the temporal factor seems to be ignored as the projects are required to be ‘finished projects’ as though the users and their needs do not change through time. The research suggests that, rather than preserving a critical attitude regarding the role of the architect in society, the state award system tends, like any other non-reflective social organism, to simply promote its own unexamined values as well as prejudices. This is perhaps more evident in the shared aesthetic character of the awarded houses and less so in the hidden spatial genotype to which they belong. If the design of houses is indeed a great opportunity for architecture to contribute in a more deliberate manner to the evolution of society, then what the present study shows is that this opportunity seems to be largely missed. The findings may serve better less as a verdict and more as a chance for introspection and discussion.Keywords: award systems, houses, spatial genotype, aesthetic qualities
Procedia PDF Downloads 62698 A Machine Learning Model for Predicting Students’ Academic Performance in Higher Institutions
Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu
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There has been a need in recent years to predict student academic achievement prior to graduation. This is to assist them in improving their grades, especially for those who have struggled in the past. The purpose of this research is to use supervised learning techniques to create a model that predicts student academic progress. Many scholars have developed models that predict student academic achievement based on characteristics including smoking, demography, culture, social media, parent educational background, parent finances, and family background, to mention a few. This element, as well as the model used, could have misclassified the kids in terms of their academic achievement. As a prerequisite to predicting if the student will perform well in the future on related courses, this model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester. With a 96.7 percent accuracy, the model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost. This model is offered as a desktop application with user-friendly interfaces for forecasting student academic progress for both teachers and students. As a result, both students and professors are encouraged to use this technique to predict outcomes better.Keywords: artificial intelligence, ML, logistic regression, performance, prediction
Procedia PDF Downloads 101697 The Diversity of DRB1 Locus of Exon 2 of MHC Molecule of Sudanese Indigenous Desert Sheep
Authors: Muna A. Eissawi, Safaa Abed Elfataah, Haytham Hago, Fatima E Abukunna, Ibtisam Amin Goreish, Nahid Gornas
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The study examined and analyzed the genetic diversity of DRB1locus of exon 2 of major histocompatibility complex of Sudanese desert sheep using PCR-RFLP and DNA sequencing. Five hundred samples belonging to five ecotypes of Desert Sudanese sheep (Abrag (Ab), Ashgar (Ash), Hamari (H), Kabashi (K) and Watish (W) were included. Amplification of exon 2 of the DRB1 gene yielded (300bp) amplified product in different ecotypes. Nine different digestion patterns corresponding to Five distinct alleles were observed with Rsa1 digestion. Genotype (ag) was the most common among all ecotypes, with a percentage comprised (40.4 %). The Hardy-Weinberg equilibrium (HWE) test showed that the studied ecotypes have significantly deviated from the theoretical proportions of Rsa1 patterns; probability values of the Chi-square test for HWE for MHC-DRB1 gene in SDS were 0.00 in all ecotypes. The constructed phylogenetic tree revealed the relation of 22 Sudanese isolates with each other and showed the shared sequences with 47 published foreign sequences randomly selected from different geographic regions. The results of this study highlight the effect of heterozygosity of MHC genes of the Desert sheep of Sudan which may clarify some of genetic back ground of their disease resistance and adaptation to environment.Keywords: desert sheep, MHC, Ovar-DRB1, polymerase chain reaction (PCR), restriction fragment length polymorphism (RFLP)
Procedia PDF Downloads 68696 Classification of Potential Biomarkers in Breast Cancer Using Artificial Intelligence Algorithms and Anthropometric Datasets
Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi
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Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.Keywords: breast cancer, diagnosis, machine learning, biomarker classification, neural network
Procedia PDF Downloads 127695 Fruit Growing in Romania and Its Role for Rural Communities’ Development
Authors: Maria Toader, Gheorghe Valentin Roman
