Search results for: IF rough relational database
1133 Journals' Productivity in the Literature on Malaria in Africa
Authors: Yahya Ibrahim Harande
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The purpose of this study was to identify the journals that published articles on malaria disease in Africa and to determine the core of productive journals from the identified journals. The data for the study were culled out from African Index Medicus (AIM) database. A total of 529 articles was gathered from 115 journal titles from 1979-2011. In order to obtain the core of productive journals, Bradford`s law was applied to the collected data. Five journal titles were identified and determined as core journals. The data used for the study was analyzed and that, the subject matter used, Malaria was in conformity with the Bradford`s law. On the aspect dispersion of the literature, English was found to be the dominant language of the journals. (80.9%) followed by French (16.5%). Followed by Portuguese (1.7%) and German (0.9%). Recommendation is hereby proposed for the medical libraries to acquire these five journals that constitute the core in malaria literature for the use of their clients. It could also help in streamlining their acquision and selection exercises. More researches in the subject area using Bibliometrics approaches are hereby recommended.Keywords: productive journals, malaria disease literature, Bradford`s law, core journals, African scholars
Procedia PDF Downloads 3371132 Corporate Social Responsibility Practices and Financial Performance: The Case of French Unlisted SMEs
Authors: Zineb Abidi, Marc-Arthur Diaye
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There exists a large empirical literature concerning the relationship between corporate social responsibility (CSR) and corporate financial performance. This literature, however, applies mainly to large corporations and/or listed firms. To the best of our knowledge, the question of whether meeting CSR requirements impacts the financial performance of small and medium-sized unlisted SMEs has not so far been analyzed. This paper aims to analyze, for the first time, the effect of CSR on the financial performance of SMEs. Using an original database including 5,257 French SMEs, we show that adopting CSR practices has a positive but weak effect on a firm’s financial performance. To develop this further, we analyzed CSR practices interactions assessing the best combination of CSR components that positively influence SME financial performance. Our results show that French SMEs benefit more from their pro-social behavior when they choose a combination of CSR components best adapted to their individual characteristics.Keywords: corporate social responsibility, financial performance, unlisted firms, SMEs
Procedia PDF Downloads 1621131 Geospatial Data Complexity in Electronic Airport Layout Plan
Authors: Shyam Parhi
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Airports GIS program collects Airports data, validate and verify it, and stores it in specific database. Airports GIS allows authorized users to submit changes to airport data. The verified data is used to develop several engineering applications. One of these applications is electronic Airport Layout Plan (eALP) whose primary aim is to move from paper to digital form of ALP. The first phase of development of eALP was completed recently and it was tested for a few pilot program airports across different regions. We conducted gap analysis and noticed that a lot of development work is needed to fine tune at least six mandatory sheets of eALP. It is important to note that significant amount of programming is needed to move from out-of-box ArcGIS to a much customized ArcGIS which will be discussed. The ArcGIS viewer capability to display essential features like runway or taxiway or the perpendicular distance between them will be discussed. An enterprise level workflow which incorporates coordination process among different lines of business will be highlighted.Keywords: geospatial data, geology, geographic information systems, aviation
Procedia PDF Downloads 4071130 Automatic Facial Skin Segmentation Using Possibilistic C-Means Algorithm for Evaluation of Facial Surgeries
Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammad Hossein Sedaaghi
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Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.Keywords: facial image, segmentation, PCM, FCM, skin error, facial surgery
Procedia PDF Downloads 5761129 Associated Factors of Hypercholesterolemia, Hyperuricemia and Double Burden of Hypercuricémia-Hypercholesterolemia in Gout Patients: Hospital Based Study
Authors: Pierre Mintom, Armel Assiene Agamou, Leslie Toukem, William Dakam, Christine Fernande Nyangono Biyegue
