Search results for: automatic classification

Authors: Saba Fahham, Supak Ngamsom, Suchaya Damrongsri

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Objective: The objective is to determine the optimal threshold of Romexis software for the airway volume and minimum cross-section area (MCA) analysis using Image J as a gold standard. Materials and Methods: A total of ten cone-beam computed tomography (CBCT) images were collected. The airway volume and MCA of each patient were analyzed using the automatic airway segmentation function in the CBCT DICOM viewer (Romexis). Airway volume and MCA measurements were conducted on each CBCT sagittal view with fifteen different threshold values from the Romexis software, Ranging from 300 to 1000. Duplicate DICOM files, in axial view, were imported into Image J for concurrent airway volume and MCA analysis as the gold standard. The airway volume and MCA measured from Romexis and Image J were compared using a t-test with Bonferroni correction, and statistical significance was set at p<0.003. Results: Concerning airway volume, thresholds of 600 to 850 as well as 1000, exhibited results that were not significantly distinct from those obtained through Image J. Regarding MCA, employing thresholds from 400 to 850 within Romexis Viewer showed no variance from Image J. Notably, within the threshold range of 600 to 850, there were no statistically significant differences observed in both airway volume and MCA analyses, in comparison to Image J. Conclusion: This study demonstrated that the utilization of Planmeca Romexis Viewer 6.4.3.3 within threshold range of 600 to 850 yields airway volume and MCA measurements that exhibit no statistically significant variance in comparison to measurements obtained through Image J. This outcome holds implications for diagnosing upper airway obstructions and post-orthodontic surgical monitoring.

Keywords: airway analysis, airway segmentation, cone beam computed tomography, threshold

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Authors: Fayyaz Rasool, Naureen Aziz Qureshi, Shakeela Parveen

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Labeo rohita populations from five geographical locations from the hatchery and riverine system of Punjab-Pakistan were studied for the clustering on the basis of similarities and differences based on morphometric parameters within the species. Agglomerative Hierarchical Clustering (AHC) was done by using Pearson Correlation Coefficient and Unweighted Pair Group Method with Arithmetic Mean (UPGMA) as Agglomeration method by XLSTAT 2012 version 1.02. A dendrogram with the data on the morphometrics of the representative samples of each site divided the populations of Labeo rohita in to five major clusters or classes. The variance decomposition for the optimal classification values remained as 19.24% for within class variation, while 80.76% for the between class differences. The representative central objects of the each class, the distances between the class centroids and also the distance between the central objects of the classes were generated by the analysis. A measurable distinction between the classes of the populations of the Labeo rohita was indicated in this study which determined the impacts of changing environment and other possible factors influencing the variation level among the populations of the same species.

Keywords: AHC, Labeo rohita, hatchery, riverine, morphometric

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Authors: Muthukumarasamy Govindarajan

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Detection of unwanted, unsolicited mails called spam from email is an interesting area of research. It is necessary to evaluate the performance of any new spam classifier using standard data sets. Recently, ensemble-based classifiers have gained popularity in this domain. In this research work, an efficient email filtering approach based on ensemble methods is addressed for developing an accurate and sensitive spam classifier. The proposed approach employs Naive Bayes (NB), Support Vector Machine (SVM) and Genetic Algorithm (GA) as base classifiers along with different ensemble methods. The experimental results show that the ensemble classifier was performing with accuracy greater than individual classifiers, and also hybrid model results are found to be better than the combined models for the e-mail dataset. The proposed ensemble-based classifiers turn out to be good in terms of classification accuracy, which is considered to be an important criterion for building a robust spam classifier.

