Search results for: database spatio-temporal
827 Content-Based Image Retrieval Using HSV Color Space Features
Authors: Hamed Qazanfari, Hamid Hassanpour, Kazem Qazanfari
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In this paper, a method is provided for content-based image retrieval. Content-based image retrieval system searches query an image based on its visual content in an image database to retrieve similar images. In this paper, with the aim of simulating the human visual system sensitivity to image's edges and color features, the concept of color difference histogram (CDH) is used. CDH includes the perceptually color difference between two neighboring pixels with regard to colors and edge orientations. Since the HSV color space is close to the human visual system, the CDH is calculated in this color space. In addition, to improve the color features, the color histogram in HSV color space is also used as a feature. Among the extracted features, efficient features are selected using entropy and correlation criteria. The final features extract the content of images most efficiently. The proposed method has been evaluated on three standard databases Corel 5k, Corel 10k and UKBench. Experimental results show that the accuracy of the proposed image retrieval method is significantly improved compared to the recently developed methods.Keywords: content-based image retrieval, color difference histogram, efficient features selection, entropy, correlation
Procedia PDF Downloads 238826 Network Based Molecular Profiling of Intracranial Ependymoma over Spinal Ependymoma
Authors: Hyeon Su Kim, Sungjin Park, Hae Ryung Chang, Hae Rim Jung, Young Zoo Ahn, Yon Hui Kim, Seungyoon Nam
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Ependymoma, one of the most common parenchymal spinal cord tumor, represents 3-6% of all CNS tumor. Especially intracranial ependymomas, which are more frequent in childhood, have a more poor prognosis and more malignant than spinal ependymomas. Although there are growing needs to understand pathogenesis, detailed molecular understanding of pathogenesis remains to be explored. A cancer cell is composed of complex signaling pathway networks, and identifying interaction between genes and/or proteins are crucial for understanding these pathways. Therefore, we explored each ependymoma in terms of differential expressed genes and signaling networks. We used Microsoft Excel™ to manipulate microarray data gathered from NCBI’s GEO Database. To analyze and visualize signaling network, we used web-based PATHOME algorithm and Cytoscape. We show HOX family and NEFL are down-regulated but SCL family is up-regulated in cerebrum and posterior fossa cancers over a spinal cancer, and JAK/STAT signaling pathway and Chemokine signaling pathway are significantly different in the both intracranial ependymoma comparing to spinal ependymoma. We are considering there may be an age-dependent mechanism under different histological pathogenesis. We annotated mutation data of each gene subsequently in order to find potential target genes.Keywords: systems biology, ependymoma, deg, network analysis
Procedia PDF Downloads 292825 Enzymatic Activities of Two Iranian Wheat Cultivars Infected with Fusarium Culmorum
Authors: Parastoo Motallebi, Vahid Niknam, Hassan Ebrahimzadeh, Majid Hashemi
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Wheat, the most strategically important worldwide crop, is widely grown in various countries. Based on international wheat production statistics (FAOSTAT database), the total production of wheat in 2012 was 13.8 in Iran. Fusarium culmorum is one of the principal causative agents of Fusarium crown rot (FCR), an overwhelming disease of wheat and barley which is in the early stages causing yield losses, stand reductions and rotting of root and lower stem tissues. In this study inoculation of two wheat seedlings of the susceptible cultivar Falat and the partially field-resistant cultivar Pishtaz were carried out in greenhouse conditions and root samples were taken for 6 days. The activity of peroxidase (POX) and polyphenoloxidase (PPO) enzymes were analyzed to identify possible relations between resistance and enzymatic activities. Although the POX and PPO activities in both geno types increased, this significant increase was more dominant in Pishtaz. The results showed an earlier elevation in the activity of these defense related enzymes in semi-resistant cv. Pishtaz after inoculation, suggested that the activities of POX and PPO in wheat geno types play an important role in the induction of resistance to this disease.Keywords: Defense responses, Fusarium culmorum, Wheat
Procedia PDF Downloads 529824 Integration of Artificial Neural Network with Geoinformatics Technology to Predict Land Surface Temperature within Sun City Jodhpur, Rajasthan, India
Authors: Avinash Kumar Ranjan, Akash Anand
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The Land Surface Temperature (LST) is an essential factor accompanying to rise urban heat and climate warming within a city in micro level. It is also playing crucial role in global change study as well as radiation budgets measuring in heat balance studies. The information of LST is very substantial to recognize the urban climatology, ecological changes, anthropological and environmental interactions etc. The Chief motivation of present study focus on time series of ANN model that taken a sequence of LST values of 2000, 2008 and 2016, realize the pattern of variation within the data set and predict the LST values for 2024 and 2032. The novelty of this study centers on evaluation of LST using series of multi-temporal MODIS (MOD 11A2) satellite data by Maximum Value Composite (MVC) techniques. The results derived from this study endorse the proficiency of Geoinformatics Technology with integration of ANN to gain knowledge, understanding and building of precise forecast from the complex physical world database. This study will also focus on influence of Land Use/ Land Cover (LU/LC) variation on Land Surface Temperature.Keywords: LST, geoinformatics technology, ANN, MODIS satellite imagery, MVC
Procedia PDF Downloads 231823 Description and Evaluation of the Epidemiological Surveillance System for Meningitis in the Province of Taza Between 2016 and 2020
Authors: Bennasser Samira