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Context: Hyperuricemia, the presence of high levels of uric acid in the blood, is a known precursor to the development of gout. Recent studies have suggested a strong association between hyperuricemia and disorders of lipoprotein metabolism, specifically hypercholesterolemia. Understanding the factors associated with these conditions in gout patients is essential for effective treatment and management. Research Aim: The objective of this study was to determine the prevalence of hyperuricemia, hypercholesterolemia, and the double burden of hyperuricemia-hypercholesterolemia in the gouty population. Additionally, the study aimed to identify the factors associated with these conditions. Methodology: The study utilized a database from a survey of 150 gouty patients recruited at the Laquintinie Hospital in Douala between August 2017 and February 2018. The database contained information on anthropometric parameters, biochemical markers, and the food and drugs consumed by the patients. Hyperuricemia and hypercholesterolemia were defined based on specific serum uric acid and total cholesterol thresholds, and the double burden was defined as the co-occurrence of hyperuricemia and hypercholesterolemia. Findings: The study found that the prevalence rates for hyperuricemia, hypercholesterolemia, and the double burden were 61.3%, 76%, and 50.7% respectively. Factors associated with these conditions included hypertriglyceridemia, atherogenicity index TC/HDL ratio, atherogenicity index LDL/HDL ratio, family history, and the consumption of specific foods and drinks. Theoretical Importance: The study highlights the strong association between hyperuricemia and dyslipidemia, providing important insights for guiding treatment strategies in gout patients. Additionally, it emphasizes the significance of nutritional education in managing these metabolic disorders, suggesting the need to address eating habits in gout patients. Data Collection and Analysis Procedures: Data was collected through surveys and medical records of gouty patients. Information on anthropometric parameters, biochemical markers, and dietary habits was recorded. Prevalence rates and associated factors were determined through statistical analysis, employing odds ratios to assess the risks. Question Addressed: The study aimed to address the prevalence rates and associated factors of hyperuricemia, hypercholesterolemia, and the double burden in gouty patients. It sought to understand the relationships between these conditions and determine their implications for treatment and nutritional education. Conclusion: Findings show that it’s exists an association between hyperuricemia and hypercholesterolemia in gout patients, thus creating a double burden. The findings underscore the importance of considering family history and eating habits in addressing the double burden of hyperuricemia-hypercholesterolemia. This study provides valuable insights for guiding treatment approaches and emphasizes the need for nutritional education in gout patients. This study specifically focussed on the sick population. A case–control study between gouty and non-gouty populations would be interesting to better compare and explain the results observed.Keywords: gout, hyperuricemia, hypercholesterolemia, double burden
Procedia PDF Downloads 471128 A t-SNE and UMAP Based Neural Network Image Classification Algorithm
Authors: Shelby Simpson, William Stanley, Namir Naba, Xiaodi Wang
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Both t-SNE and UMAP are brand new state of art tools to predominantly preserve the local structure that is to group neighboring data points together, which indeed provides a very informative visualization of heterogeneity in our data. In this research, we develop a t-SNE and UMAP base neural network image classification algorithm to embed the original dataset to a corresponding low dimensional dataset as a preprocessing step, then use this embedded database as input to our specially designed neural network classifier for image classification. We use the fashion MNIST data set, which is a labeled data set of images of clothing objects in our experiments. t-SNE and UMAP are used for dimensionality reduction of the data set and thus produce low dimensional embeddings. Furthermore, we use the embeddings from t-SNE and UMAP to feed into two neural networks. The accuracy of the models from the two neural networks is then compared to a dense neural network that does not use embedding as an input to show which model can classify the images of clothing objects more accurately.Keywords: t-SNE, UMAP, fashion MNIST, neural networks
Procedia PDF Downloads 1891127 An E-Assessment Website to Implement Hierarchical Aggregate Assessment
Authors: M. Lesage, G. Raîche, M. Riopel, F. Fortin, D. Sebkhi
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This paper describes a Web server implementation of the hierarchical aggregate assessment process in the field of education. This process describes itself as a field of teamwork assessment where teams can have multiple levels of hierarchy and supervision. This process is applied everywhere and is part of the management, education, assessment and computer science fields. The E-Assessment website named “Cluster” records in its database the students, the course material, the teams and the hierarchical relationships between the students. For the present research, the hierarchical relationships are team member, team leader and group administrator appointments. The group administrators have the responsibility to supervise team leaders. The experimentation of the application has been performed by high school students in geology courses and Canadian army cadets for navigation patrols in teams. This research extends the work of Nance that uses a hierarchical aggregation process similar as the one implemented in the “Cluster” application.Keywords: e-learning, e-assessment, teamwork assessment, hierarchical aggregate assessment
Procedia PDF Downloads 3631126 Effectiveness of a Pasifika Women’s Diabetes Wellness Program (PWDWP) – Co-design With, by and for MāOri and Pasifika Women Living in Queensland
Authors: Heena Akbar, Winnie Niumata, Danielle Gallegos