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The importance of fruit trees and bushes growing for Romania is due the concordance that exists between the different ecological conditions in natural basins, and the requirements of different species and varieties. There are, in Romania, natural areas dedicated to the main trees species: plum, apple, pear, cherry, sour cherry, finding optimal conditions for harnessing the potential of fruitfulness, making fruit quality both in terms of ratio commercial, and content in active principles. The share of fruits crops in the world economy of agricultural production is due primarily to the role of fruits in nourishment for human, and in the prevention and combating of diseases, in increasing the national income of cultivator countries and to improve comfort for human life. For Romania, the perspectives of the sector are positive, and are due to European funding opportunities, which provide farmers a specialized program that meets the needs of development and modernization of fruit growing industry, cultivation technology and equipment, organization and grouping of producers, creating storage facilities, conditioning, marketing and the joint use of fresh fruit. This paper shows the evolution of fruit growing, in Romania compared to other states. The document presents the current situation of the main tree species both in terms of surface but also of the productions and the role that this activity may have for the development of rural communities.Keywords: fruit growing, fruits trees, productivity, rural development
Procedia PDF Downloads 254694 Low-Dose Chest Computed Tomography Can Help in Differential Diagnosis of Asthma–COPD Overlap Syndrome in Children
Authors: Frantisek Kopriva, Kamila Michalkova, Radim Dudek, Jana Volejnikova
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Rationale: Diagnostic criteria of asthma–COPD overlap syndrome (ACOS) are controversial in pediatrics. Emphysema is characteristic of COPD and usually does not occur in typical asthma; its presence in patients with asthma suggests the concurrence with COPD. Low-dose chest computed tomography (CT) allows a non-invasive assessment of the lung tissue structure. Here we present CT findings of emphysematous changes in a child with ACOS. Patient and Methods: In a 6-year-old boy, atopy was confirmed by a skin prick test using common allergen extracts (grass and tree pollen, house dust mite, molds, cat, dog; manufacturer Stallergenes Greer, London, UK), where reactions over 3 mm were considered positive. Treatment with corticosteroids was started during the course of severe asthma. At 12 years of age, his spirometric parameters deteriorated despite treatment adjustment (VC 1.76 L=85%, FEV1 1.13 L=67%, TI%VCmax 64%, MEF25 19%, TLC 144%) and the bronchodilator test became negative. Results: Low-dose chest CT displayed irregular regions with increased radiolucency of pulmonary parenchyma (typical for hyperinflation in emphysematous changes) in both lungs. This was in accordance with the results of spirometric examination. Conclusions: ACOS is infrequent in children. However, low-dose chest CT scan can be considered to confirm this diagnosis or eliminate other diagnoses when the clinical condition is deteriorating and treatment response is poor.Keywords: child, asthma, low-dose chest CT, ACOS
Procedia PDF Downloads 141693 Traumatic Brachiocephalic Artery Pseudoaneurysm
Authors: Sally Shepherd, Jessica Wong, David Read
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Traumatic brachiocephalic artery aneurysm is a rare injury that typically occurs as a result of a blunt chest injury. A 19-year-old female sustained a head-on, high speed motor vehicle crash into a tree. Upon release after 45 minutes of entrapment, she was tachycardic but normotensive, with a significant seatbelt sign across her chest and open deformed right thigh with weak pulses in bilateral lower limbs. A chest XR showed mild upper mediastinal widening. A CT trauma series plus gated CT chest revealed a grade 3a aortic arch transection with brachiocephalic pseudoaneurysm. Endovascular repair of the brachiocephalic artery was attempted post-presentation but was unsuccessful as the first stent migrated to the infrarenal abdominal aorta and the second stent across the brachiocephalic artery origin had a persistent leak at the base. She was transferred to Intensive Care for strict blood pressure control. She returned to theatre 5 hours later for a median sternotomy, aortic arch repair with an 8mm graft extraction, and excision of the innominate artery pseudoaneurysm. She had an uncomplicated post-operative recovery. This case highlights that brachiocephalic artery injury is a rare but potentially lethal injury as a result of blunt chest trauma. Safe management requires a combined Vascular and Cardiothoracic team approach, as stenting alone may be insufficient.Keywords: blunt chest injury, Brachiocephalic aneurysm, innominate artery, trauma
Procedia PDF Downloads 227692 Comparative Analysis of Classification Methods in Determining Non-Active Student Characteristics in Indonesia Open University
Authors: Dewi Juliah Ratnaningsih, Imas Sukaesih Sitanggang
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Classification is one of data mining techniques that aims to discover a model from training data that distinguishes records into the appropriate category or class. Data mining classification methods can be applied in education, for example, to determine the classification of non-active students in Indonesia Open University. This paper presents a comparison of three methods of classification: Naïve Bayes, Bagging, and C.45. The criteria used to evaluate the performance of three methods of classification are stratified cross-validation, confusion matrix, the value of the area under the ROC Curve (AUC), Recall, Precision, and F-measure. The data used for this paper are from the non-active Indonesia Open University students in registration period of 2004.1 to 2012.2. Target analysis requires that non-active