Keywords: accuracy, arcing, bagging, genetic algorithm, Naive Bayes, sentiment mining, support vector machine

Procedia PDF Downloads 142

Authors: Shu-Min Tsao, Chung-Ming Lo, Shao-Chun Chen

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Most diabetes patients tend to suffer from its complication of retina diseases. Therefore, early detection and early treatment are important. In clinical examinations, using color fundus image was the most convenient and available examination method. According to the exudates appeared in the retinal image, the status of retina can be confirmed. However, the routine screening of diabetic retinopathy by color fundus images would bring time-consuming tasks to physicians. This study thus proposed a computer-aided exudate diagnosis for the screening of diabetic retinopathy. After removing vessels and optic disc in the retinal image, six quantitative features including region number, region area, and gray-scale values etc… were extracted from the remaining regions for classification. As results, all six features were evaluated to be statistically significant (p-value < 0.001). The accuracy of classifying the retinal images into normal and diabetic retinopathy achieved 82%. Based on this system, the clinical workload could be reduced. The examination procedure may also be improved to be more efficient.

Keywords: computer-aided diagnosis, diabetic retinopathy, exudate, image processing

Procedia PDF Downloads 271

Authors: Umar Albalawi, Sang C. Suh, Jinoh Kim

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As internet continues to expand its usage with an enormous number of applications, cyber-threats have significantly increased accordingly. Thus, accurate detection of malicious traffic in a timely manner is a critical concern in today’s Internet for security. One approach for intrusion detection is to use Machine Learning (ML) techniques. Several methods based on ML algorithms have been introduced over the past years, but they are largely limited in terms of detection accuracy and/or time and space complexity to run. In this work, we present a novel method for intrusion detection that incorporates a set of supervised learning algorithms. The proposed technique provides high accuracy and outperforms existing techniques that simply utilizes a single learning method. In addition, our technique relies on partial flow information (rather than full information) for detection, and thus, it is light-weight and desirable for online operations with the property of early identification. With the mid-Atlantic CCDC intrusion dataset publicly available, we show that our proposed technique yields a high degree of detection rate over 99% with a very low false alarm rate (0.4%).

Keywords: intrusion detection, supervised learning, traffic classification, computer networks

Procedia PDF Downloads 350

Authors: Sangbok Lee

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There has been much effort on process improvement for outpatient clinics to provide quality and acute care to patients. One of the efforts is no-show analysis or prediction. This work analyzes patient no-shows along with patient health conditions. The health conditions refer to clinical symptoms that each patient has, out of the followings; hyperlipidemia, diabetes, metastatic solid tumor, dementia, chronic obstructive pulmonary disease, hypertension, coronary artery disease, myocardial infraction, congestive heart failure, atrial fibrillation, stroke, drug dependence abuse, schizophrenia, major depression, and pain. A dataset from a regional hospital is used to find the relationship between the number of the symptoms and no-show probabilities. Additional analysis reveals how each symptom or combination of symptoms affects no-shows. In the above analyses, cross-classification of patients by age and gender is carried out. The findings from the analysis will be used to take extra care to patients with particular health conditions. They will be forced to visit clinics by being informed about their health conditions and possible consequences more clearly. Moreover, this work will be used in the preparation of making institutional guidelines for patient reminder systems.

Keywords: healthcare system, no show analysis, process improvment, statistical data analysis

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Authors: Song Xinze, Cai Kejian

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To further explore the application of waste plastics in asphalt pavement, this paper begins with the classification and characteristics of waste plastics. It then provides a state-of-the-art review of the preparation methods and processes of waste plastic modifiers, waste plastic-modified asphalt, and waste plastic-modified asphalt mixtures. The paper also analyzes the factors influencing the compatibility between waste plastics and asphalt and summarizes the performance evaluation indicators for waste plastic-modified asphalt and its mixtures. It explores the research approaches and findings of domestic and international scholars and presents examples of waste plastics applications in pavement engineering. The author believes that there is a basic consensus that waste plastics can improve the high-temperature performance of asphalt. The use of cracking processes to solve the storage stability of waste plastic polymer-modified asphalt is the key to promoting its application. Additionally, the author anticipates that future research will concentrate on optimizing the recycling, processing, screening, and preparation of waste plastics, along with developing composite plastic modifiers to improve their compatibility and long-term performance in asphalt pavements.