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Type 2 diabetes is a significant public health problem for Māori and Pasifika communities in Queensland, who are experiencing a higher burden of morbidity and mortality from the condition. Despite this higher burden, there are few initiatives that are culturally tailored to improve prevention and management. Modification of personal behaviors through women’s wellness programs aimed at early intervention has been shown to reduce the risk of developing complications in established type 2 diabetes and may reduce hospitalization rates from preventable complications related to this disease. The 24-week Pasifika Women’s Diabetes Wellness Program (PWDWP) was culturally co-designed and co-developed with Māori and Pasifika women with type 2 diabetes through a community-academia partnership in Queensland. Underpinned by Social Cognitive Theory and the Indigenous Pacific Health frameworks to include family culture & spirituality and integrating a collectivist and whānau (family) centered approach to self-care, the program takes into consideration the cultural shame associated with acknowledging the disease and tailors the interventions using talanoa (storytelling or conversation in a relational context) as the key strategy to come to a shared meaning for behavior change. The pilot trial is a 12-week intervention followed by a 12-week follow-up period conducted with 50 women with type 2 diabetes, 25 women who will receive the intervention and 25 women who will receive usual care. The pilot program provides in-person and virtual access to culturally supported prevention and self-management of Māori and Pasifika women with type 2 diabetes with the aim to improve healthy lifestyles and reduce late hospital presentations from diabetes-related complications for better diabetes-related outcomes. This study will test and evaluate the effectiveness of the PWDWP pilot trial in partnership with Māori & Pasifika community organizations and key stakeholders for improved glycated hemoglobin (HbA1c) levels associated with poor management of type 2 diabetes.Keywords: culturally co-designed intervention, Indigenous methodology, Māori and Pasifika communities, type 2 diabetes self-management
Procedia PDF Downloads 771125 Optimization of Vertical Axis Wind Turbine Based on Artificial Neural Network
Authors: Mohammed Affanuddin H. Siddique, Jayesh S. Shukla, Chetan B. Meshram
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The neural networks are one of the power tools of machine learning. After the invention of perceptron in early 1980's, the neural networks and its application have grown rapidly. Neural networks are a technique originally developed for pattern investigation. The structure of a neural network consists of neurons connected through synapse. Here, we have investigated the different algorithms and cost function reduction techniques for optimization of vertical axis wind turbine (VAWT) rotor blades. The aerodynamic force coefficients corresponding to the airfoils are stored in a database along with the airfoil coordinates. A forward propagation neural network is created with the input as aerodynamic coefficients and output as the airfoil co-ordinates. In the proposed algorithm, the hidden layer is incorporated into cost function having linear and non-linear error terms. In this article, it is observed that the ANNs (Artificial Neural Network) can be used for the VAWT’s optimization.Keywords: VAWT, ANN, optimization, inverse design
Procedia PDF Downloads 3121124 Cultivating Social-Ecological Resilience, Harvesting Biocultural Resistance in Southern Andes
Authors: Constanza Monterrubio-Solis, Jose Tomas Ibarra
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The fertile interdependence of social-ecological systems reveals itself in the interactions between native forests and seeds, home gardens, kitchens, foraging activities, local knowledge, and food practices, creating particular flavors and food meanings as part of cultural identities within territories. Resilience in local-food systems, from a relational perspective, can be understood as the balance between persistence and adaptability to change. Food growing, preparation, and consumption are constantly changing and adapting as expressions of agency of female and male indigenous peoples and peasants. This paper explores local food systems’ expressions of resilience in the la Araucanía region of Chile, namely: diversity, redundancy, buffer capacity, modularity, self-organization, governance, learning, equity, and decision-making. Applying ethnographic research methods (participant observation, focus groups, and semi-structured interviews), this work reflects on the experience developed through work with Mapuche women cultivating home gardens in the region since 2012; it looks to material and symbolic elements of resilience in the local indigenous food systems. Local food systems show indeed indicators of social-ecological resilience. The biocultural memory is expressed in affection to particular flavors and recipes, the cultural importance of seeds and reciprocity networks, as well as an accurate knowledge about the indicators of the seasons and weather, which have allowed local food systems to thrive with a strong cultural foundation. Furthermore, these elements turn into biocultural resistance in the face of the current institutional pressures for rural specialization, processes of cultural assimilation such as agroecosystems and diet homogenization, as well as structural threats towards the diversity and freedom of native seeds. Thus, the resilience-resistance dynamic shown by the social-ecological systems of the southern Andes is daily expressed in the local food systems and flavors and is key for diverse and culturally sound social-ecological health.Keywords: biocultural heritage, indigenous food systems, social-ecological resilience, southern Andes
