Search results for: texture features.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4262

Search results for: texture features.

2402 Ensemble-Based SVM Classification Approach for miRNA Prediction

Authors: Sondos M. Hammad, Sherin M. ElGokhy, Mahmoud M. Fahmy, Elsayed A. Sallam

Abstract:

In this paper, an ensemble-based Support Vector Machine (SVM) classification approach is proposed. It is used for miRNA prediction. Three problems, commonly associated with previous approaches, are alleviated. These problems arise due to impose assumptions on the secondary structural of premiRNA, imbalance between the numbers of the laboratory checked miRNAs and the pseudo-hairpins, and finally using a training data set that does not consider all the varieties of samples in different species. We aggregate the predicted outputs of three well-known SVM classifiers; namely, Triplet-SVM, Virgo and Mirident, weighted by their variant features without any structural assumptions. An additional SVM layer is used in aggregating the final output. The proposed approach is trained and then tested with balanced data sets. The results of the proposed approach outperform the three base classifiers. Improved values for the metrics of 88.88% f-score, 92.73% accuracy, 90.64% precision, 96.64% specificity, 87.2% sensitivity, and the area under the ROC curve is 0.91 are achieved.

Keywords: MiRNAs, SVM classification, ensemble algorithm, assumption problem, imbalance data

Procedia PDF Downloads 343
2401 Fuels and Platform Chemicals Production from Lignocellulosic Biomass: Current Status and Future Prospects

Authors: Chandan Kundu, Sankar Bhattacharya

Abstract:

A significant disadvantage of fossil fuel energy production is the considerable amount of carbon dioxide (CO₂) released, which is one of the contributors to climate change. Apart from environmental concerns, changing fossil fuel prices have pushed society gradually towards renewable energy sources in recent years. Biomass is a plentiful and renewable resource and a source of carbon. Recent years have seen increased research interest in generating fuels and chemicals from biomass. Unlike fossil-based resources, biomass is composed of lignocellulosic material, which does not contribute to the increase in atmospheric CO₂ over a longer term. These considerations contribute to the current move of the chemical industry from non-renewable feedstock to renewable biomass. This presentation focuses on generating bio-oil and two major platform chemicals that can potentially improve the environment. Thermochemical processes such as pyrolysis are considered viable methods for producing bio-oil and biomass-based platform chemicals. Fluidized bed reactors, on the other hand, are known to boost bio-oil yields during pyrolysis due to their superior mixing and heat transfer features, as well as their scalability. This review and the associated experimental work are focused on the thermochemical conversion of biomass to bio-oil and two high-value platform chemicals, Levoglucosenone (LGO) and 5-Chloromethyl furfural (5-CMF), in a fluidized bed reactor. These two active molecules with distinct features can potentially be useful monomers in the chemical and pharmaceutical industries since they are well adapted to the manufacture of biologically active products. This process took several meticulous steps. To begin, the biomass was delignified using a peracetic acid pretreatment to remove lignin. Because of its complicated structure, biomass must be pretreated to remove the lignin, increasing access to the carbohydrate components and converting them to platform chemicals. The biomass was then characterized by Thermogravimetric analysis, Synchrotron-based THz spectroscopy, and in-situ DRIFTS in the laboratory. Based on the results, a continuous-feeding fluidized bed reactor system was constructed to generate platform chemicals from pretreated biomass using hydrogen chloride acid-gas as a catalyst. The procedure also yields biochar, which has a number of potential applications, including soil remediation, wastewater treatment, electrode production, and energy resource utilization. Consequently, this research also includes a preliminary experimental evaluation of the biochar's prospective applications. The biochar obtained was evaluated for its CO₂ and steam reactivity. The outline of the presentation will comprise the following: Biomass pretreatment for effective delignification Mechanistic study of the thermal and thermochemical conversion of biomass Thermochemical conversion of untreated and pretreated biomass in the presence of an acid catalyst to produce LGO and CMF A thermo-catalytic process for the production of LGO and 5-CMF in a continuously-fed fluidized bed reactor and efficient separation of chemicals Use of biochar generated from the platform chemicals production through gasification

Keywords: biomass, pretreatment, pyrolysis, levoglucosenone

Procedia PDF Downloads 131
2400 Development of Extruded Prawn Snack Using Prawn Flavor Powder from Prawn Head Waste

Authors: S. K. Sharma, P. Kumar, Pratibha Singh

Abstract:

Consumption of SNACK is growing its popularity every day in India and a broad range of these items are available in the market. The end user interest in ready-to-eat snack foods is constantly growing mainly due to their ease, ample accessibility, appearance, taste and texture. Food extrusion has been practiced for over fifty years. Its role was initially limited to mixing and forming cereal products. Although thermoplastic extrusion has been successful for starch products, extrusion of proteins has achieved only limited success. In this study, value-added extruded prawn product was prepared with prawn flavor powder and corn flour using a twin-screw extruder. Prawn flavor concentrates prepared from fresh prawn head (Solenocera indica). To prepare flavor concentrate prawn head washed with potable water and blended with 200ml 3% salt solution per 250gm head weight to make the slurry, which was further put in muslin cloth and boiled with salt and starch solution for 10 minutes, cooled to room temperature and filtered, starch added to the filtrate and made into powder in an electrically drier at 43-450c. The mixture was passed through the twin-screw extruder (co-rotating twin screw extruder - basic technology Pvt. Ltd., Kolkata) which was operated at a particular speed of rotation, die diameter, temperature, moisture, and fish powder concentration. Many trial runs were conducted to set up the process variables. The different extrudes produced after each trail were examined for the quality and characteristics. The effect of temperature, moisture, screw speed, protein, fat, ash and thiobarbituric acid (TBA) number and expansion ratio were studied. In all the four trials, moisture, temperature, speed and die diameter used was 20%, 100°C, 350 rpm and 4 mm, respectively. The ratio of prawn powder and cornstarch used in different trials ranged between 2:98 and 10:90. The storage characteristics of the final product were studied using three different types of packaging under nitrogen flushing, i.e. a- 12-pm polyester, 12-pm metalized polyester, 60-11m polyethylene (metalized polyester a), b- 12-11m metalized polyester, 37.5-11m polyethylene (metalized polyester b), c- 12-11m polyethylene, 9-11m aluminium foil, 37.5-11m polyethylene (aluminium foil). The organoleptic analysis was carried out on a 9-point hedonic scale. The study revealed that the fried product packed in aluminum foil under nitrogen flushing would remain acceptable for more than three months.

Keywords: extruded product, prawn flavor, twin-screw extruder, storage characteristics

Procedia PDF Downloads 137
2399 Geometric Continuity in the Form of Iranian Domes, Study of Prominent Safavid and Sasanian Domes

Authors: Nima Valibeig, Haniyeh Mohammadi, Neda Sadat Abdelahi

Abstract:

Persian domes follow different forms depending on the materials used to construct and other factors. One of the factors that shape the form of a dome is the geometric proportion used in the drawing and construction of the dome. Some commonly used proportions are revealed by analysing the shapes and geometric ratio of the monuments’ domes. The proportions are achieved by the proficiency of the skilled architects of the buildings. These proportions can be used to reconstruct damaged parts of the historical monuments. Most of the research on domes is about the historical or stability features of domes, and less attention is made to the geometric system in domes. Therefore, in this study, we study the explicit and implicit geometric proportions in Iranian dome structures for the first time. The study is done based on a literature review and field survey. This research reveals that the permanent geometric rules are perfectly used in the design and construction of the prominent domes.

Keywords: geometry in architecture, architectural proportions, prominent domes, iranian golden ratio, geometric proportion

Procedia PDF Downloads 276
2398 Blockchain Technology in Supply Chain Management: A Systematic Review And Meta-Analysis

Authors: Mohammad Yousuf Khan, Bhavya Alankar

Abstract:

Blockchain is a promising technology with its features such as immutability and decentralized database. It has applications in various fields such as pharmaceutical, finance, & the food industry. At the core of its heart lies its feature, traceability which is the most desired key in supply chains. However, supply chains have always been hit rock bottom by scandals and controversies. In this review paper, we have explored the advancement and research gaps of blockchain technology (BT) in supply chain management (SCM). We have used the Prisma framework for systematic literature review (SLR) and included a minuscule amount of grey literature to reduce publication bias. We found that supply chain traceability and transparency is the most researched objective in SCM. There was hardly any research in supply chain resilience. Further, we found that 40 % of the papers were application based. Most articles have focused on the advantages of BT, rather than analyzing it critically. This study will help identify gaps and suitable actions to be followed for an efficient implementation of BT in SCM.

Keywords: blockchain technology, supply chain management, supply chain transparency, supply chain resilience

Procedia PDF Downloads 155
2397 Factors Impacting Shopping Behavior for Luxury Fashion Brands: A Case of National Capital Region in India

Authors: Manoj Kumar, Preeti Goel

Abstract:

National Capital Region of India is one of the most populous urban agglomerations in the world. This region has residents from all the parts of India, and their shopping behaviors are quite different. The region also has the substantial population of people from other countries. Due to high purchasing power of a large number of people, NCR is one the major markets for luxury fashion brands. Marketers of luxury fashion brands keep on adding innovative features to their products to attract the buyers. This research is an attempt to understand the major factors which impact the brand selection for these brands and other buying decisions like purchasing time and location. The research is based on primary data collected from potential buyers of luxury fashion brands and the people involved in the marketing of these brands in various roles. The research has tried to identify the relative strength of various factors on the shopping behavior for these brands.

