Search results for: online learning environment.
1229 UPPAAL-Based Design and Analysis of Intelligent Parking System
Authors: Abobaker M. Q. Farhan, Olof M. A. Saif
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The demand for parking spaces in urban areas, particularly in developing countries, has led to a significant issue in the absence of sufficient parking spaces in crowded areas, which results in daily traffic congestion as drivers search for parking. This not only affects the appearance of the city but also has indirect impacts on the economy, society, and environment. In response to these challenges, researchers from various countries have sought technical and intelligent solutions to mitigate the problem through the development of smart parking systems. This paper aims to analyze and design three models of parking lots, with a focus on parking time and security. The study used computer software and Uppaal tools to simulate the models and determine the best among them. The results and suggestions provided in the paper aim to reduce the parking problems and improve the overall efficiency and safety of the parking process. The conclusion of the study highlights the importance of utilizing advanced technology to address the pressing issue of insufficient parking spaces in urban areas.
Keywords: Preliminaries, system requirements, timed automata, uppaal.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1441228 Modern Detection and Description Methods for Natural Plants Recognition
Authors: Masoud Fathi Kazerouni, Jens Schlemper, Klaus-Dieter Kuhnert
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Green planet is one of the Earth’s names which is known as a terrestrial planet and also can be named the fifth largest planet of the solar system as another scientific interpretation. Plants do not have a constant and steady distribution all around the world, and even plant species’ variations are not the same in one specific region. Presence of plants is not only limited to one field like botany; they exist in different fields such as literature and mythology and they hold useful and inestimable historical records. No one can imagine the world without oxygen which is produced mostly by plants. Their influences become more manifest since no other live species can exist on earth without plants as they form the basic food staples too. Regulation of water cycle and oxygen production are the other roles of plants. The roles affect environment and climate. Plants are the main components of agricultural activities. Many countries benefit from these activities. Therefore, plants have impacts on political and economic situations and future of countries. Due to importance of plants and their roles, study of plants is essential in various fields. Consideration of their different applications leads to focus on details of them too. Automatic recognition of plants is a novel field to contribute other researches and future of studies. Moreover, plants can survive their life in different places and regions by means of adaptations. Therefore, adaptations are their special factors to help them in hard life situations. Weather condition is one of the parameters which affect plants life and their existence in one area. Recognition of plants in different weather conditions is a new window of research in the field. Only natural images are usable to consider weather conditions as new factors. Thus, it will be a generalized and useful system. In order to have a general system, distance from the camera to plants is considered as another factor. The other considered factor is change of light intensity in environment as it changes during the day. Adding these factors leads to a huge challenge to invent an accurate and secure system. Development of an efficient plant recognition system is essential and effective. One important component of plant is leaf which can be used to implement automatic systems for plant recognition without any human interface and interaction. Due to the nature of used images, characteristic investigation of plants is done. Leaves of plants are the first characteristics to select as trusty parts. Four different plant species are specified for the goal to classify them with an accurate system. The current paper is devoted to principal directions of the proposed methods and implemented system, image dataset, and results. The procedure of algorithm and classification is explained in details. First steps, feature detection and description of visual information, are outperformed by using Scale invariant feature transform (SIFT), HARRIS-SIFT, and FAST-SIFT methods. The accuracy of the implemented methods is computed. In addition to comparison, robustness and efficiency of results in different conditions are investigated and explained.