Procedia PDF Downloads 1271123 Reading Literacy, Storytelling and Cognitive Learning: an Effective Connection in Sustainability Education
Authors: Rosa Tiziana Bruno
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The connection between education and sustainability has been posited to have benefit for realizing a social development compatible with environmental protection. However, an educational paradigm based on the passage of information or on the fear of a catastrophe might not favor the acquisition of eco-identity. To build a sustainable world, it is necessary to "become people" in harmony with other human beings, being aware of belonging to the same human community that is part of the natural world. This can only be achieved within an authentic educating community and the most effective tools for building educating communities are reading literacy and storytelling. This paper is the report of a research-action carried out in this direction, in agreement with the sociology department of the University of Salerno, which involved four hundred children and their teachers in a path based on the combination of reading literacy, storytelling, autobiographical writing and outdoor education. The goal of the research was to create an authentic educational community within the school, capable to encourage the acquisition of an eco-identity by the pupils, that is, personal and relational growth in the full realization of the Self, in harmony with the social and natural environment, with a view to an authentic education for sustainability. To ensure reasonable validity and reliability of findings, the inquiry started with participant observation and a process of triangulation has been used including: semi-structured interview, socio-semiotic analysis of the conversation and time budget. Basically, a multiple independent sources of data was used to answer the questions. Observing the phenomenon through multiple "windows" helped to comparing data through a variety of lenses. All teachers had the experience of implementing a socio-didactic strategy called "Fiabadiario" and they had the possibility to use it with approaches that fit their students. The data being collected come from the very students and teachers who are engaged with this strategy. The educational path tested during the research has produced sustainable relationships and conflict resolution within the school system and between school and families, creating an authentic and sustainable learning community.Keywords: educating community, education for sustainability, literature in education, social relations
Procedia PDF Downloads 1161122 Data Collection Based on the Questionnaire Survey In-Hospital Emergencies
Authors: Nouha Mhimdi, Wahiba Ben Abdessalem Karaa, Henda Ben Ghezala
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The methods identified in data collection are diverse: electronic media, focus group interviews and short-answer questionnaires [1]. The collection of poor-quality data resulting, for example, from poorly designed questionnaires, the absence of good translators or interpreters, and the incorrect recording of data allow conclusions to be drawn that are not supported by the data or to focus only on the average effect of the program or policy. There are several solutions to avoid or minimize the most frequent errors, including obtaining expert advice on the design or adaptation of data collection instruments; or use technologies allowing better "anonymity" in the responses [2]. In this context, we opted to collect good quality data by doing a sizeable questionnaire-based survey on hospital emergencies to improve emergency services and alleviate the problems encountered. At the level of this paper, we will present our study, and we will detail the steps followed to achieve the collection of relevant, consistent and practical data.Keywords: data collection, survey, questionnaire, database, data analysis, hospital emergencies
Procedia PDF Downloads 991121 Part of Geomatics Technology in the Capability to Implement an on Demand Transport in Oran Wilaya (the Northwestern of Algeria)
Authors: N. Brahmia
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The growing needs of displacements led advanced countries in this field install new specific transport systems, able to palliate any deficiencies, especially when regular public transport does not adequately meet the requests of users. In this context, on-demand transport systems (ODT) are very efficient; they rely on techniques based on the location of trip generators which should be assured effectively with the use of operators responsible of the advance reservation, planning and organization, and studying the different ODT criteria. As the advanced countries in the field of transport, some developing countries are involved in the adaptation of the new technologies to reduce the deficit in their communication system. This communication presents the study of an ODT implementation in the west of Algeria, by developing the Geomatics side of the study. This part requires the use of specific systems such as Geographic Information System (GIS), Road Database Management System (RDBMS)… so we developed the process through an application in an environment of mobility by using the computer tools dedicated to the management of the entities related to the transport field.Keywords: geomatics, GIS, ODT, transport systems