students were divided into 3 groups: C1, C2, and C3. Data analyzed are as many as 4173 students. Results of the study show: (1) Bagging method gave a high degree of classification accuracy than Naïve Bayes and C.45, (2) the Bagging classification accuracy rate is 82.99 %, while the Naïve Bayes and C.45 are 80.04 % and 82.74 % respectively, (3) the result of Bagging classification tree method has a large number of nodes, so it is quite difficult in decision making, (4) classification of non-active Indonesia Open University student characteristics uses algorithms C.45, (5) based on the algorithm C.45, there are 5 interesting rules which can describe the characteristics of non-active Indonesia Open University students.Keywords: comparative analysis, data mining, clasiffication, Bagging, Naïve Bayes, C.45, non-active students, Indonesia Open University
Procedia PDF Downloads 308691 Growth and Laying Performance of Commercial Hens Fed with Varying Levels of Trichanthera gigantea (Nees.) Leaf Meal
Authors: Carmel Khrisna Wong Moreno, Dinah M. Espina
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The increasing price of feed ingredients has prompted farmers to seek feasible feed alternatives like the utilization of locally-grown protein-rich feedstuff which is cheaper but gives a positive result in poultry production. Trichanthera gigantea, a fodder tree which is an excellent alternative as feed ingredient in the Philippines has now gained popularity as feed supplement. This study was conducted to determine the growth and laying performance of commercial hens fed with varying levels of Trichanthera gigantea leaf meal. The incorporation of Trichanthera gigantea leaf meal at 5%, 10%, and 15% into the diet of commercial hens did not affect the growth and laying performance. Results of the study revealed that the weight gain of the birds fed with Trichanthera gigantea supplemented diets was not significantly different with the control (100% commercial layer mash). The voluntary feed intake, feed conversion ratio, weekly average egg weight and egg production of the commercial hens fed with T. gigantea leaf meal supplemented diets were not significantly different from the control. Results of the study showed that the supplementation of Trichanthera gigantea leaf meal of up to 15% into the diets of commercial hens is highly acceptable since it does not affect the growth and laying performance of the birds. In addition, it would mean a 15% savings in production cost from commercial feeds.Keywords: egg production, growth, laying performance, trichanthera gigantea (nees)
Procedia PDF Downloads 413690 Archaic Ontologies Nowadays: Music of Rituals
Authors: Luminiţa Duţică, Gheorghe Duţică
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Many of the interrogations or dilemmas of the contemporary world found the answer in what was generically called the appeal to matrix. This genuine spiritual exercise of re-connection of the present to origins, to the primary source, revealed the ontological condition of timelessness, ahistorical, immutable (epi)phenomena, of those pure essences concentrated in the archetypal-referential layer of the human existence. The musical creation was no exception to this trend, the impasse generated by the deterministic excesses of the whole serialism or, conversely, by some questionable results of the extreme indeterminism proper to the avant-garde movements, stimulating the orientation of many composers to rediscover a universal grammar, as an emanation of a new ‘collective’ order (reverse of the utopian individualism). In this context, the music of oral tradition and therefore the world of the ancient modes represented a true revelation for the composers of the twentieth century, who were suddenly in front of some unsuspected (re)sources, with a major impact on all levels of edification of the musical work: morphology, syntax, timbrality, semantics etc. For the contemporary Romanian creators, the music of rituals, existing in the local archaic culture, opened unsuspected perspectives for which it meant to be a synthetic, inclusive and recoverer vision, where the primary (archetypal) genuine elements merge with the latest achievements of language of the European composers. Thus, anchored in a strong and genuine modal source, the compositions analysed in this paper evoke, in a manner as modern as possible, the atmosphere of some ancestral rituals such as: the invocation of rain during the drought (Paparudele, Scaloianul), funeral ceremony (Bocetul), traditions specific to the winter holidays and new year (Colinda, Cântecul de stea, Sorcova, Folklore traditional dances) etc. The reactivity of those rituals in the sound context of the twentieth century meant potentiating or resizing the archaic spirit of the primordial symbolic entities, in terms of some complexity levels generated by the technique of harmonies of chordal layers, of complex aggregates (gravitational or non-gravitational, geometric), of the mixture polyphonies and with global effect (group, mass), by the technique of heterophony, of texture and cluster, leading to the implementation of some processes of collective improvisation and instrumental theatre.Keywords: archetype, improvisation, polyphony, ritual, instrumental theatre
Procedia PDF Downloads 300689 Influence of Agroforestry Trees Leafy Biomass and Nitrogen Fertilizer on Crop Growth Rate and Relative Growth Rate of Maize