Keywords: SIFT combination, feature extraction, feature detection, natural images, natural plant recognition, HARRIS-SIFT, FAST-SIFT.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7291227 Selective Separation of Lead and Mercury Ions from Synthetic Produced Water via a Hollow Fiber Supported Liquid Membrane
Authors: S. Suren, U. Pancharoen
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A double module hollow fiber supported liquid membrane (HFSLM) was applied to selectively separate lead and mercury ions from dilute synthetic produced water. The experiments were investigated on several variables: types of extractants (D2EHPA, Cyanex 471, Aliquat 336, and TOA), concentration of the selected extractant and operating time. The results clearly showed that the double module HFSLM could selectively separate Pb(II) and Hg(II) in feed solution at a very low concentration to less than the regulatory discharge limit of 0.2 and 0.005 mg/L issued by the Ministry of Industry and the Ministry of Natural Resource Environment, Thailand. The highest extractions of lead and mercury ions from synthetic produced water were 96% and 100% using 0.03 M D2EHPA and 0.06 M Aliquat 336 as the extractant for the first and second modules.Keywords: Hollow fiber, Lead ions, Liquid membrane, Mercury ions, Selective separation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23341226 A Critical Review on the Development of a Theoretical Framework for Managing Environmental Impacts of Construction Project
Authors: Sami Mustafa M. E. Ahmed, Noor Amila Wan Abdullah Zawawi, Zulkipli B. Ghazali
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Construction industry is considered as one of the main contributor of natural resources depletion, responsible for high level pollution and it is one of the attributes that pose climate changes and other environmental threats. A lot of efforts had and have been done to reduce and control these impacts. Project Environmental Management (PEM) includes the processes required to ensure that the impacts of the project execution to the surrounding environment will remain within the limits stated in legal permits. The main aim of most of researches conducted managing Environmental Impacts (EI) is to protect earth planet from pollution. Those researches are presenting four major environmental elements; Environmental Management Systems (EMS), Environmental Design (ED), Environmental Planning (EP) and Environmental Impacts Assessments (EIA). Although everything has been said about environmental management for construction projects, but almost everything remains to be said and therefore to be explored or rediscovered because incontestably, almost everything remains to be done. This paper aimed at reviewing some of what has been said about PEM. Also one of its objectives is to explore and rediscover the whole view of managing the EI problems by proposing a framework that based on the relation between these environmental researches.
Keywords: Environmental planning, sustainable design, EIA and EMS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24191225 A Block Cipher for Resource-Constrained IoT Devices
Authors: Muhammad Rana, Quazi Mamun, Rafiqul Islam
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In the Internet of Things (IoT), many devices are connected and accumulate a sheer amount of data. These Internet-driven raw data need to be transferred securely to the end-users via dependable networks. Consequently, the challenges of IoT security in various IoT domains are paramount. Cryptography is being applied to secure the networks for authentication, confidentiality, data integrity and access control. However, due to the resource constraint properties of IoT devices, the conventional cipher may not be suitable in all IoT networks. This paper designs a robust and effective lightweight cipher to secure the IoT environment and meet the resource-constrained nature of IoT devices. We also propose a symmetric and block-cipher based lightweight cryptographic algorithm. The proposed algorithm increases the complexity of the block cipher, maintaining the lowest computational requirements possible. The proposed algorithm efficiently constructs the key register updating technique, reduces the number of encryption rounds, and adds a layer between the encryption and decryption processes.
Keywords: Internet of Things, IoT, cryptography block cipher, s-box, key management, IoT security.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5411224 Speech Intelligibility Improvement Using Variable Level Decomposition DWT
Authors: Samba Raju, Chiluveru, Manoj Tripathy
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Intelligibility is an essential characteristic of a speech signal, which is used to help in the understanding of information in speech signal. Background noise in the environment can deteriorate the intelligibility of a recorded speech. In this paper, we presented a simple variance subtracted - variable level discrete wavelet transform, which improve the intelligibility of speech. The proposed algorithm does not require an explicit estimation of noise, i.e., prior knowledge of the noise; hence, it is easy to implement, and it reduces the computational burden. The proposed algorithm decides a separate decomposition level for each frame based on signal dominant and dominant noise criteria. The performance of the proposed algorithm is evaluated with speech intelligibility measure (STOI), and results obtained are compared with Universal Discrete Wavelet Transform (DWT) thresholding and Minimum Mean Square Error (MMSE) methods. The experimental results revealed that the proposed scheme outperformed competing methodsKeywords: Discrete Wavelet Transform, speech intelligibility, STOI, standard deviation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6931223 Eco-Friendly Preservative Treated Bamboo Culm: Compressive Strength Analysis
Authors: Perminder JitKaur, Santosh Satya, K. K. Pant, S. N. Naik
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Bamboo is extensively used in construction industry. Low durability of bamboo due to fungus infestation and termites attack under storage puts certain constrains for it usage as modern structural material. Looking at many chemical formulations for bamboo treatment leading to severe harmful environment effects, research on eco-friendly preservatives for bamboo treatment has been initiated world-over. In the present studies, eco-friendly preservative for bamboo treatment has been developed. To validate its application for structural purposes, investigation of effect of treatment on compressive strength has been investigated. Neemoil (25%) integrated with copper naphthenate (0.3%) on dilution with kerosene oil impregnated into bamboo culm at 2 bar pressure, has shown weight loss of only 3.15% in soil block analysis method. The results from compressive strength analysis using HEICO Automatic Compression Testing Machine reveal that preservative treatment has not altered the structural properties of bamboo culms. Compressive strength of control (11.72 N/mm2) and above treated samples (11.71 N/mm2) was found to be comparable.