Keywords: waste plastics, asphalt pavement, asphalt performance, asphalt modification

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Authors: Hosam A. Shawky, Amr A. Abdel Fatah, Moustafa M. S. Abo ElFad, Abdel Hameed M. El-Aassar

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Water desalination projects based on reverse osmosis technology are being introduced in Egypt to combat drinking water shortage in remote areas. Reverse osmosis (RO) desalination is a pressure driven process. This paper focuses on the design of an integrated brackish water and seawater RO desalination and solar Photovoltaic (PV) technology. A small Mobile PV driven RO desalination plant prototype without batteries is designed and tested. Solar-driven reverse osmosis desalination can potentially break the dependence of conventional desalination on fossil fuels, reduce operational costs, and improve environmental sustainability. Moreover, the innovative features incorporated in the newly designed PV-RO plant prototype are focusing on improving the cost effectiveness of producing drinkable water in remote areas. This is achieved by maximizing energy yield through an integrated automatic single axis PV tracking system with programmed tilting angle adjustment. An autonomous cleaning system for PV modules is adopted for maximizing energy generation efficiency. RO plant components are selected so as to produce 4-5 m3/day of potable water. A basic criterion in the design of this PV-RO prototype is to produce a minimum amount of fresh water by running the plant during peak sun hours. Mobility of the system will provide potable water to isolated villages and population as well as ability to provide good drinking water to different number of people from any source that is not drinkable.

Keywords: design, reverse osmosis, photovoltaic, energy, desalination, Egypt

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Authors: Siao-Wei Jiang, Boy-Young Hsieh, Ching-Liang Hsieh, Cheng-Yung Lin

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The problems of multiple drug resistance in the pig farming industry have been emphasized in recent years. Diarrhea syndrome is common in weaning piglets and often treated with antibiotics as a feed additive, leading to the rapid spread of antibiotic resistance and posing high health risks to humans. The study aimed to alleviate diarrhea syndrome with traditional herbal medicine, Xiang Sha Liu Jun Zi Tang, whose effects enhanced digestive function. Piglets at 4 weeks old with stool classified to Bristol stool classification type 6 or type 7 were randomly divided into the control group, group A (1% of Xiang Sha Liu Jun Zi Tang) and group B (0.1% Colistin). The piglets were administrated for 7 days, and their weight, feed intake, and stool score were recorded daily before and after the trial. The results showed that the diarrhea index score in group A and group B improved significantly compared to the control group, indicating that Xiang Sha Liu Jun Zi Tang may have the same effect on alleviating diarrhea syndrome as Colistin, and it may be another replacement for antibiotics.

Keywords: pig, diarrhea, herbal medicine, Xiang Sha Liu Jun Zi Tang

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Authors: Blessing Mavhuru, Nthaduleni Nethengwe, Hector Chikoore, Onyango Beneah Daniel Odhiambo

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The main objective of this study was to classify land use/cover and how it has changed in Nzhelele Valley Limpopo Province, South Africa. The study aimed to identify and analyse the types of land use/cover in the years 2005, 2010, and 2015 with a view to assess the impact on soil erosion over time. Using GIS, the changes within land use/cover were assessed through the classification of satellite images. The study area was classified into four major land cover/use classes, which are vegetation, gravel road, built up land and agricultural fields. Over the period 2005-2015 the resultant land use/cover demonstrated (i) a significant increase (12%) for vegetation cover, (ii) a significant decrease in agriculture (16%) land use/cover, (iii) increase in built-up land (1%), as well as (iv) an increase in gravel roads (3%). This study envisages assisting policy makers in decision making on land use management for Nzhelele Valley.

Keywords: land use, land cover, change, soil erosion

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Authors: Sabra Saeidi

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This research focuses on the historical techniques associated with the lajevardina and Haft-Rangi production methods in creating tiles, with emphasis on the identification of the techniques of inserting gold sheets on the surface of such historical glazed tiles. In this regard, firstly, the history of the production of enamel, gold plated, and Lajevardina glazed pottery work made during the Khwarizmanshahid and Mongol era (eleventh to the thirteenth century) have been assessed to reach a better understanding of the background and the history associated with historical glazing methods. After the historical overview of the production technique of glazed pottery work and introductions of the civilizations using those techniques, we focused on the niches production methods of enamel and Lajevardina glazing, which are two categories of decorations usually found in tiles. Next, a general classification method for various types of gilt tiles has been introduced, which is applicable to the tile works up to Safavid period (Sixteenth to the seventeenth century). Gilded lajevardina glazed tiles, gilt Haft-Rangi tiles, monolithic glazed gilt tiles, and gilt mosaic tiles are included in the categories.