Authors: A. B. Alarape, O. D. Aba
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The use of legume tree pruning as mulch in agroforestry system is a common practice to maintain soil organic matter and improve soil fertility in the tropics. The study was conducted to determine the influence of agroforestry trees leafy biomass and nitrogen fertilizer on crop growth rate and relative growth rate of maize. The experiments were laid out as 3 x 4 x 2 factorial in a split-split plot design with three replicates. Control, biomass species (Parkia biglobosa and Albizia lebbeck) as main plots were considered, rates of nitrogen considered include (0, 40, 80, 120 kg N ha⁻¹) as sub-plots, and maize varieties (DMR-ESR-7 and 2009 EVAT) were used as sub-sub plots. Data were analyzed using descriptive and inferential statistics (ANOVA) at α = 0.05. Incorporation of leafy biomass was significant in 2015 on Relative Growth Rate (RGR), while nitrogen application was significant on Crop Growth Rate (CGR). 2009 EVAT had higher CGR in 2015 at 4-6 and 6-8 WAP. Incorporation of Albizia leaves enhanced the growth of maize than Parkia leaves. Farmers are, therefore, encouraged to use Albizia leaves as mulch to enrich their soil for maize production and most especially, in case of availability of inorganic fertilizers. Though, production of maize with biomass and application of 120 kg N ha⁻¹ will bring better growth of maize.Keywords: agroforestry trees, fertilizer, growth, incorporation, leafy biomass
Procedia PDF Downloads 182688 Fighting the Crisis with 4.0 Competences: Higher Education Projects in the Times of Pandemic
Authors: Jadwiga Fila, Mateusz Jezowski, Pawel Poszytek
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The outbreak of the global COVID-19 pandemic started the times of crisis full of uncertainty, especially in the field of transnational cooperation projects based on the international mobility of their participants. This is notably the case of Erasmus+ Program for higher education, which is the flagship European initiative boosting cooperation between educational institutions, businesses, and other actors, enabling students and staff mobility, as well as strategic partnerships between different parties. The aim of this abstract is to study whether competences 4.0 are able to empower Erasmus+ project leaders in sustaining their international cooperation in times of global crisis, widespread online learning, and common project disruption or cancellation. The concept of competences 4.0 emerged from the notion of the industry 4.0, and it relates to skills that are fundamental for the current labor market. For the aim of the study presented in this abstract, four main 4.0 competences were distinguished: digital, managerial, social, and cognitive competence. The hypothesis for the study stipulated that the above-mentioned highly-developed competences may act as a protective shield against the pandemic challenges in terms of projects’ sustainability and continuation. The objective of the research was to assess to what extent individual competences are useful in managing projects in times of crisis. For this purpose, the study was conducted, involving, among others, 141 Polish higher education project leaders who were running their cooperation projects during the peak of the COVID-19 pandemic (Mar-Nov 2020). The research explored the self-perception of the above-mentioned competences among Erasmus+ project leaders and the contextual data regarding the sustainability of the projects. The quantitative character of data permitted validation of scales (Cronbach’s Alfa measure), and the use of factor analysis made it possible to create a distinctive variable for each competence and its dimensions. Finally, logistic regression was used to examine the association of competences and other factors on project status. The study shows that the project leaders’ competence profile attributed the highest score to digital competence (4.36 on the 1-5 scale). Slightly lower values were obtained for cognitive competence (3.96) and managerial competence (3.82). The lowest score was accorded to one specific dimension of social competence: adaptability and ability to manage stress (1.74), which proves that the pandemic was a real challenge which had to be faced by project coordinators. For higher education projects, 10% were suspended or prolonged because of the COVID-19 pandemic, whereas 90% were undisrupted (continued or already successfully finished). The quantitative analysis showed a positive relationship between the leaders’ levels of competences and the projects status. In the case of all competences, the scores were higher for project leaders who finished projects successfully than for leaders who suspended or prolonged their projects. The research demonstrated that, in the demanding times of the COVID-19 pandemic, competences 4.0, to a certain extent, do play a significant role in the successful management of Erasmus+ projects. The implementation and sustainability of international educational projects, despite mobility and sanitary obstacles, depended, among other factors, on the level of leaders’ competences.Keywords: Competences 4.0, COVID-19 pandemic, Erasmus+ Program, international education, project sustainability
Procedia PDF Downloads 87687 Comparation of Essential Oils Composition from the Leaves and Flowers of Salvia pratensis L.