Keywords: Compressive strength, D. strictus bamboo, Ecofriendly treatment, neem oil.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34451222 Comparison of Hough Transform and Mean Shift Algorithm for Estimation of the Orientation Angle of Industrial Data Matrix Codes
Authors: Ion-Cosmin Dita, Vasile Gui, Franz Quint, Marius Otesteanu
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In automatic manufacturing and assembling of mechanical, electrical and electronic parts one needs to reliably identify the position of components and to extract the information of these components. Data Matrix Codes (DMC) are established by these days in many areas of industrial manufacturing thanks to their concentration of information on small spaces. In today’s usually order-related industry, where increased tracing requirements prevail, they offer further advantages over other identification systems. This underlines in an impressive way the necessity of a robust code reading system for detecting DMC on the components in factories. This paper compares two methods for estimating the angle of orientation of Data Matrix Codes: one method based on the Hough Transform and the other based on the Mean Shift Algorithm. We concentrate on Data Matrix Codes in industrial environment, punched, milled, lasered or etched on different materials in arbitrary orientation.
Keywords: Industrial data matrix code, Hough transform, mean shift.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13361221 A Study of Adaptive Fault Detection Method for GNSS Applications
Authors: Je Young Lee, Hee Sung Kim, Kwang Ho Choi, Joonhoo Lim, Sebum Chun, Hyung Keun Lee
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This study is purposed to develop an efficient fault detection method for Global Navigation Satellite Systems (GNSS) applications based on adaptive noise covariance estimation. Due to the dependence on radio frequency signals, GNSS measurements are dominated by systematic errors in receiver’s operating environment. In the proposed method, the pseudorange and carrier-phase measurement noise covariances are obtained at time propagations and measurement updates in process of Carrier-Smoothed Code (CSC) filtering, respectively. The test statistics for fault detection are generated by the estimated measurement noise covariances. To evaluate the fault detection capability, intentional faults were added to the filed-collected measurements. The experiment result shows that the proposed method is efficient in detecting unhealthy measurements and improves GNSS positioning accuracy against fault occurrences.
Keywords: Adaptive estimation, fault detection, GNSS, residual.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25551220 Measuring the Cognitive Abilities of Teenage Basketball Players in Singapore
Authors: Stella Y. Ng, John B. Peacock, Kay Chuan Tan
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This paper discusses the use of a computerized test to measure the decision-making abilities of teenage basketball players in Singapore. There are five sections in this test – Competitive state anxiety inventory-2 (CSAI-2) questionnaire (measures player’s cognitive anxiety, somatic anxiety and self-confidence), Corsi block-tapping task (measures player’s short-term spatial memory), situation awareness global assessment technique (SAGAT) (measures players’ situation awareness in a basketball game), multiple choice questions on basketball knowledge (measures players’ knowledge of basketball rules and concepts), and lastly, a learning test that requires participants to recall and recognize basketball set plays (measures player’s ability to learn and recognize set plays). A total of 25 basketball players, aged 14 to 16 years old, from three secondary school teams participated in this experiment. The results that these basketball players obtained from this cognitive test were then used to compare with their physical fitness and basketball performance.