Procedia PDF Downloads 5931120 A Hybrid Model Tree and Logistic Regression Model for Prediction of Soil Shear Strength in Clay
Authors: Ehsan Mehryaar, Seyed Armin Motahari Tabari
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Without a doubt, soil shear strength is the most important property of the soil. The majority of fatal and catastrophic geological accidents are related to shear strength failure of the soil. Therefore, its prediction is a matter of high importance. However, acquiring the shear strength is usually a cumbersome task that might need complicated laboratory testing. Therefore, prediction of it based on common and easy to get soil properties can simplify the projects substantially. In this paper, A hybrid model based on the classification and regression tree algorithm and logistic regression is proposed where each leaf of the tree is an independent regression model. A database of 189 points for clay soil, including Moisture content, liquid limit, plastic limit, clay content, and shear strength, is collected. The performance of the developed model compared to the existing models and equations using root mean squared error and coefficient of correlation.Keywords: model tree, CART, logistic regression, soil shear strength
Procedia PDF Downloads 1831119 OPEN-EmoRec-II-A Multimodal Corpus of Human-Computer Interaction
Authors: Stefanie Rukavina, Sascha Gruss, Steffen Walter, Holger Hoffmann, Harald C. Traue
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OPEN-EmoRecII is an open multimodal corpus with experimentally induced emotions. In the first half of the experiment, emotions were induced with standardized picture material and in the second half during a human-computer interaction (HCI), realized with a wizard-of-oz design. The induced emotions are based on the dimensional theory of emotions (valence, arousal and dominance). These emotional sequences - recorded with multimodal data (mimic reactions, speech, audio and physiological reactions) during a naturalistic-like HCI-environment one can improve classification methods on a multimodal level. This database is the result of an HCI-experiment, for which 30 subjects in total agreed to a publication of their data including the video material for research purposes. The now available open corpus contains sensory signal of: video, audio, physiology (SCL, respiration, BVP, EMG Corrugator supercilii, EMG Zygomaticus Major) and mimic annotations.Keywords: open multimodal emotion corpus, annotated labels, intelligent interaction
Procedia PDF Downloads 4051118 Exploring Pisa Monuments Using Mobile Augmented Reality
Authors: Mihai Duguleana, Florin Girbacia, Cristian Postelnicu, Raffaello Brodi, Marcello Carrozzino
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Augmented Reality (AR) has taken a big leap with the introduction of mobile applications which co-locate bi-dimensional (e.g. photo, video, text) and tridimensional information with the location of the user enriching his/her experience. This study presents the advantages of using Mobile Augmented Reality (MAR) technologies in traveling applications, improving cultural heritage exploration. We propose a location-based AR application which combines co-location with the augmented visual information about Pisa monuments to establish a friendly navigation in this historic city. AR was used to render contextual visual information in the outdoor environment. The developed Android-based application offers two different options: it provides the ability to identify the monuments positioned close to the user’s position and it offers location information for getting near the key touristic objectives. We present the process of creating the monuments’ 3D map database and the navigation algorithm.Keywords: augmented reality, electronic compass, GPS, location-based service
Procedia PDF Downloads 2781117 A Model for Adaptive Online Quiz: QCitra
Authors: Rosilah Hassan, Karam Dhafer Mayoof, Norngainy Mohd Tawil, Shamshubaridah Ramlee
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Application of adaptive online quiz system and a design are performed in this paper. The purpose of adaptive quiz system is to establish different questions automatically for each student and measure their competence on a definite area of discipline. This model determines students competencies in cases like distant-learning which experience challenges frequently. Questions are specialized to allow clear deductions about student gains; they are able to identify student competencies more effectively. Also, negative effects of questions requiring higher knowledge than competency over student’s morale and self-confidence are dismissed. The advantage of the system in the quiz management requires less total time for measuring and is more flexible. Self sufficiency of the system in terms of repeating, planning and assessment of the measurement process allows itself to be used in the individual education sets. Adaptive quiz technique prevents students from distraction and motivation loss, which is led by the questions with quite lower hardness level than student’s competency.Keywords: e-learning, adaptive system, security, quiz database
Procedia PDF Downloads 4431116 Reliability Analysis for the Functioning of Complete and Low Capacity MLDB Systems in Piston Plants
Authors: Ramanpreet Kaur, Upasana Sharma