Keywords: luxury brands, fashion, shopping, National Capital Region (NCR)

Procedia PDF Downloads 405
2396 Quality Characteristics of Road Runoff in Coastal Zones: A Case Study in A25 Highway, Portugal

Authors: Pedro B. Antunes, Paulo J. Ramísio

Abstract:

Road runoff is a linear source of diffuse pollution that can cause significant environmental impacts. During rainfall events, pollutants from both stationary and mobile sources, which have accumulated on the road surface, are dragged through the superficial runoff. Road runoff in coastal zones may present high levels of salinity and chlorides due to the proximity of the sea and transported marine aerosols. Appearing to be correlated to this process, organic matter concentration may also be significant. This study assesses this phenomenon with the purpose of identifying the relationships between monitored water quality parameters and intrinsic site variables. To achieve this objective, an extensive monitoring program was conducted on a Portuguese coastal highway. The study included thirty rainfall events, in different weather, traffic and salt deposition conditions in a three years period. The evaluations of various water quality parameters were carried out in over 200 samples. In addition, the meteorological, hydrological and traffic parameters were continuously measured. The salt deposition rates (SDR) were determined by means of a wet candle device, which is an innovative feature of the monitoring program. The SDR, variable throughout the year, appears to show a high correlation with wind speed and direction, but mostly with wave propagation, so that it is lower in the summer, in spite of the favorable wind direction in the case study. The distance to the sea, topography, ground obstacles and the platform altitude seems to be also relevant. It was confirmed the high salinity in the runoff, increasing the concentration of the water quality parameters analyzed, with significant amounts of seawater features. In order to estimate the correlations and patterns of different water quality parameters and variables related to weather, road section and salt deposition, the study included exploratory data analysis using different techniques (e.g. Pearson correlation coefficients, Cluster Analysis and Principal Component Analysis), confirming some specific features of the investigated road runoff. Significant correlations among pollutants were observed. Organic matter was highlighted as very dependent of salinity. Indeed, data analysis showed that some important water quality parameters could be divided into two major clusters based on their correlations to salinity (including organic matter associated parameters) and total suspended solids (including some heavy metals). Furthermore, the concentrations of the most relevant pollutants seemed to be very dependent on some meteorological variables, particularly the duration of the antecedent dry period prior to each rainfall event and the average wind speed. Based on the results of a monitoring case study, in a coastal zone, it was proven that SDR, associated with the hydrological characteristics of road runoff, can contribute for a better knowledge of the runoff characteristics, and help to estimate the specific nature of the runoff and related water quality parameters.

Keywords: coastal zones, monitoring, road runoff pollution, salt deposition

Procedia PDF Downloads 235
2395 The Video Database for Teaching and Learning in Football Refereeing

Authors: M. Armenteros, A. Domínguez, M. Fernández, A. J. Benítez

Abstract:

The following paper describes the video database tool used by the Fédération Internationale de Football Association (FIFA) as part of the research project developed in collaboration with the Carlos III University of Madrid. The database project began in 2012, with the aim of creating an educational tool for the training of instructors, referees and assistant referees, and it has been used in all FUTURO III courses since 2013. The platform now contains 3,135 video clips of different match situations from FIFA competitions. It has 1,835 users (FIFA instructors, referees and assistant referees). In this work, the main features of the database are described, such as the use of a search tool and the creation of multimedia presentations and video quizzes. The database has been developed in MySQL, ActionScript, Ruby on Rails and HTML. This tool has been rated by users as "very good" in all courses, which prompt us to introduce it as an ideal tool for any other sport that requires the use of video analysis.

Keywords: assistants referees, cloud computing, e-learning, instructors, FIFA, referees, soccer, video database

Procedia PDF Downloads 434
2394 Artificial Intelligence in Duolingo

Authors: Elana Mahboub, Lamar Bakhurji, Hind Alhindi, Sara Alesayi

Abstract:

Duolingo is a revolutionary language learning platform that offers an interactive and accessible learning experience. Its gamified approach makes language learning engaging and enjoyable, with a diverse range of languages available. The platform's adaptive learning system tailors lessons to individual proficiency levels, ensuring a personalized and efficient learning journey. The incorporation of multimedia elements enhances the learning experience and promotes practical language application. Duolingo's success is attributed to its mobile accessibility, offering basic access to language courses for free, with optional premium features for those seeking additional resources. Research shows positive outcomes for users, and the app's global impact extends beyond individual learning to formal language education initiatives. Duolingo is a transformative force in language education, breaking down barriers and making language learning an attainable goal for millions worldwide.