Authors: Valerija Dunkić, Nada Bezić
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Salvia is a genus of the well-known medicinal plant of Lamiaceae family and growing wild throughout the world. This abstract reports the comparation of the essential oils from leaves and flowers composition of Salvia pratensis L. from mountain Velebit, Croatia. Water distilled essential oils from aerial parts of investigation plant have been analysed by GC and GC/MS using VF-5ms capillary column. Fifty-three constituents, representing 99.4% of the leaf oil composition; 51 constituents, representing 86.8% of the flower oil composition. Essential oil yield varied from 0.9% to 1.3% in the leaf and flower parts of the plant. The flower essential oil was characterized by a high concentration of E-caryophyllene (21.9%) and germacrene D (10.2%). Major constituents of the leaf oil were linalool (17.7%), linalool acetate (15.3%) and limonene (9.8%). The comparative results clearly indicated that the leaf and flower oil compositions of S. pratensis were quite different in terms of major components content. The present study gives additional knowledge about secondary metabolites contents on the genus Salvia.Keywords: essential oil, leaf, flower, Salvia pratensis L.
Procedia PDF Downloads 297686 Quantifying Freeway Capacity Reductions by Rainfall Intensities Based on Stochastic Nature of Flow Breakdown
Authors: Hoyoung Lee, Dong-Kyu Kim, Seung-Young Kho, R. Eddie Wilson
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This study quantifies a decrement in freeway capacity during rainfall. Traffic and rainfall data were gathered from Highway Agencies and Wunderground weather service. Three inter-urban freeway sections and its nearest weather stations were selected as experimental sites. Capacity analysis found reductions of maximum and mean pre-breakdown flow rates due to rainfall. The Kruskal-Wallis test also provided some evidence to suggest that the variance in the pre-breakdown flow rate is statistically insignificant. Potential application of this study lies in the operation of real time traffic management schemes such as Variable Speed Limits (VSL), Hard Shoulder Running (HSR), and Ramp Metering System (RMS), where speed or flow limits could be set based on a number of factors, including rainfall events and their intensities.
Keywords: capacity randomness, flow breakdown, freeway capacity, rainfall
Procedia PDF Downloads 376685 Analyzing the Impact of Global Financial Crisis on Interconnectedness of Asian Stock Markets Using Network Science
Authors: Jitendra Aswani
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In the first section of this study, impact of Global Financial Crisis (GFC) on the synchronization of fourteen Asian Stock Markets (ASM’s) of countries like Hong Kong, India, Thailand, Singapore, Taiwan, Pakistan, Bangladesh, South Korea, Malaysia, Indonesia, Japan, China, Philippines and Sri Lanka, has been analysed using the network science and its metrics like degree of node, clustering coefficient and network density. Then in the second section of this study by introducing the US stock market in existing network and developing a Minimum Spanning Tree (MST) spread of crisis from the US stock market to Asian Stock Markets (ASM) has been explained. Data used for this study is adjusted the closing price of these indices from 6th January, 2000 to 15th September, 2013 which further divided into three sub-periods: Pre, during and post-crisis. Using network analysis, it is found that Asian stock markets become more interdependent during the crisis than pre and post crisis, and also Hong Kong, India, South Korea and Japan are systemic important stock markets in the Asian region. Therefore, failure or shock to any of these systemic important stock markets can cause contagion to another stock market of this region. This study is useful for global investors’ in portfolio management especially during the crisis period and also for policy makers in formulating the financial regulation norms by knowing the connections between the stock markets and how the system of these stock markets changes in crisis period and after that.Keywords: global financial crisis, Asian stock markets, network science, Kruskal algorithm
Procedia PDF Downloads 411684 Software Component Identification from Its Object-Oriented Code: Graph Metrics Based Approach
Authors: Manel Brichni, Abdelhak-Djamel Seriai
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Systems are increasingly complex. To reduce their complexity, an abstract view of the system can simplify its development. To overcome this problem, we propose a method to decompose systems into subsystems while reducing their coupling. These subsystems represent components. Consisting of an existing object-oriented systems, the main idea of our approach is based on modelling as graphs all entities of an oriented object source code. Such modelling is easy to handle, so we can apply restructuring algorithms based on graph metrics. The particularity of our approach consists in integrating in addition to standard metrics, such as coupling and cohesion, some graph metrics giving more precision during the components identication. To treat this problem, we relied on the ROMANTIC approach that proposed a component-based software architecture recovery from an object oriented system.Keywords: software reengineering, software component and interfaces, metrics, graphs
Procedia PDF Downloads 497683 Performance Assessment of Multi-Level Ensemble for Multi-Class Problems
Authors: Rodolfo Lorbieski, Silvia Modesto Nassar