Keywords: gilt tiles, Islamic art, Iranian art, historical studies, gilding

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Authors: N. Bekenova, A. Aitkaliyev, B. Kassiyeva, T. Vochshenkova

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Cardiac autonomic neuropathy is not always detected in diabetes, and its phenotypic manifestations may not be evident. Therefore, the study of genetic markers predisposing to the disease is gaining increasing relevance. Research Objective: The goal is to investigate the association of polymorphisms in the APOE and FTO genes with cardiac autonomic neuropathy among individuals of Kazakh nationality. Materials and Methods: A case-control study included 147 patients with cardiac autonomic neuropathy (cases) and 153 patients without cardiac autonomic neuropathy (controls). 300 individuals of Kazakh nationality were recruited from a hospital affiliated with the RSE ‘Medical Centre Hospital of the President's Affairs Administration of the Republic of Kazakhstan.’ Patients were genotyped for 5 FTO gene polymorphisms (rs17817449, rs1121980, rs11075995, rs9939609, rs12149832) and 2 APOE gene polymorphisms (rs429358, rs7412) using real-time PCR. Statistical analysis involved Chi-square methods and calculation of odds ratios (OR) with 95% confidence intervals (CI) and was performed using the Gen Expert genetic calculator. Results. Our research revealed an association between cardiac autonomic neuropathy and rs12149832 (FTO) and rs429358 (APOE). The AA genotype of the rs12149832 polymorphism was found to double the risk of neuropathy development, while the GA genotype decreased the risk of autonomic neuropathy (2.21 (1.38-3.52) and 0.61 (0.38-0.96), respectively, p=0.003). Additionally, we identified that the TC genotype of rs429358 predisposes individuals to the development of cardiac autonomic neuropathy, while the CC genotype decreases the risk (2.23 (1.18-4.22) and 0.26 (0.03-2.31), respectively). Conclusion. Thus, polymorphisms in the APOE and FTO genes (rs429358 and rs12149832) are associated with a predisposition to cardiac autonomic neuropathy and may play a significant role in the pathogenesis of the disease. Further research with a larger sample size and an assessment of their impact on the phenotype is necessary.

Keywords: polymorphisms, APOE gene, FTO gene, automatic neuropathy, Kazakh population.

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Authors: Qiang Zhang, Xiaojian Hu1

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Intersection is the place where vehicles and pedestrians must pass through, turn and evacuate. Obtaining the motion data of vehicles near the intersection is of great significance for transportation research. Since there are usually many targets and there are more conflicts between targets, this makes it difficult to obtain vehicle motion parameters in traffic videos of intersections. According to the characteristics of traffic videos, this paper applies video technology to realize the automated track, count and trajectory extraction of vehicles to collect traffic data by roadside surveillance cameras installed near the intersections. Based on the video recognition method, the vehicles in each lane near the intersection are tracked with extracting trajectory and counted respectively in various degrees of occlusion and visibility. The performances are compared with current recognized CPU-based algorithms of real-time tracking-by-detection. The speed of the presented system is higher than the others and the system has a better real-time performance. The accuracy of direction has reached about 94.99% on average, and the accuracy of classification and statistics has reached about 75.12% on average.