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Meningitis, especially the meningococcal one, is a serious problem of public health. A system of vigilanceand surveillance is in place to allow effective actions to be taken on actual or potential health problems caused by all forms of meningitis. Objectives: 1. Describe the epidemiological surveillance system for meningitis in the province of Taza. 2. Evaluate the quality and responsiveness of the epidemiological surveillance system for meningitis in the province of Taza. 3. Propose measures to improve this system at the provincial level. Methods: This was a descriptive study with a purely quantitative approach by evaluating the quality and responsiveness of the system during 5 years between January 2016 and December 2020. We usedfor that the investigation files of meningitis cases and the provincial database of meningitis. We calculated some quality indicators of surveillance system already defined by the National Program for the Prevention and Control of Meningitis. Results: The notification is passive, the completeness of the data is quite good (94%), and the timeliness don’t exceed 71%. The quality of the data is acceptable (91% agreement). The systematic and rapid performance of lumbar punctures increases the diagnostic capabilities of the system. The local response actions are effected in 100%. Conclusion: The improvement of this surveillance system depends on strengthening the staff skills in diagnostic, reviewing surveillance tools, and encouraging judicious use of the data.Keywords: evaluation, meningitis, system, taza, morocco
Procedia PDF Downloads 151822 Detectability Analysis of Typical Aerial Targets from Space-Based Platforms
Authors: Yin Zhang, Kai Qiao, Xiyang Zhi, Jinnan Gong, Jianming Hu
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In order to achieve effective detection of aerial targets over long distances from space-based platforms, the mechanism of interaction between the radiation characteristics of the aerial targets and the complex scene environment including the sunlight conditions, underlying surfaces and the atmosphere are analyzed. A large simulated database of space-based radiance images is constructed considering several typical aerial targets, target working modes (flight velocity and altitude), illumination and observation angles, background types (cloud, ocean, and urban areas) and sensor spectrums ranging from visible to thermal infrared. The target detectability is characterized by the signal-to-clutter ratio (SCR) extracted from the images. The influence laws of the target detectability are discussed under different detection bands and instantaneous fields of view (IFOV). Furthermore, the optimal center wavelengths and widths of the detection bands are suggested, and the minimum IFOV requirements are proposed. The research can provide theoretical support and scientific guidance for the design of space-based detection systems and on-board information processing algorithms.Keywords: space-based detection, aerial targets, detectability analysis, scene environment
Procedia PDF Downloads 139821 Educational Data Mining: The Case of the Department of Mathematics and Computing in the Period 2009-2018
Authors: Mário Ernesto Sitoe, Orlando Zacarias
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University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.Keywords: evasion and retention, cross-validation, bagging, stacking
Procedia PDF Downloads 72820 Comparison of Real-Time PCR and FTIR with Chemometrics Technique in Analysing Halal Supplement Capsules
Authors: Mohd Sukri Hassan, Ahlam Inayatullah Badrul Munir, M. Husaini A. Rahman
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Halal authentication and verification in supplement capsules are highly required as the gelatine available in the market can be from halal or non-halal sources. It is an obligation for Muslim to consume and use the halal consumer goods. At present, real-time polymerase chain reaction (RT-PCR) is the most common technique being used for the detection of porcine and bovine DNA in gelatine due to high sensitivity of the technique and higher stability of DNA compared to protein. In this study, twenty samples of supplements capsules from different products with different Halal logos were analyzed for porcine and bovine DNA using RT-PCR. Standard bovine and porcine gelatine from eurofins at a range of concentration from 10-1 to 10-5 ng/µl were used to determine the linearity range, limit of detection and specificity on RT-PCR (SYBR Green method). RT-PCR detected porcine (two samples), bovine (four samples) and mixture of porcine and bovine (six samples). The samples were also tested using FT-IR technique where normalized peak of IR spectra were pre-processed using Savitsky Golay method before Principal Components Analysis (PCA) was performed on the database. Scores plot of PCA shows three clusters of samples; bovine, porcine and mixture (bovine and porcine). The RT-PCR and FT-IR with chemometrics technique were found to give same results for porcine gelatine samples which can be used for Halal authentication.Keywords: halal, real-time PCR, gelatine, chemometrics
Procedia PDF Downloads 228819 Interpretation of Sweep Frequency Response Analysis (SFRA) Traces for the Earth Fault Damage Practically Simulated on the Power Transformer Specially Developed for Performing Sweep Frequency Response Analysis for Various Transformers
Authors: Akshay A. Pandya, B. R. Parekh
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This paper presents how earth fault damage in the transformer can be detected by Sweep Frequency Response Analysis (SFRA). The test methods used by the authors for presenting the results are described. The power transformer of rating 10 KVA, 11000 V/440 V, 3-phase, 50 Hz, Dyn11 has been specially developed in-house for carrying out SFRA testing by practically simulated various transformer damages on it. Earth fault has been practically simulated on HV “U” phase winding and LV “W” phase winding separately. The result of these simulated faults are presented and discussed. The motivation of this presented work is to extend the guideline approach; there are ideas to organize database containing collected measurement results. Since the SFRA interpretation is based on experience, such databases are thought to be of great importance when interpreting SFRA response. The evaluation of the SFRA responses against guidelines and experience have to be performed and conclusions regarding usefulness of each simulation has been drawn and at last overall conclusion has also been drawn.Keywords: earth fault damage, power transformer, practical simulation, SFRA traces, transformer damages
