Search results for: taxonomic classification

Authors: Panprapa Yongtrakul, Punyaphat Sirithanabadeekul, Pakjira Siriphan

Abstract:

Background: The thread lift technique has become popular because it is less invasive, requires a shorter operation, less downtime, and results in fewer postoperative complications. The advantage of the technique is that the thread can be inserted under the skin without the need for long incisions. Currently, there are a lot of thread lift techniques with respect to the specific types of thread used on specific areas, such as the mid-face, lower face, or neck area. Objective: To review the thread lift technique for specific areas according to type of thread, patient selection, and how to match the most appropriate to the patient. Materials and Methods: A literature review technique was conducted by searching PubMed and MEDLINE, then compiled and summarized. Result: We have divided our protocols into two sections: Protocols for short suture, and protocols for long suture techniques. We also created 3D pictures for each technique to enhance understanding and application in a clinical setting. Conclusion: There are advantages and disadvantages to short suture and long suture techniques. The best outcome for each patient depends on appropriate patient selection and determining the most suitable technique for the defect and area of patient concern.

Keywords: thread lift, thread lift method, thread lift technique, thread lift procedure, threading

Procedia PDF Downloads 265

Authors: Dimitar Karastoyanov, Todor Penchev

Abstract:

The paper presents the research of a kind of autonomous mobile robots, intended for work and adaptive perception in unknown and unstructured environment. The objective are robots, dedicated for multi-sensory environment perception and exploration, like measurements and samples taking, discovering and putting a mark on the objects as well as environment interactions–transportation, carrying in and out of equipment and objects. At that ground classification of the different types mobile robots in accordance with the way of locomotion (wheel- or chain-driven, walking, etc.), used drive mechanisms, kind of sensors, end effectors, area of application, etc. is made. Modular system for the mechanical construction of the mobile robots is proposed. Special PLC on the base of AtMega128 processor for robot control is developed. Electronic modules for the wireless communication on the base of Jennic processor as well as the specific software are developed. The methods, means and algorithms for adaptive environment behaviour and tasks realization are examined. The methods of group control of mobile robots and for suspicious objects detecting and handling are discussed too.

Keywords: mobile robots, wireless communications, environment investigations, group control, suspicious objects

Procedia PDF Downloads 358

Authors: Fayyaz Rasool, Naureen Aziz Qureshi, Shakeela Parveen

Abstract:

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

Procedia PDF Downloads 456

Authors: Muthukumarasamy Govindarajan

Abstract:

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 143

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

Abstract:

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 274

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

Abstract:

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 353

Authors: Sangbok Lee

Abstract:

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

Procedia PDF Downloads 233

Authors: Song Xinze, Cai Kejian

Abstract:

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

Procedia PDF Downloads 39

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

Abstract:

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

Procedia PDF Downloads 51

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

Abstract:

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

Procedia PDF Downloads 254

Authors: Sabra Saeidi

Abstract:

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

Procedia PDF Downloads 123

Authors: D. Madhushanka, Y. Liu, H. C. Fernando

Abstract:

Fires are one of the foremost factors of land surface disturbance in diverse ecosystems, causing soil erosion and land-cover changes and atmospheric effects affecting people's lives and properties. Generally, the severity of the fire is calculated as the Normalized Burn Ratio (NBR) index. This is performed manually by comparing two images obtained afterward. Then by using the bitemporal difference of the preprocessed satellite images, the dNBR is calculated. The burnt area is then classified as either unburnt (dNBR<0.1) or burnt (dNBR>= 0.1). Furthermore, Wildfire Severity Assessment (WSA) classifies burnt areas and unburnt areas using classification levels proposed by USGS and comprises seven classes. This procedure generates a burn severity report for the area chosen by the user manually. This study is carried out with the objective of producing an automated tool for the above-mentioned process, namely the World Wildfire Severity Assessment Tool (WWSAT). It is implemented in Google Earth Engine (GEE), which is a free cloud-computing platform for satellite data processing, with several data catalogs at different resolutions (notably Landsat, Sentinel-2, and MODIS) and planetary-scale analysis capabilities. Sentinel-2 MSI is chosen to obtain regular processes related to burnt area severity mapping using a medium spatial resolution sensor (15m). This tool uses machine learning classification techniques to identify burnt areas using NBR and to classify their severity over the user-selected extent and period automatically. Cloud coverage is one of the biggest concerns when fire severity mapping is performed. In WWSAT based on GEE, we present a fully automatic workflow to aggregate cloud-free Sentinel-2 images for both pre-fire and post-fire image compositing. The parallel processing capabilities and preloaded geospatial datasets of GEE facilitated the production of this tool. This tool consists of a Graphical User Interface (GUI) to make it user-friendly. The advantage of this tool is the ability to obtain burn area severity over a large extent and more extended temporal periods. Two case studies were carried out to demonstrate the performance of this tool. The Blue Mountain national park forest affected by the Australian fire season between 2019 and 2020 is used to describe the workflow of the WWSAT. This site detected more than 7809 km2, using Sentinel-2 data, giving an error below 6.5% when compared with the area detected on the field. Furthermore, 86.77% of the detected area was recognized as fully burnt out, of which high severity (17.29%), moderate-high severity (19.63%), moderate-low severity (22.35%), and low severity (27.51%). The Arapaho and Roosevelt National Forest Park, California, the USA, which is affected by the Cameron peak fire in 2020, is chosen for the second case study. It was found that around 983 km2 had burned out, of which high severity (2.73%), moderate-high severity (1.57%), moderate-low severity (1.18%), and low severity (5.45%). These spots also can be detected through the visual inspection made possible by cloud-free images generated by WWSAT. This tool is cost-effective in calculating the burnt area since satellite images are free and the cost of field surveys is avoided.