Keywords: tracking and statistics, vehicle, signalized intersection, motion parameter, trajectory

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Authors: S. Bayona, J. Nunez, D. Paez, C. Diaz

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The application of Lean manufacturing tools continues to be an effective solution for increasing productivity, reducing costs and eliminating waste in the manufacture of goods and services. This article analyzes the production process of a hot asphalt manufacturing company from an administrative and technical perspective. Three main phases were analyzed, the first phase was related to the determination of the risk priority number of the main operations in asphalt mix production process by an FMEA (Failure Mode Effects Analysis), in the second phase the Value Stream Mapping (VSM) of the production line was performed and in the third phase a SWOT (Strengths, Weaknesses Opportunities, Threats) matrix was constructed. Among the most valued failure modes were the lack training of workers in occupational safety and health issues, the lack of signaling and classification of granulated material, and the overweight of vehicles loaded. The analysis of the results in the three phases agree on the importance of training operational workers, improve communication with external actors in order to minimize delays in material orders and strengthen control suppliers.

Keywords: asphalt, lean manufacturing, productivity, process

Procedia PDF Downloads 117

Authors: Lindelwa Mngomezulu, Tonderai Muchenje

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Over the decades, E-mails provide easy, fast and timely communication enabling businesses and state owned agencies to communicate with their stakeholders and with their own employees in real-time. Moreover, since the launch of Microsoft office 365 and many other clouds based E-mail services, many businesses have been migrating from the on premises E-mail services to the cloud and more precisely since the beginning of the Covid-19 pandemic, there has been a significant increase of E-mails utilization, which then leads to the increase of cyber-attacks. In that regard, E-mail security has become very important in the E-mail transportation to ensure that the E-mail gets to the recipient without the data integrity being compromised. The classification of the features to enhance E-mail security for further from the enhanced cyber-attacks as we are aware that since the technology is advancing so at the cyber-attacks. Therefore, in order to maximize the data integrity we need to also maximize security of the E-mails such as enhanced E-mail authentication. The successful enhancement of E-mail security in the future may lessen the frequency of information thefts via E-mails, resulting in the data of South African State-owned agencies not being compromised.

Keywords: e-mail security, cyber-attacks, data integrity, authentication

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Authors: Eugene Stepanov, Arkadi Ponossov

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Many mathematical models used in biological and other applications are ill-posed. The reason for that is the nature of differential equations, where the nonlinearities are assumed to be step functions, which is done to simplify the analysis. Prominent examples are switched systems arising from gene regulatory networks and neural field equations. This simplification leads, however, to theoretical and numerical complications. In the presentation, it is proposed to apply the theory of hybrid feedback controls to regularize the problem. Roughly speaking, one attaches a finite state control (‘automaton’), which follows the trajectories of the original system and governs its dynamics at the points of ill-posedness. The construction of the automaton is based on the classification of the attractors of the specially designed adjoint dynamical system. This ‘hybridization’ is shown to regularize the original switched system and gives rise to efficient hybrid numerical schemes. Several examples are provided in the presentation, which supports the suggested analysis. The method can be of interest in other applied fields, where differential equations contain step-like nonlinearities.

Keywords: hybrid feedback control, ill-posed problems, singular perturbation analysis, step-like nonlinearities

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Authors: Ram Manohar Singh, Meenakshi Gupta

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Various terms such as ‘learning style’, ‘cognitive style’, ‘conceptual style’, ‘thinking style’, ‘intellectual style’ are used in literature to refer to an individual’s characteristic and consistent approach to organizing and processing information. However, style concepts are criticized for mutually overlapping definitions and confusing classification. This confusion should be addressed at the conceptual as well as empirical level. This paper is an attempt to bridge this gap in literature by proposing a new concept: expansive-restrictive intellectual style based on phenomenological analysis of an auto-ethnography and interview of 26 information technology (IT) professionals working in knowledge intensive organizations (KIOs) in India. Expansive style is an individual’s preference to expand his/her horizon of knowledge and understanding by gaining real meaning and structure of his/her work. On the contrary restrictive style is characterized by an individual’s preference to take minimalist approach at work reflected in executing a job efficiently without an attempt to understand the real meaning and structure of the work. The analysis suggests that expansive-restrictive style has three dimensions: (1) field dependence-independence (2) cognitive involvement and (3) epistemological beliefs.