Procedia PDF Downloads 276818 The Distribution of HLA-C* 14:02 Allele in Thai Population to See Risk Factors for Severe COVID-19
Authors: Naso Isaiah Thanavisuth, Patompong Satapornpong
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Introduction: Covid-19 has been a global pandemic for some time now, causing severe symptoms to patients that received the virus. However, there has been no report on this gene in the Thai population. Objective: Our aim in this study is to explore and compare the frequency of HLA-C allele that is associated with severe COVID-19 symptoms in Thais and other populations. Method: 200 general Thai population were enrolled in this study. The genotyping of HLA -C alleles were determined by the polymerase chain reaction with sequence-specific oligonucleotide probes (PCR-SSOP) and Luminex®IS 100 system (Luminex Corporation, Austin, Texas, USA). Results: We found that the frequency of alleles HLA-C* 01:02 (16.00%), HLA-C* 08:01(10.50%), HLA-C* 03:04 (10.25%),HLA-C* 07:02 (10.00%), HLA-C* 03:02 (9.25%), HLA-C* 07:01 (6.75%), HLA-C* 04:01 (5.00%), HLA-C* 06:02 (4.00%), HLA-C* 04:03 (4.00%), and HLA-C* 07:04 (3.75%) were more common in the Thai population. HLA-C* 01:02 (16.00%) allele was the highest frequency in the North, Center, and North East groups in Thailand, but there was the South region that was not significantly different when compared with the other groups of the region. Additionally, HLA-C∗14:02 allele was similarly distributed in Thais (3.00%), African Americans (1.98%), Caucasians (2.08%), Hispanics (1.71%), North American Natives (1.34%) and Asians (5.01%) by p-value = 0.6506, 0.6506, 0.6506, 0.6135 and 0.7182, respectively. Conclusion: Genetic variation database is important to identify HLA can be a risk factor for severe COVID-19 in many populations. In this study, we will support the research of the HLA markers for screening severe COVID-19 in many populations.Keywords: HLA-C * 14:02, COVID-19, allele frequency, Thailand
Procedia PDF Downloads 99817 The Theory of Domination at the Bane of Conflict Resolution and Peace Building Processes in Cameroon
Authors: Nkatow Mafany Christian
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According to UNHCR’s annual Database, humanitarian crises have globally been on the increase since the beginning of the 21st Century, especially in the Middle East and in Sub-Saharan Africa. Cameroon is one of the countries that has suffered tremendously from humanitarian challenges in recent years, especially with crises in the Far North, the East and its Two English-speaking Regions. These have been a result of failed mechanisms in conflict resolution peacebuilding by the government. The paper draws from this basic premise to argue that the failure to reach a consensus in order to curb internal conflicts has largely been due to the government’s attachment to the domineering attitude which emphasizes an imposition of peace terms by a superordinate (government) agency on the subordinate (aggrieved) entities. This has stalled peace efforts that have so far been engaged to address the dreaded armed conflicts in the North and South West Regions, leading to the persistence of the armed conflict. The paper exploits written, oral and online sources to sustain its argument. It suggests that an eclectic approach to resolving conflicts, which emphasizes open and frank dialogue as well as a review of the root causes, can go a long way not only to build trust but also to address the Anglophone-Cameroonian problems in Cameroon.Keywords: conflict, conflict resolution, peace building, humanitarian crisis
Procedia PDF Downloads 58816 Applying Neural Networks for Solving Record Linkage Problem via Fuzzy Description Logics
Authors: Mikheil Kalmakhelidze
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Record linkage (RL) problem has become more and more important in recent years due to the growing interest towards big data analysis. The problem can be formulated in a very simple way: Given two entries a and b of a database, decide whether they represent the same object or not. There are two classical deterministic and probabilistic ways of solving the RL problem. Using simple Bayes classifier in many cases produces useful results but sometimes they show to be poor. In recent years several successful approaches have been made towards solving specific RL problems by neural network algorithms including single layer perception, multilayer back propagation network etc. In our work, we model the RL problem for specific dataset of student applications in fuzzy description logic (FDL) where linkage of specific pair (a,b) depends on the truth value of corresponding formula A(a,b) in a canonical FDL model. As a main result, we build neural network for deciding truth value of FDL formulas in a canonical model and thus link RL problem to machine learning. We apply the approach to dataset with 10000 entries and also compare to classical RL solving approaches. The results show to be more accurate than standard probabilistic approach.Keywords: description logic, fuzzy logic, neural networks, record linkage
Procedia PDF Downloads 267815 Attention Based Fully Convolutional Neural Network for Simultaneous Detection and Segmentation of Optic Disc in Retinal Fundus Images
Authors: Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, Goutam Kumar Ghorai, Gautam Sarkar, Ashis K. Dhara
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Accurate segmentation of the optic disc is very important for computer-aided diagnosis of several ocular diseases such as glaucoma, diabetic retinopathy, and hypertensive retinopathy. The paper presents an accurate and fast optic disc detection and segmentation method using an attention based fully convolutional network. The network is trained from scratch using the fundus images of extended MESSIDOR database and the trained model is used for segmentation of optic disc. The false positives are removed based on morphological operation and shape features. The result is evaluated using three-fold cross-validation on six public fundus image databases such as DIARETDB0, DIARETDB1, DRIVE, AV-INSPIRE, CHASE DB1 and MESSIDOR. The attention based fully convolutional network is robust and effective for detection and segmentation of optic disc in the images affected by diabetic retinopathy and it outperforms existing techniques.Keywords: attention-based fully convolutional network, optic disc detection and segmentation, retinal fundus image, screening of ocular diseases