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The purpose of this paper is to address the challenges facing the water supply for the Machine Learning Database (MLDB) system at the piston foundry plant. In the MLDB system, one main unit, i.e., robotic, is connected by two sub-units. The functioning of the system depends on the robotic and water supply. Lack of water supply causes system failure. The system operates at full capacity with the help of two sub-units. If one sub-unit fails, the system runs at a low capacity. Reliability modeling is performed using semi-Markov processes and regenerative point techniques. Several system effects such as mean time to system failure, availability at full capacity, availability at reduced capacity, busy period for repair and expected number of visits have been achieved. Benefits have been analyzed. The graphical study is designed for a specific case using programming in C++ and MS Excel.Keywords: MLDB system, robotic, semi-Markov process, regenerative point technique
Procedia PDF Downloads 981115 Experimental Investigation on the Effect of Adding CuO Nanoparticles to R-600a Refrigerant on Heat Transfer Enhancement of a Horizontal Flattened Tube
Authors: M. A. Akhavan-Behabadi, M. Najafi, A. Abbasi
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An empirical investigation was performed in order to study the heat transfer characteristics of R600a flow boiling inside horizontal flattened tubes and the simultaneous effect of nanoparticles on boiling heat transfer in flattened channel. Round copper tubes of 8.7 mm I.D. were deformed into flattened shapes with different inside heights of 6.9, 5.5, and 3.4 mm as test areas. The effect of different parameters such as mass flux, vapor quality and inside height on heat transfer coefficient was studied. Flattening the tube caused significant enhancement in heat transfer performance so that the maximum augmentation ratio of 163% was obtained in flattened channel with lowest internal height. A new correlation was developed based on the present experimental data to predict the heat transfer coefficient in flattened tubes. This correlation estimated 90% of the entire database within ±20%.Keywords: nano particles, flattend tube, R600a, CuO
Procedia PDF Downloads 3161114 Research and Application of the Three-Dimensional Visualization Geological Modeling of Mine
Authors: Bin Wang, Yong Xu, Honggang Qu, Rongmei Liu, Zhenji Gao
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Today's mining industry is advancing gradually toward digital and visual direction. The three dimensional visualization geological modeling of mine is the digital characterization of mineral deposit, and is one of the key technology of digital mine. The three-dimensional geological modeling is a technology that combines the geological spatial information management, geological interpretation, geological spatial analysis and prediction, geostatistical analysis, entity content analysis and graphic visualization in three-dimensional environment with computer technology, and is used in geological analysis. In this paper, the three-dimensional geological modeling of an iron mine through the use of Surpac is constructed, and the weight difference of the estimation methods between distance power inverse ratio method and ordinary kriging is studied, and the ore body volume and reserves are simulated and calculated by using these two methods. Compared with the actual mine reserves, its result is relatively accurate, so it provided scientific bases for mine resource assessment, reserve calculation, mining design and so on.Keywords: three-dimensional geological modeling, geological database, geostatistics, block model
Procedia PDF Downloads 621113 Interpretation and Clustering Framework for Analyzing ECG Survey Data
Authors: Irum Matloob, Shoab Ahmad Khan, Fahim Arif
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As Indo-Pak has been the victim of heart diseases since many decades. Many surveys showed that percentage of cardiac patients is increasing in Pakistan day by day, and special attention is needed to pay on this issue. The framework is proposed for performing detailed analysis of ECG survey data which is conducted for measuring prevalence of heart diseases statistics in Pakistan. The ECG survey data is evaluated or filtered by using automated Minnesota codes and only those ECGs are used for further analysis which is fulfilling the standardized conditions mentioned in the Minnesota codes. Then feature selection is performed by applying proposed algorithm based on discernibility matrix, for selecting relevant features from the database. Clustering is performed for exposing natural clusters from the ECG survey data by applying spectral clustering algorithm using fuzzy c means algorithm. The hidden patterns and interesting relationships which have been exposed after this analysis are useful for further detailed analysis and for many other multiple purposes.Keywords: arrhythmias, centroids, ECG, clustering, discernibility matrix
Procedia PDF Downloads 4611112 The Design of Information Technology System for Traceability of Thailand’s Tubtimjun Roseapple
Authors: Pimploi Tirastittam, Phutthiwat Waiyawuththanapoom, Sawanath Treesathon