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Many supervised machine learning tasks require decision making across numerous different classes. Multi-class classification has several applications, such as face recognition, text recognition and medical diagnostics. The objective of this article is to analyze an adapted method of Stacking in multi-class problems, which combines ensembles within the ensemble itself. For this purpose, a training similar to Stacking was used, but with three levels, where the final decision-maker (level 2) performs its training by combining outputs from the tree-based pair of meta-classifiers (level 1) from Bayesian families. These are in turn trained by pairs of base classifiers (level 0) of the same family. This strategy seeks to promote diversity among the ensembles forming the meta-classifier level 2. Three performance measures were used: (1) accuracy, (2) area under the ROC curve, and (3) time for three factors: (a) datasets, (b) experiments and (c) levels. To compare the factors, ANOVA three-way test was executed for each performance measure, considering 5 datasets by 25 experiments by 3 levels. A triple interaction between factors was observed only in time. The accuracy and area under the ROC curve presented similar results, showing a double interaction between level and experiment, as well as for the dataset factor. It was concluded that level 2 had an average performance above the other levels and that the proposed method is especially efficient for multi-class problems when compared to binary problems.Keywords: stacking, multi-layers, ensemble, multi-class
Procedia PDF Downloads 263682 Co-Integration Model for Predicting Inflation Movement in Nigeria
Authors: Salako Rotimi, Oshungade Stephen, Ojewoye Opeyemi
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The maintenance of price stability is one of the macroeconomic challenges facing Nigeria as a nation. This paper attempts to build a co-integration multivariate time series model for inflation movement in Nigeria using data extracted from the abstract of statistics of the Central Bank of Nigeria (CBN) from 2008 to 2017. The Johansen cointegration test suggests at least one co-integration vector describing the long run relationship between Consumer Price Index (CPI), Food Price Index (FPI) and Non-Food Price Index (NFPI). All three series show increasing pattern, which indicates a sign of non-stationary in each of the series. Furthermore, model predictability was established with root-mean-square-error, mean absolute error, mean average percentage error, and Theil’s unbiased statistics for n-step forecasting. The result depicts that the long run coefficient of a consumer price index (CPI) has a positive long-run relationship with the food price index (FPI) and non-food price index (NFPI).Keywords: economic, inflation, model, series
Procedia PDF Downloads 237681 Logistic Regression Based Model for Predicting Students’ Academic Performance in Higher Institutions
Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu
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In recent years, there has been a desire to forecast student academic achievement prior to graduation. This is to help them improve their grades, particularly for individuals with poor performance. The goal of this study is to employ supervised learning techniques to construct a predictive model for student academic achievement. Many academics have already constructed models that predict student academic achievement based on factors such as smoking, demography, culture, social media, parent educational background, parent finances, and family background, to name a few. This feature and the model employed may not have correctly classified the students in terms of their academic performance. This model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester as a prerequisite to predict if the student will perform well in future on related courses. The model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost, returning a 96.7% accuracy. This model is available as a desktop application, allowing both instructors and students to benefit from user-friendly interfaces for predicting student academic achievement. As a result, it is recommended that both students and professors use this tool to better forecast outcomes.Keywords: artificial intelligence, ML, logistic regression, performance, prediction
Procedia PDF Downloads 90680 Infodemic Detection on Social Media with a Multi-Dimensional Deep Learning Framework
Authors: Raymond Xu, Cindy Jingru Wang
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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis
Procedia PDF Downloads 238679 Ethnobotanical Survey of Vegetable Plants Traditionally Used in Kalasin Thailand
Authors: Aree Thongpukdee, Chockpisit Thepsithar, Chuthalak Thammaso