Procedia PDF Downloads 132814 Auditory Rehabilitation via an VR Serious Game for Children with Cochlear Implants: Bio-Behavioral Outcomes
Authors: Areti Okalidou, Paul D. Hatzigiannakoglou, Aikaterini Vatou, George Kyriafinis
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Young children are nowadays adept at using technology. Hence, computer-based auditory training programs (CBATPs) have become increasingly popular in aural rehabilitation for children with hearing loss and/or with cochlear implants (CI). Yet, their clinical utility for prognostic, diagnostic, and monitoring purposes has not been explored. The purposes of the study were: a) to develop an updated version of the auditory rehabilitation tool for Greek-speaking children with cochlear implants, b) to develop a database for behavioral responses, and c) to compare accuracy rates and reaction times in children differing in hearing status and other medical and demographic characteristics, in order to assess the tool’s clinical utility in prognosis, diagnosis, and progress monitoring. The updated version of the auditory rehabilitation tool was developed on a tablet, retaining the User-Centered Design approach and the elements of the Virtual Reality (VR) serious game. The visual stimuli were farm animals acting in simple game scenarios designed to trigger children’s responses to animal sounds, names, and relevant sentences. Based on an extended version of Erber’s auditory development model, the VR game consisted of six stages, i.e., sound detection, sound discrimination, word discrimination, identification, comprehension of words in a carrier phrase, and comprehension of sentences. A familiarization stage (learning) was set prior to the game. Children’s tactile responses were recorded as correct, false, or impulsive, following a child-dependent set up of a valid delay time after stimulus offset for valid responses. Reaction times were also recorded, and the database was in Εxcel format. The tablet version of the auditory rehabilitation tool was piloted in 22 preschool children with Νormal Ηearing (ΝΗ), which led to improvements. The study took place in clinical settings or at children’s homes. Fifteen children with CI, aged 5;7-12;3 years with post-implantation 0;11-5;1 years used the auditory rehabilitation tool. Eight children with CI were monolingual, two were bilingual and five had additional disabilities. The control groups consisted of 13 children with ΝΗ, aged 2;6-9;11 years. A comparison of both accuracy rates, as percent correct, and reaction times (in sec) was made at each stage, across hearing status, age, and also, within the CI group, based on presence of additional disability and bilingualism. Both monolingual Greek-speaking children with CI with no additional disabilities and hearing peers showed high accuracy rates at all stages, with performances falling above the 3rd quartile. However, children with normal hearing scored higher than the children with CI, especially in the detection and word discrimination tasks. The reaction time differences between the two groups decreased in language-based tasks. Results for children with CI with additional disability or bilingualism varied. Finally, older children scored higher than younger ones in both groups (CI, NH), but larger differences occurred in children with CI. The interactions between familiarization of the software, age, hearing status and demographic characteristics are discussed. Overall, the VR game is a promising tool for tracking the development of auditory skills, as it provides multi-level longitudinal empirical data. Acknowledgment: This work is part of a project that has received funding from the Research Committee of the University of Macedonia under the Basic Research 2020-21 funding programme.Keywords: VR serious games, auditory rehabilitation, auditory training, children with cochlear implants
Procedia PDF Downloads 77813 Interval Type-2 Fuzzy Vibration Control of an ERF Embedded Smart Structure
Authors: Chih-Jer Lin, Chun-Ying Lee, Ying Liu, Chiang-Ho Cheng
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The main objective of this article is to present the semi-active vibration control using an electro-rheological fluid embedded sandwich structure for a cantilever beam. ER fluid is a smart material, which cause the suspended particles polarize and connect each other to form chain. The stiffness and damping coefficients of the ER fluid can be changed in 10 micro seconds; therefore, ERF is suitable to become the material embedded in the tunable vibration absorber to become a smart absorber. For the ERF smart material embedded structure, the fuzzy control law depends on the experimental expert database and the proposed self-tuning strategy. The electric field is controlled by a CRIO embedded system to implement the real application. This study investigates the different performances using the Type-1 fuzzy and interval Type-2 fuzzy controllers. The Interval type-2 fuzzy control is used to improve the modeling uncertainties for this ERF embedded shock absorber. The self-tuning vibration controllers using Type-1 and Interval Type-2 fuzzy law are implemented to the shock absorber system. Based on the resulting performance, Internal Type-2 fuzzy is better than the traditional Type-1 fuzzy control for this vibration control system.Keywords: electro-rheological fluid, semi-active vibration control, shock absorber, type 2 fuzzy control
Procedia PDF Downloads 439812 Advancement of Computer Science Research in Nigeria: A Bibliometric Analysis of the Past Three Decades
Authors: Temidayo O. Omotehinwa, David O. Oyewola, Friday J. Agbo