Keywords: burnt area, burnt severity, fires, google earth engine (GEE), sentinel-2

Procedia PDF Downloads 238

Authors: Qiang Zhang, Xiaojian Hu1

Abstract:

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

Procedia PDF Downloads 221

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

Abstract:

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 118

Authors: Lindelwa Mngomezulu, Tonderai Muchenje

Abstract:

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

Procedia PDF Downloads 138

Authors: Eugene Stepanov, Arkadi Ponossov

Abstract:

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

Procedia PDF Downloads 247

Authors: Ram Manohar Singh, Meenakshi Gupta

Abstract:

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

Procedia PDF Downloads 424

Authors: Kristina Karapetyan, Flora Tkhruni, Tsovinar Balabekyan, Arevik Israyelyan, Tatyana Khachatryan

Abstract:

The ability of the lactic acid bacteria (LAB) to prevent and cure a variety of diseases, their protective role against infections and colonization of pathogenic microorganisms in the digestive tract, has lead to the coining of the term probiotics or pro-life. LAB inhibiting the growth of pathogenic and food spoilage microorganisms, maintaining the nutritive quality and improving the shelf life of foods. They have also been used as flavor and texture producers. Enterococcus strains have been used for treatment of diseases such as diarrhea or antibiotic associated diarrhea, inflammatory pathologies that affect colon such as irritable bowel syndrome, or immune regulation, diarrhea caused by antibiotic treatments. The obtaining and investigation of biological properties of proteinoceous antibiotics, on the basis of probiotic LAB shown, that bacteriocins, metabiotics, and peptides of LAB represent bactericides have a broad range of activity and are excellent candidates for development of new prophylactic and therapeutic substances to complement or replace conventional antibiotics. The genotyping by 16S rRNA sequencing for LAB were used. Cell free culture broth (CFC) broth was purified by the Gel filtration method on the Sephadex Superfine G 25 resin. Antimicrobial activity was determined by spot-on-lawn method and expressed in arbitrary units (AU/ml). The diversity of multidrug-resistance (MDR) of pathogenic strains to antibiotics, most widely used for treatment of human diseases in the Republics of Armenia and Nagorno Karabakh were examined. It was shown, that difference of resistance of pathogens to antibiotics depends on their isolation sources. The influences of partially purified antimicrobial preparations (AMP), obtained from the different strains of Enterococcus genus on the growth of MDR pathogenic bacteria were investigated. It was shown, that bacteriocin containing partially purified preparations, obtained from different strains of Enterococcus faecium and durans species, possess bactericidal or bacteriostatic activity against antibiotic resistant intestinal, spoilage and food-borne pathogens such as Listeria monocytogenes, Staphylococcus aureus, E. coli, and Salmonella. Endemic strains of LAB, isolated from Matsoni made from donkey, buffalo and goat milk, shown broad spectrum of activity against food spoiling microorganisms, moulds and fungi, such as Salmonella sp., Esherichia coli, Aspergillus and Penicillium species. Highest activity against MDR pathogens shown bacteria, isolated from goat milk products. High stability of the investigated strains of the genus Enerococcus, isolated from samples of matsun from different regions of Nagorno-Karabakh (NKR) to the antibiotics was shown. The obtained data show high stability of the investigated different strains of the genus Enerococcus. The high genetic diversity in Enterococcus group suggests adaptations for specific mutations in different environments. Thus, endemic strains of LAB are able to produce bacteriocins with high and different inhibitory activity against broad spectrum of microorganisms isolated from different sources and belong to different taxonomic group. Prospect of the use of certain antimicrobial preparations against pathogenic strains is obvious. These AMP can be applied for long term use against different etiology antibiotic resistant pathogens for prevention or treatment of infectional diseases as an alternative to antibiotics.