Keywords: expansive, knowledge workers, restrictive, style

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Authors: Maria Konstadinou, Etienne Alderlieste, Anderson Peccin da Silva, Ben Arntz, Leonard van der Bijl, Wouter Verschueren

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The shear strength and compression properties of stiff Boom clay from Belgium at the depth of about 30 m has been investigated by means of cone penetration and laboratory testing. The latter consisted of index classification, constant rate of strain, direct, simple shear, and unconfined compression tests. The Boom clay samples exhibited strong swelling tendencies. The suction pressure was measured via different procedures and has been compared to the expected in-situ stress. The undrained shear strength and OCR profile determined from CPTs is not compatible with the experimental measurements, which gave significantly lower values. The observed response can be attributed to the presence of pre-existing discontinuities, as shown in microscale CT scans of the samples. The results of this study demonstrate that the microstructure of the clay prior to testing has an impact on the mechanical behaviour and can cause inconsistencies in the comparison of the laboratory test results with in-situ data.

Keywords: boom clay, laboratory testing, overconsolidation ratio, stress-strain response, swelling, undrained shear strength

Procedia PDF Downloads 146

Authors: Anita Kushwaha

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We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance.

Keywords: bio-inspired computation, nature- inspired computation, natural computing, data mining

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Authors: Franziska Klauser, Manuel Schwabl, Alexander Weissinger, Christoph Schmidl, Walter Haslinger, Anne Kasper-Giebl

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Benzo(a)pyrene (BaP) is the most widely investigated representative of Polycyclic Aromatic Hydrocarbons (PAH) as well as one of the most toxic compounds in this group. Since 2013 in the European Union a limit value for BaP concentration in the ambient air is applied, which was set to a yearly average value of 1 ng m-3. Several reports show that in some regions, even where industry and traffic are of minor impact this threshold is regularly exceeded. This is taken as proof that biomass combustion for heating purposes contributes significantly to BaP pollution. Several investigations have been already carried out on the BaP emission behavior of biomass combustion furnaces, mostly focusing on a certain aspect like the influences from wood type, of operation type or of technology type. However, a superior view on emission patterns of BaP from biomass combustion and the aggregation of determined values also from recent studies is not presented so far. The combination of determined values allows a better understanding of the BaP emission behavior from biomass combustion. In this work the review conclusions are driven from the combination of outcomes from different publication. In two examples it was shown that technical progress leads to 10 to 100 fold lower BaP emission from modern furnaces compared to old technologies of equivalent type. It was also indicated that the operation with pellets or wood chips exhibits clearly lower BaP emission factors compared to operation with log wood. Although, the BaP emission level from automatic furnaces is strongly impacted by the kind of operation. This work delivers an overview on BaP emission factors from different biomass combustion appliances, from different operation modes and from the combustion of different fuel and wood types. The main impact factors are depicted, and suggestions for low BaP emission biomass combustion are derived. As one result possible investigation fields concerning BaP emissions from biomass combustion that seem to be most important to be clarified are suggested.

Keywords: benzo(a)pyrene, biomass, combustion, emission, pollution

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Authors: Isomar Lima da Silva, Aristeu Jonatas Leite de Oliveira, Roberto Maia Augusto

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Biological isolation capsules are equipment commonly used in the control and prevention of infectious diseases in the hospital environment. This type of equipment, combined with pre-established medical protocols, contributes significantly to the containment of highly transmissible pathogens such as COVID-19. Due to its hermetic isolation, it allows more excellent patient safety, protecting companions and the health team. In this context, this work presents the development, testing, and validation of a medical capsule to treat patients affected by COVID-19. To this end, requirements such as low cost and easy handling were considered to meet the demand of people infected with the virus in remote locations in the Amazon region and/or where there are no ICU beds and mechanical ventilators for orotracheal intubation. Conceived and developed in a partnership between SAMEL Planos de Saúde and Instituto Conecthus, the device entitled "Vanessa Capsule" was designed to be used together with the NIV protocol (non-invasive ventilation), has an automatic exhaust system and filters performing the CO2 exchange, in addition to having BiPaps ventilatory support equipment (mechanical fans) in the Cabin Kit. The results show that the degree of effectiveness in protecting against infection by aerosols, with the protection cabin, is satisfactory, implying the consideration of the Vanessa capsule as an auxiliary method to be evaluated by the health team. It should also be noted that the medical observation of the evaluated patients found that the treatment against the COVID-19 virus started earlier with non-invasive mechanical ventilation reduces the patient's suffering and contributes positively to their recovery, in association with isolation through the Vanessa capsule.