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This study aims to gather a proper perspective of the development landscape of Computer Science research in Nigeria. Therefore, a bibliometric analysis of 4,333 bibliographic records of Computer Science research in Nigeria in the last 31 years (1991-2021) was carried out. The bibliographic data were extracted from the Scopus database and analyzed using VOSviewer and the bibliometrix R package through the biblioshiny web interface. The findings of this study revealed that Computer Science research in Nigeria has a growth rate of 24.19%. The most developed and well-studied research areas in the Computer Science field in Nigeria are machine learning, data mining, and deep learning. The social structure analysis result revealed that there is a need for improved international collaborations. Sparsely established collaborations are largely influenced by geographic proximity. The funding analysis result showed that Computer Science research in Nigeria is under-funded. The findings of this study will be useful for researchers conducting Computer Science related research. Experts can gain insights into how to develop a strategic framework that will advance the field in a more impactful manner. Government agencies and policymakers can also utilize the outcome of this research to develop strategies for improved funding for Computer Science research.Keywords: bibliometric analysis, biblioshiny, computer science, Nigeria, science mapping
Procedia PDF Downloads 97811 Random Subspace Neural Classifier for Meteor Recognition in the Night Sky
Authors: Carlos Vera, Tetyana Baydyk, Ernst Kussul, Graciela Velasco, Miguel Aparicio
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This article describes the Random Subspace Neural Classifier (RSC) for the recognition of meteors in the night sky. We used images of meteors entering the atmosphere at night between 8:00 p.m.-5: 00 a.m. The objective of this project is to classify meteor and star images (with stars as the image background). The monitoring of the sky and the classification of meteors are made for future applications by scientists. The image database was collected from different websites. We worked with RGB-type images with dimensions of 220x220 pixels stored in the BitMap Protocol (BMP) format. Subsequent window scanning and processing were carried out for each image. The scan window where the characteristics were extracted had the size of 20x20 pixels with a scanning step size of 10 pixels. Brightness, contrast and contour orientation histograms were used as inputs for the RSC. The RSC worked with two classes and classified into: 1) with meteors and 2) without meteors. Different tests were carried out by varying the number of training cycles and the number of images for training and recognition. The percentage error for the neural classifier was calculated. The results show a good RSC classifier response with 89% correct recognition. The results of these experiments are presented and discussed.Keywords: contour orientation histogram, meteors, night sky, RSC neural classifier, stars
Procedia PDF Downloads 130810 Optimal Evaluation of Weather Risk Insurance for Wheat
Authors: Slim Amami
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A model is developed to prevent the risks related to climate conditions in the agricultural sector. It will determine the yearly optimum premium to be paid by a farmer in order to reach his required turnover. The model is mainly based on both climatic stability and 'soft' responses of usually grown species to average climate variations at the same place and inside a safety ball which can be determined from past meteorological data. This allows the use of linear regression expression for dependence of production result in terms of driving meteorological parameters, main ones of which are daily average sunlight, rainfall and temperature. By a simple best parameter fit from the expert table drawn with professionals, optimal representation of yearly production is deduced from records of previous years, and yearly payback is evaluated from minimum yearly produced turnover. Optimal premium is then deduced, and gives the producer a useful bound for negotiating an offer by insurance companies to effectively protect their harvest. The application to wheat production in the French Oise department illustrates the reliability of the present model with as low as 6% difference between predicted and real data. The model can be adapted to almost every agricultural field by changing state parameters and calibrating their associated coefficients.Keywords: agriculture, database, meteorological factors, production model, optimal price
Procedia PDF Downloads 217809 Experimental Investigation on the Mechanical Behaviour of Three-Leaf Masonry Walls under In-Plane Loading
Authors: Osama Amer, Yaser Abdel-Aty, Mohamed Abd El Hady
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The present paper illustrates an experimental approach to provide understanding of the mechanical behavior and failure mechanisms of different typologies of unreinforced three-leaf masonry walls of historical Islamic architectural heritage in Egypt. The main objective of this study is to investigate the propagation of possible cracking, ultimate load, deformations and failure mechanisms. Experimental data on interface-shear and compression tests on large scale three-leaf masonry wallets are provided. The wallets were built basically of Egyptian limestone and modified lime mortar. External wallets were built of stone blocks while the inner leaf was built of rubble limestone. Different loading conditions and dimensions of core layer for two types of collar joints (with and without shear keys) are considered in the tests. Mechanical properties of the constituent materials of masonry were tested and a database of characteristic properties was created. The results of the experiments will highlight the properties, force-displacement curves, stress distribution of multiple-leaf masonry walls contributing to the derivation of rational design rules and validation of numerical models.Keywords: masonry, three-leaf walls, mechanical behavior, testing, architectural heritage
Procedia PDF Downloads 283808 A Study on the Assessment of Prosthetic Infection after Total Knee Replacement Surgery
Authors: Chun-Lang Chang, Chun-Kai Liu