Keywords: duolingo, artificial intelligence, artificial intelligence in duolingo, benefit of artificial intelligence

Procedia PDF Downloads 67
2393 The Cult of St. Agata as Cultural Mark of Heritage Community Resilience in Abruzzo (Italy, Central Apennine)

Authors: Carmen Soria

Abstract:

The aim of this paper is the study of the cultural and anthropological consequences of the historical natural disasters in Abruzzo (Italy, Central Apennine). These events have left cultural marks in local traditions as well as mythological stories, specific cults, or sanctuary areas in apotropaic function to prevent catastrophic events. Despite the difficult to find archaeological evidence of natural disasters, neverthless, the analisys of micro placenames, directly or indirectly related to such events, represents an integrated and interdisciplinary approach between seismology studies and landscape analysis. Toponymic data, indeed, highlight the strong relation between geomorphological features of areas affected by natural disasters and heritage community resilience, such as, for example, the cult of St. Agatha, widespread in the nearby of healing spring-water and ancient caves as a place of worship, in continuity with pagan rituals.

Keywords: abruzzo, heritage community resilience, seismic planames, St. agata

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2392 Studying the Role of Teachers’ Self-Acceptance in the Development of Their Self-Esteem and Efficacy Level: A Case Study Applied to 37 Teachers at the English Department, Sidi Bel Abbes, Algeria

Authors: Asmaa Baghli

Abstract:

Self-acceptance is one of the most pertinent notions that attracted the attention of many scholars. These latters believed that the sense of self-acceptance for people contributes in the emergence of their self-esteem and helps to improve their efficacy level. Simply defined, self-acceptance stands for the ability of the person to admire and accept herself and her potentials. This fact is believed to participate in the personal image creation depending on the qualities and features possessed. Hitherto, the following paper aims, first, to provide a brief and concise definition of self-acceptance, self-esteem and self-efficacy. It tries to explain the correlation between the three concepts along with its linkage to language teaching. Then, it examines teachers’ acceptance level and its influence on their classroom actions. For that purpose, the main methodology undertaken is the mixed method. That means the combination between both quantitative and qualitative research methods. The prime tools selected are a questionnaire and self-acceptance test for teachers. Finally, it suggests some techniques for developing teachers’ self-acceptance.

Keywords: competence, development, efficacy, Self-acceptance, self-esteem, teachers

Procedia PDF Downloads 133
2391 From the Recursive Definition of Refutability to the Invalidity of Gödel’s 1931 Incompleteness

Authors: Paola Cattabriga

Abstract:

According to Gödel’s first incompleteness argument it is possible to construct a formally undecidable proposition in Principia mathematica, a statement that, although true, turns out to be neither provable nor refutable for the system, making therefore incomplete any formal system suitable for the arithmetic of integers. Its features and limitation effects are today widespread basics throughout whole scientific thought. This article brings Gödel’s achievement into question by the definition of the refutability predicate as a number-theoretical statement. We develop proof of invalidity of Theorem VI in Gödel’s 1931, the so-called Gödel’s first incompleteness theorem, in two steps: defining refutability within the same recursive status as provability and showing that as a consequence propositions (15) and (16), derived from definition 8.1 in Gödel’s 1931, are false and unacceptable for the system. The achievement of their falsity blocks the derivation of Theorem VI, which turns out to be therefore invalid, together with all the depending theorems. This article opens up thus new perspectives for mathematical research and for the overall scientific reasoning.

Keywords: Gödel numbering, incompleteness, provability predicate, refutability predicate

Procedia PDF Downloads 185
2390 The Study of Fine and Nanoscale Gold in the Ores of Primary Deposits and Gold-Bearing Placers of Kazakhstan

Authors: G. Omarova, S. Assubayeva, S. Tugambay, K. Bulegenov

Abstract:

The article discusses the problem of developing a methodology for studying thin and nanoscale gold in ores and placers of primary deposits, which will allow us to develop schemes for revealing dispersed gold inclusions and thus improve its recovery rate to increase the gold reserves of the Republic of Kazakhstan. The type of studied gold, is characterized by a number of features. In connection with this, the conditions of its concentration and distribution in ore bodies and formations, as well as the possibility of reliably determining it by "traditional" methods, differ significantly from that of fine gold (less than 0.25 microns) and even more so from that of larger grains. The mineral composition of rocks (metasomatites) and gold ore and the mineralization associated with them was studied in detail on the Kalba ore field in Kazakhstan. Mineralized zones were identified and samples were taken from them for analytical studies. The research revealed paragenetic relationships of newly formed mineral formations at the nanoscale, which makes it possible to clarify the conditions for formation of deposits with a particular type of mineralization. This will provide significant assistance in developing a scheme for study. Typomorphic features of gold were revealed, and mechanisms of formation and aggregation of gold nanoparticles were proposed. The presence of a large number of particles isolated at the laboratory stage from concentrates of gravitational enrichment can serve as an indicator of the presence of even smaller particles in the object. Even the most advanced devices based on gravitational methods for gold concentration provide extraction of metal at a level of around 50%, while pulverized metal is extracted much worse, and gold of less than 1 micron size is extracted at only a few percent. Therefore, when particles of gold smaller than 10 microns are detected, their actual numbers may be significantly higher than expected. In particular, at the studied sites, enrichment of slurry and samples with volumes up to 1 m³ was carried out using a screw lock or separator to produce a final concentrate weighing up to several kilograms. Free gold particles were extracted from the concentrates in the laboratory using a number of processes (magnetic and electromagnetic separation, washing with bromoform in a cup to obtain an ultracontentrate, etc.) and examined under electron microscopes to investigate the nature of their surface and chemical composition. The main result of the study was the detection of gold nanoparticles located on the surface of loose metal grains. The most characteristic forms of gold secretions are individual nanoparticles and aggregates of different configurations. Sometimes, aggregates form solid dense films, deposits, and crusts, all of which are confined to the negative forms of the nano- and microrelief on the surfaces of golden. The results will provide significant knowledge about the prevalence and conditions for the distribution of fine and nanoscale gold in Kazakhstan deposits, as well as the development of methods for studying it, which will minimize losses of this type of gold during extraction.