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Use of plants grown in local area for edible has a long tradition in different culture. The indigenous knowledge such as usage of plants as vegetables by local people is risk to disappear when no records are done. In order to conserve and transfer this valuable heritage to the new generation, ethnobotanical study should be investigated and documented. The survey of vegetable plants traditionally used was carried out in the year 2012. Information was accumulated via questionnaires and oral interviewing from 100 people living in 36 villages of 9 districts in Amphoe Huai Mek, Kalasin, Thailand. Local plant names, utilized parts and preparation methods of the plants were recorded. Each mentioned plant species were collected and voucher specimens were prepared. A total of 55 vegetable plant species belonging to 34 families and 54 genera were identified. The plant habits were tree, shrub, herb, climber, and shrubby fern at 21.82%, 18.18%, 38.18%, 20.00% and 1.82% respectively. The most encountered vegetable plant families were Leguminosae (20%), Cucurbitaceae (7.27%), Apiaceae (5.45%), whereas families with 3.64% uses were Araceae, Bignoniaceae, Lamiaceae, Passifloraceae, Piperaceae and Solanaceae. The most common consumptions were fresh or brief boiled young shoot or young leaf as side dishes of ‘jaeo, laab, namprik, pon’ or curries. Most locally known vegetables included 45% of the studied plants which grow along road side, backyard garden, hedgerow, open forest and rice field.Keywords: vegetable plants, ethnobotanical survey, Kalasin, Thailand
Procedia PDF Downloads 307678 Information Management Approach in the Prediction of Acute Appendicitis
Authors: Ahmad Shahin, Walid Moudani, Ali Bekraki
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This research aims at presenting a predictive data mining model to handle an accurate diagnosis of acute appendicitis with patients for the purpose of maximizing the health service quality, minimizing morbidity/mortality, and reducing cost. However, acute appendicitis is the most common disease which requires timely accurate diagnosis and needs surgical intervention. Although the treatment of acute appendicitis is simple and straightforward, its diagnosis is still difficult because no single sign, symptom, laboratory or image examination accurately confirms the diagnosis of acute appendicitis in all cases. This contributes in increasing morbidity and negative appendectomy. In this study, the authors propose to generate an accurate model in prediction of patients with acute appendicitis which is based, firstly, on the segmentation technique associated to ABC algorithm to segment the patients; secondly, on applying fuzzy logic to process the massive volume of heterogeneous and noisy data (age, sex, fever, white blood cell, neutrophilia, CRP, urine, ultrasound, CT, appendectomy, etc.) in order to express knowledge and analyze the relationships among data in a comprehensive manner; and thirdly, on applying dynamic programming technique to reduce the number of data attributes. The proposed model is evaluated based on a set of benchmark techniques and even on a set of benchmark classification problems of osteoporosis, diabetes and heart obtained from the UCI data and other data sources.Keywords: healthcare management, acute appendicitis, data mining, classification, decision tree
Procedia PDF Downloads 343677 Climate Change: Affecting Basic Human Rights in Bangladesh
Authors: Shekh Shadi Rahaman
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In Bangladesh, basic human rights more specifically right to food and right to shelter are being adversely affected by the consequences of climate change. Over the last two decades, a considerable number of environmental studies revealed that basic human rights, more specifically, the right to food and right to a shelter are going to be seriously affected by climate change. Agriculture, forestry, and fisheries and livestock, which are most sensitive to climate change, are key sources interconnected with food security and the security of shelter. Consequences of climate change affecting these key sources, and with the change of time, climate change is turning into a gigantic challenge towards ensuring basic human rights in Bangladesh. This study was carried out by employing a general review of literature on climate change, focusing on effects of climate change on basic two major human rights in Bangladesh. Upon analysis of existing researches, it is found very few researches focused on correlating climate change and right to food and right to shelter. This study shows how the consequences of climate change affects food production and abode of people of Bangladesh. This study recommends that tree plantation, floating agricultural practice, co-operation with international organization, developing environment friendly institutions, increased use of renewable energy, proper management of wetlands and forests, shelter for climate induced migrated people, encouraging research and public awareness are key issues to be followed for combating climate change and protecting basic human right to food and shelter.Keywords: achievements, agriculture and forestry, fisheries and livestock, renewable energy
Procedia PDF Downloads 127676 Natural Regeneration Assessment of a Double Bunrt Mediterranean Coniferous Forest: A Pilot Study from West Peloponnisos, Greece
Authors: Dionisios Panagiotaras, Ioannis P. Kokkoris, Dionysios Koulougliotis, Dimitra Lekka, Alexandra Skalioti
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In the summer of 2021, Greece was affected by devastating forest fires in various regions of the country, resulting in human losses, destruction or degradation of the natural environment, infrastructure, livestock and cultivations. The present study concerns a pilot assessment of natural vegetation regeneration in the second, in terms of area, fire-affected region for 2021, at Ancient Olympia area, located in West Peloponnisos (Ilia Prefecture), Greece. A standardised field sampling protocol for assessing natural regeneration was implemented at selected sites where the forest fire had occurred previously (in 2007), and the vegetation (Pinus halepensis forest) had regenerated naturally. The results of the study indicate the loss of the established natural regeneration of Pinus halepensis forest, as well as of the tree-layer in total. Post-fire succession species are recorded to the shrub and the herb layer, with a varying cover. Present findings correspond to the results of field work and analysis one year after the fire, which will form the basis for further research and conclusions on taking action for restoration schemes in areas that have been affected by fire more than once within a 20-year period.Keywords: forest, pinus halepensis, ancient olympia, post fire vegetation