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In this study, the patients that have undergone total knee replacement surgery from the 2010 National Health Insurance database were adopted as the study participants. The important factors were screened and selected through literature collection and interviews with physicians. Through the Cross Entropy Method (CE), Genetic Algorithm Logistic Regression (GALR), and Particle Swarm Optimization (PSO), the weights of the factors were obtained. In addition, the weights of the respective algorithms, coupled with the Excel VBA were adopted to construct the Case Based Reasoning (CBR) system. The results through statistical tests show that the GALR and PSO produced no significant differences, and the accuracy of both models were above 97%. Moreover, the area under the curve of ROC for these two models also exceeded 0.87. This study shall serve as a reference for medical staff as an assistance for clinical assessment of infections in order to effectively enhance medical service quality and efficiency, avoid unnecessary medical waste, and substantially contribute to resource allocations in medical institutions.Keywords: Case Based Reasoning, Cross Entropy Method, Genetic Algorithm Logistic Regression, Particle Swarm Optimization, Total Knee Replacement Surgery
Procedia PDF Downloads 317807 SAMRA: Dataset in Al-Soudani Arabic Maghrebi Script for Recognition of Arabic Ancient Words Handwritten
Authors: Sidi Ahmed Maouloud, Cheikh Ba
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Much of West Africa’s cultural heritage is written in the Al-Soudani Arabic script, which was widely used in West Africa before the time of European colonization. This Al-Soudani Arabic script is an African version of the Maghrebi script, in particular, the Al-Mebssout script. However, the local African qualities were incorporated into the Al-Soudani script in a way that gave it a unique African diversity and character. Despite the existence of several Arabic datasets in Oriental script, allowing for the analysis, layout, and recognition of texts written in these calligraphies, many Arabic scripts and written traditions remain understudied. In this paper, we present a dataset of words from Al-Soudani calligraphy scripts. This dataset consists of 100 images selected from three different manuscripts written in Al-Soudani Arabic script by different copyists. The primary source for this database was the libraries of Boston University and Cambridge University. This dataset highlights the unique characteristics of the Al-Soudani Arabic script as well as the new challenges it presents in terms of automatic word recognition of Arabic manuscripts. An HTR system based on a hybrid ANN (CRNN-CTC) is also proposed to test this dataset. SAMRA is a dataset of annotated Arabic manuscript words in the Al-Soudani script that can help researchers automatically recognize and analyze manuscript words written in this script.Keywords: dataset, CRNN-CTC, handwritten words recognition, Al-Soudani Arabic script, HTR, manuscripts
Procedia PDF Downloads 107806 Triangular Geometric Feature for Offline Signature Verification
Authors: Zuraidasahana Zulkarnain, Mohd Shafry Mohd Rahim, Nor Anita Fairos Ismail, Mohd Azhar M. Arsad
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Handwritten signature is accepted widely as a biometric characteristic for personal authentication. The use of appropriate features plays an important role in determining accuracy of signature verification; therefore, this paper presents a feature based on the geometrical concept. To achieve the aim, triangle attributes are exploited to design a new feature since the triangle possesses orientation, angle and transformation that would improve accuracy. The proposed feature uses triangulation geometric set comprising of sides, angles and perimeter of a triangle which is derived from the center of gravity of a signature image. For classification purpose, Euclidean classifier along with Voting-based classifier is used to verify the tendency of forgery signature. This classification process is experimented using triangular geometric feature and selected global features. Based on an experiment that was validated using Grupo de Senales 960 (GPDS-960) signature database, the proposed triangular geometric feature achieves a lower Average Error Rates (AER) value with a percentage of 34% as compared to 43% of the selected global feature. As a conclusion, the proposed triangular geometric feature proves to be a more reliable feature for accurate signature verification.Keywords: biometrics, euclidean classifier, features extraction, offline signature verification, voting-based classifier
Procedia PDF Downloads 370805 Detection and Classification of Myocardial Infarction Using New Extracted Features from Standard 12-Lead ECG Signals
Authors: Naser Safdarian, Nader Jafarnia Dabanloo
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In this paper we used four features i.e. Q-wave integral, QRS complex integral, T-wave integral and total integral as extracted feature from normal and patient ECG signals to detection and localization of myocardial infarction (MI) in left ventricle of heart. In our research we focused on detection and localization of MI in standard ECG. We use the Q-wave integral and T-wave integral because this feature is important impression in detection of MI. We used some pattern recognition method such as Artificial Neural Network (ANN) to detect and localize the MI. Because these methods have good accuracy for classification of normal and abnormal signals. We used one type of Radial Basis Function (RBF) that called Probabilistic Neural Network (PNN) because of its nonlinearity property, and used other classifier such as k-Nearest Neighbors (KNN), Multilayer Perceptron (MLP) and Naive Bayes Classification. We used PhysioNet database as our training and test data. We reached over 80% for accuracy in test data for localization and over 95% for detection of MI. Main advantages of our method are simplicity and its good accuracy. Also we can improve accuracy of classification by adding more features in this method. A simple method based on using only four features which extracted from standard ECG is presented which has good accuracy in MI localization.Keywords: ECG signal processing, myocardial infarction, features extraction, pattern recognition
Procedia PDF Downloads 450804 Causes of Variation Orders in the Egyptian Construction Industry: Time and Cost Impacts
Authors: A. Samer Ezeldin, Jwanda M. El Sarag