Keywords: electron microscopy, microminerology, placers, thin and nanoscale gold

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2389 Evaluation of Neighbourhood Characteristics and Active Transport Mode Choice

Authors: Tayebeh Saghapour, Sara Moridpour, Russell George Thompson

Abstract:

One of the common aims of transport policy makers is to switch people’s travel to active transport. For this purpose, a variety of transport goals and investments should be programmed to increase the propensity towards active transport mode choice. This paper aims to investigate whether built environment features in neighbourhoods could enhance the odds of active transportation. The present study introduces an index measuring public transport accessibility (PTAI), and a walkability index along with socioeconomic variables to investigate mode choice behaviour. Using travel behaviour data, an ordered logit regression model is applied to examine the impacts of explanatory variables on walking trips. The findings indicated that high rates of active travel are consistently associated with higher levels of walking and public transport accessibility.

Keywords: active transport, public transport accessibility, walkability, ordered logit model

Procedia PDF Downloads 347
2388 An Efficient Activated Carbon for Copper (II) Adsorption Synthesized from Indian Gooseberry Seed Shells

Authors: Somen Mondal, Subrata Kumar Majumder

Abstract:

Removal of metal pollutants by efficient activated carbon is challenging research in the present-day scenario. In the present study, the characteristic features of an efficient activated carbon (AC) synthesized from Indian gooseberry seed shells for the copper (II) adsorption are reported. A three-step chemical activation method consisting of the impregnation, carbonization and subsequent activation is used to produce the activated carbon. The copper adsorption kinetics and isotherms onto the activated carbon were analyzed. As per present investigation, Indian gooseberry seed shells showed the BET surface area of 1359 m²/g. The maximum adsorptivity of the activated carbon at a pH value of 9.52 was found to be 44.84 mg/g at 30°C. The adsorption process followed the pseudo-second-order kinetic model along with the Langmuir adsorption isotherm. This AC could be used as a favorable and cost-effective copper (II) adsorbent in wastewater treatment to remove the metal contaminants.

Keywords: activated carbon, adsorption isotherm, kinetic model, characterization

Procedia PDF Downloads 157
2387 Seismic Perimeter Surveillance System (Virtual Fence) for Threat Detection and Characterization Using Multiple ML Based Trained Models in Weighted Ensemble Voting

Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

Abstract:

Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

Procedia PDF Downloads 74
2386 Drone Classification Using Classification Methods Using Conventional Model With Embedded Audio-Visual Features

Authors: Hrishi Rakshit, Pooneh Bagheri Zadeh

Abstract:

This paper investigates the performance of drone classification methods using conventional DCNN with different hyperparameters, when additional drone audio data is embedded in the dataset for training and further classification. In this paper, first a custom dataset is created using different images of drones from University of South California (USC) datasets and Leeds Beckett university datasets with embedded drone audio signal. The three well-known DCNN architectures namely, Resnet50, Darknet53 and Shufflenet are employed over the created dataset tuning their hyperparameters such as, learning rates, maximum epochs, Mini Batch size with different optimizers. Precision-Recall curves and F1 Scores-Threshold curves are used to evaluate the performance of the named classification algorithms. Experimental results show that Resnet50 has the highest efficiency compared to other DCNN methods.