Procedia PDF Downloads 83675 Breast Cancer Survivability Prediction via Classifier Ensemble
Authors: Mohamed Al-Badrashiny, Abdelghani Bellaachia
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This paper presents a classifier ensemble approach for predicting the survivability of the breast cancer patients using the latest database version of the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. The system consists of two main components; features selection and classifier ensemble components. The features selection component divides the features in SEER database into four groups. After that it tries to find the most important features among the four groups that maximizes the weighted average F-score of a certain classification algorithm. The ensemble component uses three different classifiers, each of which models different set of features from SEER through the features selection module. On top of them, another classifier is used to give the final decision based on the output decisions and confidence scores from each of the underlying classifiers. Different classification algorithms have been examined; the best setup found is by using the decision tree, Bayesian network, and Na¨ıve Bayes algorithms for the underlying classifiers and Na¨ıve Bayes for the classifier ensemble step. The system outperforms all published systems to date when evaluated against the exact same data of SEER (period of 1973-2002). It gives 87.39% weighted average F-score compared to 85.82% and 81.34% of the other published systems. By increasing the data size to cover the whole database (period of 1973-2014), the overall weighted average F-score jumps to 92.4% on the held out unseen test set.Keywords: classifier ensemble, breast cancer survivability, data mining, SEER
Procedia PDF Downloads 318674 Studies on Phylogeny of Helicoverpa armigera Populations from North Western Himalaya Region with Help of Cytochromeoxidase I Sequence
Authors: R. M. Srivastava, Subbanna A.R.N.S, Md Abbas Ahmad, S. P.More, Shivashankar, B. Kalyanbabu
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The similar morphology associated with high genetic variability poses problems in phylogenetic studies of Helicoverpa armigera (Hubner). To identify genetic variation of North Western Himalayan population’s, partial (Mid to terminal region) cytochrome c oxidase subunit I (COX-1) gene was amplified and sequenced for three populations collected from Pantnagar, Almora, and Chinyalisaur. The alignment of sequences with other two populations, Nagpur representing central India population and Anhui, China representing complete COX-1 sequence revealed unanimity in middle region with eleven single nucleotide polymorphisms (SNPs) in Nagpur populations. However, the consensus is missing when approaching towards terminal region, which is associated with 15 each SNPs and pair base substitutions in Chinyalisaur populations. In minimum evolution tree, all the five populations were majorly separated into two clades, one comprising of only Nagpur population and the other with rest. Amongst, North Western populations, Chinyalisaur one is promising by farming a separate clade. The pairwise genetic distance ranges from 0.025 to 0.192 with the maximum between H. armigera populations of Nagpur and Chinyalisaur. This genetic isolation of populations can be attributed to a key role of topological barriers of weather and mountain ranges and temporal barriers due to cropping patterns.Keywords: cytochrome c oxidase subunit I, northwestern Himalayan population, Helicoverpa armigera (Noctuidae: Lepidoptera), phylogenetic relationship, genetic variation
Procedia PDF Downloads 304673 Evaluation of Particle Settling in Flow Chamber
Authors: Abdulrahman Alenezi, B. Stefan
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Abstract— The investigation of fluids containing particles or filaments includes a category of complex fluids and is vital in both theory and application. The forecast of particle behaviors plays a significant role in the existing technology as well as future technology. This paper focuses on the prediction of the particle behavior through the investigation of the particle disentrainment from a pipe on a horizontal air stream. This allows for examining the influence of the particle physical properties on its behavior when falling on horizontal air stream. This investigation was conducted on a device located at the University of Greenwich's Medway Campus. Two materials were selected to carry out this study: Salt and Glass Beads particles. The shape of the Slat particles is cubic where the shape of the Glass Beads is almost spherical. The outcome from the experimental work were presented in terms of distance travelled by the particles according to their diameters as After that, the particles sizes were measured using Laser Diffraction device and used to determine the drag coefficient and the settling velocity.Keywords: flow experiment, drag coefficient, Particle Settling, Flow Chamber
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