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Variation orders are of great importance in any construction project. Variation orders are defined as any change in the scope of works of a project that can be an addition omission, or even modification. This paper investigates the variation orders that occur during construction projects in Egypt. The literature review represents a comparison of causes of variation orders among Egypt, Tanzania, Nigeria, Malaysia and the United Kingdom. A classification of occurrence of variation orders due to owner related factors, consultant related factors and other factors are signified in the literature review. These classified events that lead to variation orders were introduced in a survey with 19 events to observe their frequency of occurrence, and their time and cost impacts. The survey data was obtained from 87 participants that included clients, consultants, and contractors and a database of 42 scenarios was created. A model is then developed to help assist project managers in predicting the frequency of variations and account for a budget for any additional costs and minimize any delays that can take place. Two experts with more than 25 years of experience were given the model to verify that the model was working effectively. The model was then validated on a residential compound that was completed in July 2016 to prove that the model actually produces acceptable results.Keywords: construction, cost impact, Egypt, time impact, variation orders
Procedia PDF Downloads 173803 Dual-Channel Multi-Band Spectral Subtraction Algorithm Dedicated to a Bilateral Cochlear Implant
Authors: Fathi Kallel, Ahmed Ben Hamida, Christian Berger-Vachon
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In this paper, a Speech Enhancement Algorithm based on Multi-Band Spectral Subtraction (MBSS) principle is evaluated for Bilateral Cochlear Implant (BCI) users. Specifically, dual-channel noise power spectral estimation algorithm using Power Spectral Densities (PSD) and Cross Power Spectral Densities (CPSD) of the observed signals is studied. The enhanced speech signal is obtained using Dual-Channel Multi-Band Spectral Subtraction ‘DC-MBSS’ algorithm. For performance evaluation, objective speech assessment test relying on Perceptual Evaluation of Speech Quality (PESQ) score is performed to fix the optimal number of frequency bands needed in DC-MBSS algorithm. In order to evaluate the speech intelligibility, subjective listening tests are assessed with 3 deafened BCI patients. Experimental results obtained using French Lafon database corrupted by an additive babble noise at different Signal-to-Noise Ratios (SNR) showed that DC-MBSS algorithm improves speech understanding for single and multiple interfering noise sources.Keywords: speech enhancement, spectral substracion, noise estimation, cochlear impalnt
Procedia PDF Downloads 540802 Seismic Hazard Prediction Using Seismic Bumps: Artificial Neural Network Technique
Authors: Belkacem Selma, Boumediene Selma, Tourkia Guerzou, Abbes Labdelli
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Natural disasters have occurred and will continue to cause human and material damage. Therefore, the idea of "preventing" natural disasters will never be possible. However, their prediction is possible with the advancement of technology. Even if natural disasters are effectively inevitable, their consequences may be partly controlled. The rapid growth and progress of artificial intelligence (AI) had a major impact on the prediction of natural disasters and risk assessment which are necessary for effective disaster reduction. The Earthquakes prediction to prevent the loss of human lives and even property damage is an important factor; that is why it is crucial to develop techniques for predicting this natural disaster. This present study aims to analyze the ability of artificial neural networks (ANNs) to predict earthquakes that occur in a given area. The used data describe the problem of high energy (higher than 10^4J) seismic bumps forecasting in a coal mine using two long walls as an example. For this purpose, seismic bumps data obtained from mines has been analyzed. The results obtained show that the ANN with high accuracy was able to predict earthquake parameters; the classification accuracy through neural networks is more than 94%, and that the models developed are efficient and robust and depend only weakly on the initial database.Keywords: earthquake prediction, ANN, seismic bumps
Procedia PDF Downloads 119801 The Role of Marketing Information System on Decision-Making: An Applied Study on Algeria Telecoms Mobile "MOBILIS"
Authors: Benlakhdar Mohamed Larbi, Yagoub Asma
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Purpose: This study aims at highlighting the significance and importance of utilizing marketing information system (MKIS) on decision-making, by clarifying the need for quick and efficient decision-making due to time saving and preventing of duplication of work. Design, methodology, approach: The study shows the roles of each part of MKIS for developing marketing strategy, which present a real challenge to individuals and institutions in an era characterized by uncertainty and clarifying the importance of each part separately, depending on decision type and the nature of the situation. The empirical research method was evaluated by specialized experts, conducted by means of questionnaires. Correlation analysis was employed to test the validity of the procedure. Results: The empirical study findings confirmed positive relationships between the level of utilizing and adopting ‘decision support system and marketing intelligence’ and the success of an organizational decision-making, and provide the organization with a competitive advantage as it allows the organization to solve problems. Originality/value: The study offer better understanding of performance- increasing market share as an organizational decision making based on marketing information system.Keywords: database, marketing research, marketing intelligence, decision support system, decision-making
Procedia PDF Downloads 316800 Multichannel Surface Electromyography Trajectories for Hand Movement Recognition Using Intrasubject and Intersubject Evaluations
Authors: Christina Adly, Meena Abdelmeseeh, Tamer Basha