Keywords: drone classifications, deep convolutional neural network, hyperparameters, drone audio signal

Procedia PDF Downloads 99
2385 The Association between Attachment Styles, Satisfaction of Life, Alexithymia, and Psychological Resilience: The Mediational Role of Self-Esteem

Authors: Zahide Tepeli Temiz, Itir Tari Comert

Abstract:

Attachment patterns based on early emotional interactions between infant and primary caregiver continue to be influential in adult life, in terms of mental health and behaviors of individuals. Several studies reveal that infant-caregiver relationships have impressed the affect regulation, coping with stressful and negative situations, general satisfaction of life, and self image in adulthood, besides the attachment styles. The present study aims to examine the relationships between university students’ attachment style and their self-esteem, alexithymic features, satisfaction of life, and level of resilience. In line with this aim, the hypothesis of the prediction of attachment styles (anxious and avoidant) over life satisfaction, self-esteem, alexithymia, and psychological resilience was tested. Additionally, in this study Structural Equational Modeling was conducted to investigate the mediational role of self-esteem in the relationship between attachment styles and alexithymia, life satisfaction, and resilience. This model was examined with path analysis. The sample of the research consists of 425 university students who take education from several region of Turkey. The participants who sign the informed consent completed the Demographic Information Form, Experiences in Close Relationships-Revised, Rosenberg Self-Esteem Scale, The Satisfaction with Life Scale, Toronto Alexithymia Scale, and Resilience Scale for Adults. According to results, anxious, and avoidant dimensions of insecure attachment predicted the self-esteem score and alexithymia in positive direction. On the other hand, these dimensions of attachment predicted life satisfaction in negative direction. The results of linear regression analysis indicated that anxious and avoidant attachment styles didn’t predict the resilience. This result doesn’t support the theory and research indicating the relationship between attachment style and psychological resilience. The results of path analysis revealed the mediational role self esteem in the relation between anxious, and avoidant attachment styles and life satisfaction. In addition, SEM analysis indicated the indirect effect of attachment styles over alexithymia and resilience besides their direct effect. These findings support the hypothesis of this research relation to mediating role of self-esteem. Attachment theorists suggest that early attachment experiences, including supportive and responsive family interactions, have an effect on resilience to harmful situations in adult life, ability to identify, describe, and regulate emotions and also general satisfaction with life. Several studies examining the relationship between attachment styles and life satisfaction, alexithymia, and psychological resilience draw attention to mediational role of self-esteem. Results of this study support the theory of attachment patterns with the mediation of self-image influence the emotional, cognitive, and behavioral regulation of person throughout the adulthood. Therefore, it is thought that any intervention intended for recovery in attachment relationship will increase the self-esteem, life satisfaction, and resilience level, on the one side, decrease the alexithymic features, on the other side.

Keywords: alexithymia, anxious attachment, avoidant attachment, life satisfaction, path analysis, resilience, self-esteem, structural equation

Procedia PDF Downloads 190
2384 Syndromic Surveillance Framework Using Tweets Data Analytics

Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

Abstract:

Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

Procedia PDF Downloads 107
2383 Computer Aided Engineering Optimization of Synchronous Reluctance Motor and Vibro-Acoustic Analysis for Lift Systems

Authors: Ezio Bassi, Francesco Vercesi, Francesco Benzi

Abstract:

The aim of this study is to evaluate the potentiality of synchronous reluctance motors for lift systems by also evaluating the vibroacoustic behaviour of the motor. Two types of synchronous machines are designed, analysed, and compared with an equivalent induction motor, which is the more common solution in such gearbox applications. The machines' performance are further improved with optimization procedures based on multiobjective optimization genetic algorithm (MOGA). The difference between the two synchronous motors consists in the rotor geometry; a symmetric and an asymmetric rotor design were investigated. The evaluation of the vibroacoustic performance has been conducted with a multi-variable model and finite element software taking into account electromagnetic, mechanical, and thermal features of the motor, therefore carrying out a multi-physics analysis of the electrical machine.

Keywords: synchronous reluctance motor, vibro-acoustic, lift systems, genetic algorithm

Procedia PDF Downloads 172
2382 Metric Suite for Schema Evolution of a Relational Database

Authors: S. Ravichandra, D. V. L. N. Somayajulu

Abstract:

Requirement of stakeholders for adding more details to the database is the main cause of the schema evolution in the relational database. Further, this schema evolution causes the instability to the database. Hence, it is aimed to define a metric suite for schema evolution of a relational database. The metric suite will calculate the metrics based on the features of the database, analyse the queries on the database and measures the coupling, cohesion and component dependencies of the schema for existing and evolved versions of the database. This metric suite will also provide an indicator for the problems related to the stability and usability of the evolved database. The degree of change in the schema of a database is presented in the forms of graphs that acts as an indicator and also provides the relations between various parameters (metrics) related to the database architecture. The acquired information is used to defend and improve the stability of database architecture. The challenges arise in incorporating these metrics with varying parameters for formulating a suitable metric suite are discussed. To validate the proposed metric suite, an experimentation has been performed on publicly available datasets.