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As there are several countries which import agriculture product from Thailand, those countries demand Thailand to establish the traceability system. The traceability system is the tool to reduce the risk in the supply chain in a very effective way as it will help the stakeholder in the supply chain to identify the defect point which will reduce the cost of operation in the supply chain. This research is aimed to design the traceability system for Tubtimjun roseapple for exporting to China, and it is the qualitative research. The data was collected from the expert in the tuntimjun roseapple and fruit exporting industry, and the data was used to design the traceability system. The design of the tubtimjun roseapple traceability system was followed the theory of supply chain which starts from the upstream of the supply chain to the downstream of the supply chain to support the process and condition of the exporting which included the database designing, system architecture, user interface design and information technology of the traceability system.Keywords: design information, technology system, traceability, tubtimjun roseapple
Procedia PDF Downloads 1631111 Predicting Durability of Self Compacting Concrete Using Artificial Neural Network
Authors: R. Boudjelthia
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The aim of this study is to determine the influence of mix composition of concrete as the content of water and cement, water–binder ratio, and the replacement of fly ash on the durability of self compacting concrete (SCC) by using artificial neural networks (ANNs). To achieve this, an ANNs model is developed to predict the durability of self compacting concrete which is expressed in terms of chloride ions permeability in accordance with ASTM C1202-97 or AASHTO T277. Database gathered from the literature for the training and testing the model. A sensitivity analysis was also conducted using the trained and tested ANN model to investigate the effect of fly ash on the durability of SCC. The results indicate that the developed model is reliable and accurate. the durability of SCC expressed in terms of total charge passed over a 6-h period can be significantly improved by using at least 25% fly ash as replacement of cement. This study show that artificial neural network have strong potentialas a feasible tool for predicting accurately the durability of SCC containing fly ash.Keywords: artificial neural networks, durability, chloride ions permeability, self compacting concrete
Procedia PDF Downloads 3681110 Gut Metabolite Profiling of the Ethnic Groups from Assam, India
Authors: Madhusmita Dehingia, Supriyo Sen, Bhuwan Bhaskar, Tulsi Joishy, Mojibur R. Khan
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Human gut microbes and their metabolites are important for maintaining homeostasis in the gut and are responsible for many metabolic and immune mediated diseases. In the present study, we determined the profiles of the gut metabolites of five different ethnic groups (Bodo, Tai-Phake, Karbi, Tea tribe and Tai-Aiton) of Assam. Fecal metabolite profiling of the 39 individuals belonging to the ethnic groups was carried out using Gas chromatography – Mass spectrometry (GC-MS), and comparison was performed among the tribes for common and unique metabolites produced within their gut. Partial Least Squares Discriminant Analysis (PLS-DA) of the metabolites suggested that the individuals grouped according to their ethnicity. Among the 66 abundant metabolites, 12 metabolites were found to be common among the five ethnic groups. Additionally, ethnicity wise some unique metabolites were also detected. For example, the tea tribe of Assam contained the tea components, Aniline and Benzoate more in their gut in comparison to others. Metabolites of microbial origin were also correlated with the already published metagenomic data of the same ethnic group and functional analysis were carried out based on human metabolome database.Keywords: ethnicity, gut microbiota, GC-MS, metabolites
Procedia PDF Downloads 4141109 Micro-Hydrokinetic for Remote Rural Electrification
Authors: S. P. Koko, K. Kusakana, H. J. Vermaak
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Standalone micro-hydrokinetic river (MHR) system is one of the promising technologies to be used for remote rural electrification. It simply requires the flow of water instead of elevation or head, leading to expensive civil works. This paper demonstrates an economic benefit offered by a standalone MHR system when compared to the commonly used standalone systems such as solar, wind and diesel generator (DG) at the selected study site in Kwazulu Natal. Wind speed and solar radiation data of the selected rural site have been taken from national aeronautics and space administration (NASA) surface meteorology database. The hybrid optimization model for electric renewable (HOMER) software was used to determine the most feasible solution when using MHR, solar, wind or DG system to supply 5 rural houses. MHR system proved to be the best cost-effective option to consider at the study site due to its low cost of energy (COE) and low net present cost (NPC).Keywords: economic analysis, micro-hydrokinetic, rural-electrification, cost of energy (COE), net present cost (NPC)
Procedia PDF Downloads 4211108 An Improved Face Recognition Algorithm Using Histogram-Based Features in Spatial and Frequency Domains
Authors: Qiu Chen, Koji Kotani, Feifei Lee, Tadahiro Ohmi