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This paper proposes a system for hand movement recognition using multichannel surface EMG(sEMG) signals obtained from 40 subjects using 40 different exercises, which are available on the Ninapro(Non-Invasive Adaptive Prosthetics) database. First, we applied processing methods to the raw sEMG signals to convert them to their amplitudes. Second, we used deep learning methods to solve our problem by passing the preprocessed signals to Fully connected neural networks(FCNN) and recurrent neural networks(RNN) with Long Short Term Memory(LSTM). Using intrasubject evaluation, The accuracy using the FCNN is 72%, with a processing time for training around 76 minutes, and for RNN's accuracy is 79.9%, with 8 minutes and 22 seconds processing time. Third, we applied some postprocessing methods to improve the accuracy, like majority voting(MV) and Movement Error Rate(MER). The accuracy after applying MV is 75% and 86% for FCNN and RNN, respectively. The MER value has an inverse relationship with the prediction delay while varying the window length for measuring the MV. The different part uses the RNN with the intersubject evaluation. The experimental results showed that to get a good accuracy for testing with reasonable processing time, we should use around 20 subjects.Keywords: hand movement recognition, recurrent neural network, movement error rate, intrasubject evaluation, intersubject evaluation
Procedia PDF Downloads 129799 Lower Risk of Ischemic Stroke in Hormone Therapy Users with Use of Chinese Herbal Medicine
Authors: Shu-Hui Wen, Wei-Chuan Chang, Hsien-Chang Wu
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Background: Little is known about the benefits and risks of use of Chinese herbal medicine (CHM) in conditions related to hormone therapy (HT) use on the risk of ischemic stroke (IS). The aim of this study is to explore the risk of IS in menopausal women treated with HT and CHM. Materials and methods: A total of 32,441 menopausal women without surgical menopause aged 40- 65 years were selected from 2003 to 2010 using the 2-million random samples of the National Health Insurance Research Database in Taiwan. According to the medication usage of HT and CHM, we divided the current and recent users into two groups: an HT use-only group (n = 4,989) and an HT/CHM group (n = 9,265). Propensity-score matching samples (4,079 pairs) were further created to deal with confounding by indication. The adjusted hazard ratios (HR) of IS during HT or CHM treatment were estimated by the robust Cox proportional hazards model. Results: The incidence rate of IS in the HT/CHM group was significantly lower than in the HT group (4.5 vs. 12.8 per 1000 person-year, p < 0.001). Multivariate analysis results indicated that additional CHM use was significant with a lower risk of IS (HR = 0.3; 95% confidence interval, 0.21-0.43). Further subgroup analyses and sensitivity analyses had similar findings. Conclusion: We found that combined use of HT and CHM was associated with a lower risk for IS than HT use only. Further study is needed to examine possible mechanism underlying this association.Keywords: Chinese herbal medicine, hormone therapy, ischemic stroke, menopause
Procedia PDF Downloads 349798 Global Evidence on the Seasonality of Enteric Infections, Malnutrition, and Livestock Ownership
Authors: Aishwarya Venkat, Anastasia Marshak, Ryan B. Simpson, Elena N. Naumova
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Livestock ownership is simultaneously linked to improved nutritional status through increased availability of animal-source protein, and increased risk of enteric infections through higher exposure to contaminated water sources. Agrarian and agro-pastoral households, especially those with cattle, goats, and sheep, are highly dependent on seasonally various environmental conditions, which directly impact nutrition and health. This study explores global spatiotemporally explicit evidence regarding the relationship between livestock ownership, enteric infections, and malnutrition. Seasonal and cyclical fluctuations, as well as mediating effects, are further examined to elucidate health and nutrition outcomes of individual and communal livestock ownership. The US Agency for International Development’s Demographic and Health Surveys (DHS) and the United Nations International Children's Emergency Fund’s Multi-Indicator Cluster Surveys (MICS) provide valuable sources of household-level information on anthropometry, asset ownership, and disease outcomes. These data are especially important in data-sparse regions, where surveys may only be conducted in the aftermath of emergencies. Child-level disease history, anthropometry, and household-level asset ownership information have been collected since DHS-V (2003-present) and MICS-III (2005-present). This analysis combines over 15 years of survey data from DHS and MICS to study 2,466,257 children under age five from 82 countries. Subnational (administrative level 1) measures of diarrhea prevalence, mean livestock ownership by type, mean and median anthropometric measures (height for age, weight for age, and weight for height) were investigated. Effects of several environmental, market, community, and household-level determinants were studied. Such covariates included precipitation, temperature, vegetation, the market price of staple cereals and animal source proteins, conflict events, livelihood zones, wealth indices and access to water, sanitation, hygiene, and public health services. Children aged 0 – 6 months, 6 months – 2 years, and 2 – 5 years of age were compared separately. All observations were standardized to interview day of year, and administrative units were harmonized for consistent comparisons over time. Geographically weighted regressions were constructed for each outcome and subnational unit. Preliminary results demonstrate the importance of accounting for seasonality in concurrent assessments of malnutrition and enteric infections. Household assets, including livestock, often determine the intensity of these outcomes. In many regions, livestock ownership affects seasonal fluxes in malnutrition and enteric infections, which are also directly affected by environmental and local factors. Regression analysis demonstrates the spatiotemporal variability in nutrition outcomes due to a variety of causal factors. This analysis presents a synthesis of evidence from global survey data on the interrelationship between enteric infections, malnutrition, and livestock. These results provide a starting point for locally appropriate interventions designed to address this nexus in a timely manner and simultaneously improve health, nutrition, and livelihoods.Keywords: diarrhea, enteric infections, households, livestock, malnutrition, seasonality
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