Keywords: cohesion, coupling, entropy, metric suite, schema evolution

Procedia PDF Downloads 446
2381 Geospatial Data Complexity in Electronic Airport Layout Plan

Authors: Shyam Parhi

Abstract:

Airports GIS program collects Airports data, validate and verify it, and stores it in specific database. Airports GIS allows authorized users to submit changes to airport data. The verified data is used to develop several engineering applications. One of these applications is electronic Airport Layout Plan (eALP) whose primary aim is to move from paper to digital form of ALP. The first phase of development of eALP was completed recently and it was tested for a few pilot program airports across different regions. We conducted gap analysis and noticed that a lot of development work is needed to fine tune at least six mandatory sheets of eALP. It is important to note that significant amount of programming is needed to move from out-of-box ArcGIS to a much customized ArcGIS which will be discussed. The ArcGIS viewer capability to display essential features like runway or taxiway or the perpendicular distance between them will be discussed. An enterprise level workflow which incorporates coordination process among different lines of business will be highlighted.

Keywords: geospatial data, geology, geographic information systems, aviation

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2380 Printed Thai Character Recognition Using Particle Swarm Optimization Algorithm

Authors: Phawin Sangsuvan, Chutimet Srinilta

Abstract:

This Paper presents the applications of Particle Swarm Optimization (PSO) Method for Thai optical character recognition (OCR). OCR consists of the pre-processing, character recognition and post-processing. Before enter into recognition process. The Character must be “Prepped” by pre-processing process. The PSO is an optimization method that belongs to the swarm intelligence family based on the imitation of social behavior patterns of animals. Route of each particle is determined by an individual data among neighborhood particles. The interaction of the particles with neighbors is the advantage of Particle Swarm to determine the best solution. So PSO is interested by a lot of researchers in many difficult problems including character recognition. As the previous this research used a Projection Histogram to extract printed digits features and defined the simple Fitness Function for PSO. The results reveal that PSO gives 67.73% for testing dataset. So in the future there can be explored enhancement the better performance of PSO with improve the Fitness Function.

Keywords: character recognition, histogram projection, particle swarm optimization, pattern recognition techniques

Procedia PDF Downloads 467
2379 Modeling of a Stewart Platform for Analyzing One Directional Dynamics for Spacecraft Docking Operations

Authors: Leonardo Herrera, Shield B. Lin, Stephen J. Montgomery-Smith, Ziraguen O. Williams

Abstract:

A one-directional dynamic model of a Stewart Platform was developed to assist NASA in analyzing the dynamic response in spacecraft docking operations. A simplified mechanical drawing was created, capturing the physical structure's main features. A simplified schematic diagram was developed into a lumped mass model from the mechanical drawing. Three differential equations were derived according to the schematic diagram. A Simulink diagram was created using MATLAB to represent the three equations. System parameters, including spring constants and masses, are derived in detail from the physical system. The model can be used for further analysis via computer simulation in predicting dynamic response in its main docking direction, i.e., up-and-down motion.

Keywords: stewart platform, docking operation, spacecraft, spring constant

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2378 Automatic Facial Skin Segmentation Using Possibilistic C-Means Algorithm for Evaluation of Facial Surgeries

Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammad Hossein Sedaaghi

Abstract:

Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.

Keywords: facial image, segmentation, PCM, FCM, skin error, facial surgery

Procedia PDF Downloads 581
2377 Dissolved Oxygen Prediction Using Support Vector Machine

Authors: Sorayya Malek, Mogeeb Mosleh, Sharifah M. Syed

Abstract:

In this study, Support Vector Machine (SVM) technique was applied to predict the dichotomized value of Dissolved oxygen (DO) from two freshwater lakes namely Chini and Bera Lake (Malaysia). Data sample contained 11 parameters for water quality features from year 2005 until 2009. All data parameters were used to predicate the dissolved oxygen concentration which was dichotomized into 3 different levels (High, Medium, and Low). The input parameters were ranked, and forward selection method was applied to determine the optimum parameters that yield the lowest errors, and highest accuracy. Initial results showed that pH, water temperature, and conductivity are the most important parameters that significantly affect the predication of DO. Then, SVM model was applied using the Anova kernel with those parameters yielded 74% accuracy rate. We concluded that using SVM models to predicate the DO is feasible, and using dichotomized value of DO yields higher prediction accuracy than using precise DO value.

Keywords: dissolved oxygen, water quality, predication DO, support vector machine

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2376 Streamlines: Paths of Fluid Flow through Sandstone Samples Based on Computed Microtomography

Authors: Ł. Kaczmarek, T. Wejrzanowski, M. Maksimczuk

Abstract:

The study presents the use of the numerical calculations based on high-resolution computed microtomography in analysis of fluid flow through Miocene sandstones. Therefore, the permeability studies of rocks were performed. Miocene samples were taken from well S-3, located in the eastern part of the Carpathian Foredeep. For aforementioned analysis, two series of X-ray irradiation were performed. The first set of samples was selected to obtain the spatial distribution of grains and pores. At this stage of the study length of voxel side amounted 27 microns. The next set of X-ray irradation enabled recognition of microstructural components as well as petrophysical features. The length of voxel side in this stage was up to 2 µm. Based on this study, the samples were broken down into two distinct groups. The first one represents conventional reservoir deposits, in opposite to second one - unconventional type. Appropriate identification of petrophysical parameters such as porosity and permeability of the formation is a key element for optimization of the reservoir development.