Keywords: antimicrobial biopreparation, endemic lactic acid bacteria, intra-species diversity, multidrug resistance of pathogens

Procedia PDF Downloads 310

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

Abstract:

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 147

Authors: Anita Kushwaha

Abstract:

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

Procedia PDF Downloads 274

Authors: Elnaz Lashgari, Emel Demircan

Abstract:

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

Procedia PDF Downloads 365

Authors: Abdul Rochim, Didier Marot, Luc Sibille

Abstract:

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: K. Karapetyan, F. Tkhruni, A. Aghajanyan, T. S. Balabekyan, L. Arstamyan

Abstract:

Introduction: Globalization of the food supply has created the conditions favorable for the emergence and spread of food-borne and especially dangerous pathogens (EDP) in developing countries. The fresh-cut fruit and vegetable industry is searching for alternatives to replace chemical treatments with biopreservative approaches that ensure the safety of the processed foods product. Antimicrobial compounds of lactic acid bacteria (LAB) possess bactericidal or bacteriostatic activity against intestinal pathogens, spoilage organisms and food-borne pathogens such as Listeria monocytogenes, Staphylococcus aureus and Salmonella. Endemic strains of LAB were isolated. The strains, showing broad spectrum of antimicrobial activity against food spoiling microorganisms, were selected. The genotyping by 16S rRNA sequencing, GS-PCR, RAPD PCR methods showed that they were presented by Lactobacillus rhamnosus109, L.plantarum 65, L.plantarum 66 and Enterococcus faecium 64 species. LAB are deposited in "Microbial Depository Center" (MDC) SPC "Armbiotechnology". Methods: LAB strains were isolated from different dairy products from rural households from the highland regions of Armenia. Serially diluted samples were spread on MRS (Merck, Germany) and hydrolyzed milk agar (1,2 % w/v). Single colonies from each LAB were individually inoculated in liquid MRS medium and incubated at 37oC for 24 hours. Culture broth with biomass was centrifuged at 10,000 g during 20 min for obtaining of cell free culture broth (CFC). The antimicrobial substances from CFC broth were purified by the combination of adsorption-desorption and ion-exchange chromatography methods. Separation of bacteriocins was performed using a HPLC method on "Avex ODS" C18 column. Mass analysis of peptides recorded on the device API 4000 in the electron ionization mode. The spot-on-lawn method on the test culture plated in the solid medium was applied. The antimicrobial activity is expressed in arbitrary units (AU/ml). Results. Purification of CFC broth of LAB allowed to obtain partially purified antimicrobial preparations which contains bacteriocins with broad spectrum of antimicrobial activity. Investigation of their main biochemical properties shown, that inhibitory activity of preparations is partially reduced after treatment with proteinase K, trypsin, pepsin, suggesting a proteinaceous nature of bacteriocin-like substances containing in CFC broth. Preparations preserved their activity after heat treatment (50-121 oC, 20 min) and were stable in the pH range 3–8. The results of SDS PAAG electrophoresis show that L.plantarum 66 and Ent.faecium 64 strains have one bacteriocin (BCN) with maximal antimicrobial activity with approximate molecular weight 2.0-3.0 kDa. From L.rhamnosus 109 two BCNs were obtained. Mass spectral analysis indicates that these bacteriocins have peptide bonds and molecular weight of BCN 1 and BCN 2 are approximately 1.5 kDa and 700 Da. Discussion: Thus, our experimental data shown, that isolated endemic strains of LAB are able to produce bacteriocins with high and different inhibitory activity against broad spectrum of microorganisms of different taxonomic group, such as Salmonella sp., Esherichia coli, Bacillus sp., L.monocytogenes, Proteus mirabilis, Staph. aureus, Ps. aeruginosa. Obtained results proved the perspectives for use of endemic strains in the preservation of foodstuffs. Acknowledgments: This work was realized with financial support of the Project Global Initiatives for Preliferation Prevention (GIPP) T2- 298, ISTC A-1866.

Keywords: antimicrobial activity, bacteriocins, endemic strains, food safety

Procedia PDF Downloads 562

Authors: Dawood Al Chanti, Alice Caplier

Abstract:

Sparse representations of signals have received a great deal of attention in recent years. In this paper, the interest of using sparse representation as a mean for performing sparse discriminative analysis between spontaneous facial expressions is demonstrated. An automatic facial expressions recognition system is presented. It uses a KSVD-SVM approach which is made of three main stages: A pre-processing and feature extraction stage, which solves the problem of shared subspace distribution based on the random projection theory, to obtain low dimensional discriminative and reconstructive features; A dictionary learning and sparse coding stage, which uses the KSVD model to learn discriminative under or over dictionaries for sparse coding; Finally a classification stage, which uses a SVM classifier for facial expressions recognition. Our main concern is to be able to recognize non-basic affective states and non-acted expressions. Extensive experiments on the JAFFE static acted facial expressions database but also on the DynEmo dynamic spontaneous facial expressions database exhibit very good recognition rates.

Keywords: dictionary learning, random projection, pose and spontaneous facial expression, sparse representation

Procedia PDF Downloads 308

Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

Abstract:

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

Procedia PDF Downloads 140

Authors: Zukhrof Romadhon, Nani Kurniati

Abstract:

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

Procedia PDF Downloads 65

Authors: Vani Singhal, Jitendra Parmar, Satyendra Singh Chouhan

Abstract:

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

Procedia PDF Downloads 173

Authors: Grzegorz Sierpiński, Ireneusz Celiński, Marcin Staniek

Abstract:

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

Procedia PDF Downloads 412

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

Procedia PDF Downloads 42

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 86