Keywords: COVID-19, mechanical ventilators, medical capsule, non-invasive ventilation

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Authors: Elnaz Lashgari, Emel Demircan

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Electromyography (EMG) is one of the most important interfaces between humans and robots for rehabilitation. Decoding this signal helps to recognize muscle activation and converts it into smooth motion for the robots. Detecting each muscle’s pattern during walking and running is vital for improving the quality of a patient’s life. In this study, EMG data from 10 muscles in 10 subjects at 4 different speeds were analyzed. EMG signals are nonlinear with high dimensionality. To deal with this challenge, we extracted some features in time-frequency domain and used manifold learning and Laplacian Eigenmaps algorithm to find the intrinsic features that represent data in low-dimensional space. We then used the Bayesian classifier to identify various patterns of EMG signals for different muscles across a range of running speeds. The best result for vastus medialis muscle corresponds to 97.87±0.69 for sensitivity and 88.37±0.79 for specificity with 97.07±0.29 accuracy using Bayesian classifier. The results of this study provide important insight into human movement and its application for robotics research.

Keywords: electromyography, manifold learning, ISOMAP, Laplacian Eigenmaps, locally linear embedding

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Authors: Abdul Rochim, Didier Marot, Luc Sibille

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This paper studies the characterization of soil sensibility due to suffusion process by carrying out a series of one-dimensional downward seepage flow tests realized with an erodimeter. Tests were performed under controlled hydraulic gradient in sandy gravel soils. We propose the analysis based on energy induced by the seepage flow to characterize the hydraulic loading and the cumulative eroded dry mass to characterize the soil response. With this approach, the effect of hydraulic loading histories and initial fines contents to soil sensibility are presented. It is found that for given soils, erosion coefficients are different if tests are performed under different hydraulic loading histories. For given initial fines fraction contents, the sensibility may be grouped in the same classification. The lower fines content soils tend to require larger flow energy to the onset of erosion. These results demonstrate that this approach is effective to characterize suffusion sensibility for granular soils.

Keywords: erodimeter, sandy gravel, suffusion, water seepage energy

Procedia PDF Downloads 447

Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

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The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.

Keywords: decision tree, breast cancer, probability, data mining

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Authors: Zukhrof Romadhon, Nani Kurniati

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Availability of Spare parts is critical to support maintenance tasks and the production system. Managing spare part inventory deals with some parameters and objective functions, as well as the tradeoff between inventory costs and spare parts availability. Several mathematical models and methods have been developed to optimize the spare part policy. Many researchers who proposed optimization models need to be considered to identify other potential models. This work presents a review of several pertinent literature on spare part inventory optimization and analyzes the gaps for future research. Initial investigation on scholars and many journal database systems under specific keywords related to spare parts found about 17K papers. Filtering was conducted based on five main aspects, i.e., replenishment policy, objective function, echelon network, lead time, model solving, and additional aspects of part classification. Future topics could be identified based on the number of papers that haven’t addressed specific aspects, including joint optimization of spare part inventory and maintenance.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenance

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Authors: Vani Singhal, Jitendra Parmar, Satyendra Singh Chouhan

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Unseen class discovery has now become an important part of a machine-learning algorithm to judge new classes. Unseen classes are the classes on which the machine learning model is not trained on. With the advancement in technology and AI replacing humans, the amount of data has increased to the next level. So while implementing a model on real-world examples, we come across unseen new classes. Our aim is to find the number of unseen classes by using a hierarchical-based active learning algorithm. The algorithm is based on hierarchical clustering as well as active sampling. The number of clusters that we will get in the end will give the number of unseen classes. The total clusters will also contain some clusters that have unseen classes. Instead of first discovering unseen classes and then finding their number, we directly calculated the number by applying the algorithm. The dataset used is for intent classification. The target data is the intent of the corresponding query. We conclude that when the machine learning model will encounter real-world data, it will automatically find the number of unseen classes. In the future, our next work would be to label these unseen classes correctly.