Keywords: grains, permeability, pores, pressure distribution

Procedia PDF Downloads 246
2375 Proximate Composition and Sensory Properties of Complementary Food from Fermented Acha (Digitaria exilis), Soybean and Orange-Flesh Sweet Potato Blends

Authors: N. C. Okoronkwo, I. E. Mbaeyi-Nwaoha, C. P. Agbata

Abstract:

Childhood malnutrition is one of the most persistent public health problems throughout developing countries, including Nigeria. Demographic and Health survey data from twenty-one developing countries indicated that poor complementary feeding of children aged 6- 23 months contributes to negative growth trends. To reduce malnutrition among children in the society, formulation of complimentary food rich in essential nutrient for optimum growth and development of infants is essential. This study focused on the evaluation of complementary food produced by solid-state fermentation of Acha and Soybean using Rhizopus oligosporus (2710) and Orange-fleshed sweet potatoes (OFSP) using Lactobacillus planterum (B-41621). The raw materials were soaked separately, each in four volumes of 0.9M acetic acid for 16 hours, rinsed with clean water, steam cooked and cooled. Solid-state fermentation (SSF) was carried out by inoculating Acha and Soybean with spore suspension (1x 10⁶spores/ml) of Rhizopus oligosporus (2710) and OFSP with spore suspension (1x 106spores/ml) of Lactobacillus planterum (B-41621). Fermentation which lasted for 72hours was carried out with 24hours sampling. The samples were blended in the following ratios: Acha and soybean 100: 100 (AS), Acha/soybean and OFSP 50: 50(ASO), made into gruel and compared with a commercial infant formula (Cerelac) which served as the control (CTRL). The samples were analyzed for proximate composition using AOAC methods and sensory attributes using a hedonic scale. Results showed that moisture, crude protein, fibre and ash content increased significantly (p<0.05) as fermentation progressed, while carbohydrate and fat content decreased. The protein, moisture, fibre and ash content ranged from 17.10-19.02%, 54.97-56.27%, 7.08-7.60% and2.09-2.38%, respectively, while carbohydrate and fat content ranged from 12.95-10.21% and 5.81-4.52%, respectively. In sensory scores, there were no significant (p>0.05) difference between the average mean scores of colours, texture and consistency of the samples. The sensory score for the overall acceptability ranged from 6.20-7.80. Sample CTRL had the highest score, while sample ASO had the least score. There was no significant (p>0.05) difference between samples CTRL and AS. Solid-state fermentation improved the nutritional content and flavour of the developed complementary food, which is needed for infant growth and development.

Keywords: Complementary food, malnutrition, proximate composition, solid-state fermentation

Procedia PDF Downloads 154
2374 Oath Taking-An Approach to Combating Criminality: Challenges and Implication to the Victim Centered Approach in Human Trafficking

Authors: Faith G. Ehiemua, Chandra E. Ulinfun

Abstract:

This work presents two approaches that use competing models to combat criminality in human trafficking. It argues that oath-taking is an approach used to combat and repress crime by natives of African descent. Therefore, certain value choices reflected explicitly or implicitly in its habitual functioning are features of crime control, a model of the criminal process used to repress and prevent crime. By pitting the approaches against each other, the work examines the utility of the purpose of each approach with the aim of assessing moral worthiness. The approaches adopted are descriptive, normative, and theoretical. The findings reveal that oath-taking is effective in human trafficking mainly because Africans believe that the African traditional system is efficient. However, the utilitarian ethical theory applied to the use of oath-taking in human trafficking shows oath-taking as protecting the interest of human traffickers against the general good of society.

Keywords: human rights, human trafficking, oath taking, utilitarianism, victim-centered approach

Procedia PDF Downloads 202
2373 Sentiment Analysis: Comparative Analysis of Multilingual Sentiment and Opinion Classification Techniques

Authors: Sannikumar Patel, Brian Nolan, Markus Hofmann, Philip Owende, Kunjan Patel

Abstract:

Sentiment analysis and opinion mining have become emerging topics of research in recent years but most of the work is focused on data in the English language. A comprehensive research and analysis are essential which considers multiple languages, machine translation techniques, and different classifiers. This paper presents, a comparative analysis of different approaches for multilingual sentiment analysis. These approaches are divided into two parts: one using classification of text without language translation and second using the translation of testing data to a target language, such as English, before classification. The presented research and results are useful for understanding whether machine translation should be used for multilingual sentiment analysis or building language specific sentiment classification systems is a better approach. The effects of language translation techniques, features, and accuracy of various classifiers for multilingual sentiment analysis is also discussed in this study.

Keywords: cross-language analysis, machine learning, machine translation, sentiment analysis

Procedia PDF Downloads 709