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In this paper, we propose an improved face recognition algorithm using histogram-based features in spatial and frequency domains. For adding spatial information of the face to improve recognition performance, a region-division (RD) method is utilized. The facial area is firstly divided into several regions, then feature vectors of each facial part are generated by Binary Vector Quantization (BVQ) histogram using DCT coefficients in low frequency domains, as well as Local Binary Pattern (LBP) histogram in spatial domain. Recognition results with different regions are first obtained separately and then fused by weighted averaging. Publicly available ORL database is used for the evaluation of our proposed algorithm, which is consisted of 40 subjects with 10 images per subject containing variations in lighting, posing, and expressions. It is demonstrated that face recognition using RD method can achieve much higher recognition rate.Keywords: binary vector quantization (BVQ), DCT coefficients, face recognition, local binary patterns (LBP)
Procedia PDF Downloads 3421107 Scheduling of Repetitive Activities for Height-Rise Buildings: Optimisation by Genetic Algorithms
Authors: Mohammed Aljoma
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In this paper, a developed prototype for the scheduling of repetitive activities in height-rise buildings was presented. The activities that describe the behavior of the most of activities in multi-storey buildings are scheduled using the developed approach. The prototype combines three methods to attain the optimized planning. The methods include Critical Path Method (CPM), Gantt and Line of Balance (LOB). The developed prototype; POTER is used to schedule repetitive and non-repetitive activities with respect to all constraints that can be automatically generated using a generic database. The prototype uses the method of genetic algorithms for optimizing the planning process. As a result, this approach enables contracting organizations to evaluate various planning solutions that are calculated, tested and classified by POTER to attain an optimal time-cost equilibrium according to their own criteria of time or coast.Keywords: planning scheduling, genetic algorithms, repetitive activity, construction management, planning, scheduling, risk management, project duration
Procedia PDF Downloads 3001106 Design and Implementation of Partial Denoising Boundary Image Matching Using Indexing Techniques
Authors: Bum-Soo Kim, Jin-Uk Kim
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In this paper, we design and implement a partial denoising boundary image matching system using indexing techniques. Converting boundary images to time-series makes it feasible to perform fast search using indexes even on a very large image database. Thus, using this converting method we develop a client-server system based on the previous partial denoising research in the GUI (graphical user interface) environment. The client first converts a query image given by a user to a time-series and sends denoising parameters and the tolerance with this time-series to the server. The server identifies similar images from the index by evaluating a range query, which is constructed using inputs given from the client, and sends the resulting images to the client. Experimental results show that our system provides much intuitive and accurate matching result.Keywords: boundary image matching, indexing, partial denoising, time-series matching
Procedia PDF Downloads 1301105 A Neural Network Classifier for Identifying Duplicate Image Entries in Real-Estate Databases
Authors: Sergey Ermolin, Olga Ermolin
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A Deep Convolution Neural Network with Triplet Loss is used to identify duplicate images in real-estate advertisements in the presence of image artifacts such as watermarking, cropping, hue/brightness adjustment, and others. The effects of batch normalization, spatial dropout, and various convergence methodologies on the resulting detection accuracy are discussed. For comparative Return-on-Investment study (per industry request), end-2-end performance is benchmarked on both Nvidia Titan GPUs and Intel’s Xeon CPUs. A new real-estate dataset from San Francisco Bay Area is used for this work. Sufficient duplicate detection accuracy is achieved to supplement other database-grounded methods of duplicate removal. The implemented method is used in a Proof-of-Concept project in the real-estate industry.Keywords: visual recognition, convolutional neural networks, triplet loss, spatial batch normalization with dropout, duplicate removal, advertisement technologies, performance benchmarking
Procedia PDF Downloads 3271104 Analysis of ECGs Survey Data by Applying Clustering Algorithm
Authors: Irum Matloob, Shoab Ahmad Khan, Fahim Arif
Abstract:
As Indo-pak has been the victim of heart diseases since many decades. Many surveys showed that percentage of cardiac patients is increasing in Pakistan day by day, and special attention is needed to pay on this issue. The framework is proposed for performing detailed analysis of ECG survey data which is conducted for measuring the prevalence of heart diseases statistics in Pakistan. The ECG survey data is evaluated or filtered by using automated Minnesota codes and only those ECGs are used for further analysis which is fulfilling the standardized conditions mentioned in the Minnesota codes. Then feature selection is performed by applying proposed algorithm based on discernibility matrix, for selecting relevant features from the database. Clustering is performed for exposing natural clusters from the ECG survey data by applying spectral clustering algorithm using fuzzy c means algorithm. The hidden patterns and interesting relationships which have been exposed after this analysis are useful for further detailed analysis and for many other multiple purposes.Keywords: arrhythmias, centroids, ECG, clustering, discernibility matrix
Procedia PDF Downloads 342