Keywords: active sampling, hierarchical clustering, open world learning, unseen class discovery

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Authors: Grzegorz Sierpiński, Ireneusz Celiński, Marcin Staniek

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The article discusses multi modal mobility in contemporary societies as a main planning and organization issue in the functioning of administrative bodies, a problem which really exists in the space of contemporary cities in terms of shaping modern transport systems. The article presents classification of available resources and initiatives undertaken for developing multi modal mobility. Solutions can be divided into three groups of measures–physical measures in the form of changes of the transport network infrastructure, organizational ones (including transport policy) and information measures. The latter ones include in particular direct support for people travelling in the transport network by providing information about ways of using available means of transport. A special measure contributing to this end is a trip planner. The article compares several selected planners. It includes a short description of the Green Travelling Project, which aims at developing a planner supporting environmentally friendly solutions in terms of transport network operation. The article summarizes preliminary findings of the project.

Keywords: mobility, modal split, multimodal trip, multimodal platforms, sustainable transport

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Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

Abstract:

Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

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Authors: Dato Surmanidze, Dato Antadze, Tornike Partenadze

Abstract:

Public online services in Georgia are concentrated on main target segments: public administration, business, population, non-governmental and other interested organizations. Therefore, the strategy of digital Georgia is focused on providing G2C, G2B/B2G, G2NGO and G2G services. In G2C framework sophisticated and high-technological online services have been developed in order to provide passports, identity cards, documentations concerning residence and civil acts (birth, marriage, divorce, child adoption, change of name and surname, death, etc) as well as other services. Websites like my.gov.ge and sda.gov.ge have distance services like electronic application, processing and decision making. In line with international standards automatic services like electronic tenders, product catalogues, invoices and payment have been developed. This creates better investment climate for foreign companies in Georgia in the framework of G2B politics. The website mybusiness.gov.ge creates better conditions for local business. Among electronic services is e-NRMS (electronic system for national resource management) which was introduced by the Ministry of Finance of Georgia. The system was created in order to ensure management of national resources by state and business organizations. It is integrated with bank services and provides G2C, G2B and B2G representatives with electronic services. Also a portal meteo.gov.ge was created which gives electronic services concerning air, geological, environmental and pollution issues. Also worknet.gov.ge should be mentioned which is an electronic hub of information management for employers and employees. The information portal of labor market will facilitate receipt of information, its analysis and delivery to interested people like employers and employees. However, nowadays it’s been two years that only employees portal is activated. Therefore, awareness about the portal, its competitiveness and success is undermined.

Keywords: electronic services, public administration, information technology, information society

Procedia PDF Downloads 268

Authors: Miguel Ramirez, Ivan Lizarazo

Abstract:

The emergence of various interpretations of sustainability, including weak and strong paradigms, can be traced back to the definition of sustainable development provided in the 1987 Brundtland report and the subsequent evolution of the sustainability concept. However, there has been limited scholarly attention given to clarifying the concept of sustainability within the theoretical and conceptual framework of geography. The discipline has predominantly been focused on understanding the diverse conceptions of sustainability within its epistemological boundaries, resulting in tensions between sustainability paradigms and their associated dimensions, including the incorporation of political perspectives, with particular emphasis on environmental geography's epistemology. In response to this gap, a conceptual framework for sustainability is proposed, effectively integrating spatial and territorial concepts. This framework aims to enhance geography's role in contributing to sustainability by utilizing the land system theory, which is based on the dynamics of land use change. Such an integrated conceptual framework enables incorporating methodological tools such as remote sensing, encompassing various earth observations and fusion methods, and supervised classification techniques. Additionally, it looks for better integration of socioecological information, thereby capturing essential population-related features.

Keywords: geography, sustainability, land change science, territorial sustainability

Procedia PDF Downloads 80