Keywords: Basketball, cognitive abilities, computerized test, decision-making.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24021219 The Use of Plant-Based Natural Fibers in Reinforced Cement Composites
Authors: N. AlShaya, R. Alhomidan, S. Alromizan, W. Labib
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Plant-based natural fibers are used more increasingly in construction materials. It is done to reduce the pressure on the built environment, which has been increased dramatically due to the increases world population and their needs. Plant-based natural fibers are abundant in many countries. Despite the low-cost of such environmental friendly renewable material, it has the ability to enhance the mechanical properties of construction materials. This paper presents an extensive discussion on the use of plant-based natural fibers as reinforcement for cement-based composites, with a particular emphasis upon fiber types; fiber characteristics, and fiber-cement composites performance. It also covers a thorough overview on the main factors, affecting the properties of plant-based natural fiber cement composite in it fresh and hardened state. The feasibility of using plant-based natural fibers in producing various construction materials; such as, mud bricks and blocks is investigated. In addition, other applications of using such fibers as internal curing agents as well as durability enhancer are also discussed. Finally, recommendation for possible future work in this area is presented.
Keywords: Cement composites, plant fibers, strength, mechanical properties.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21721218 Understanding Evolutionary Algorithms through Interactive Graphical Applications
Authors: Javier Barrachina, Piedad Garrido, Manuel Fogue, Julio A. Sanguesa, Francisco J. Martinez
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It is very common to observe, especially in Computer Science studies that students have difficulties to correctly understand how some mechanisms based on Artificial Intelligence work. In addition, the scope and limitations of most of these mechanisms are usually presented by professors only in a theoretical way, which does not help students to understand them adequately. In this work, we focus on the problems found when teaching Evolutionary Algorithms (EAs), which imitate the principles of natural evolution, as a method to solve parameter optimization problems. Although this kind of algorithms can be very powerful to solve relatively complex problems, students often have difficulties to understand how they work, and how to apply them to solve problems in real cases. In this paper, we present two interactive graphical applications which have been specially designed with the aim of making Evolutionary Algorithms easy to be understood by students. Specifically, we present: (i) TSPS, an application able to solve the ”Traveling Salesman Problem”, and (ii) FotEvol, an application able to reconstruct a given image by using Evolution Strategies. The main objective is that students learn how these techniques can be implemented, and the great possibilities they offer.Keywords: Education, evolutionary algorithms, evolution strategies, interactive learning applications.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10641217 A Real-time 4M Collecting Method for Production Information System
Authors: Seung Woo Lee, So Jeong Nam, Jai-Kyung Lee
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It can be said that the business sector is faced with a range of challenges–a rapidly changing business environment, an increase and diversification of customers- demands and the consequent need for quick response–for having in place flexible management and production info systems. As a matter of fact, many manufacturers have adopted production info management systems such as MES and ERP. Nevertheless, managers are having difficulties obtaining ever-changing production process information in real time, or responding quickly to any change in production related needs on the basis of such information. This is because they rely on poor production info systems which are not capable of providing real-time factory settings. If the manufacturer doesn-t have a capacity for collecting or digitalizing the 4 Ms (Man, Machine, Material, Method), which are resources for production, on a real time basis, it might to difficult to effectively maintain the information on production process. In this regard, this paper will introduce some new alternatives to the existing methods of collecting the 4 Ms in real time, which are currently comprise the production field.
Keywords: 4M, Acquisition of Data on shop-floor, Real-time machine interface
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 43331216 Ground Heat Exchanger Modeling Developed for Energy Flows of an Incompressible Fluid
Authors: Paul Christodoulides, Georgios Florides, Panayiotis Pouloupatis, Vassilios Messaritis, Lazaros Lazari
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Ground-source heat pumps achieve higher efficiencies than conventional air-source heat pumps because they exchange heat with the ground that is cooler in summer and hotter in winter than the air environment. Earth heat exchangers are essential parts of the ground-source heat pumps and the accurate prediction of their performance is of fundamental importance. This paper presents the development and validation of a numerical model through an incompressible fluid flow, for the simulation of energy and temperature changes in and around a U-tube borehole heat exchanger. The FlexPDE software is used to solve the resulting simultaneous equations that model the heat exchanger. The validated model (through a comparison with experimental data) is then used to extract conclusions on how various parameters like the U-tube diameter, the variation of the ground thermal conductivity and specific heat and the borehole filling material affect the temperature of the fluid.Keywords: U-tube borehole, energy flow, incompressible fluid, numerical model
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20041215 Effects of Specific Essential Oil Compounds on, Feed Intake, Milk Production, and Ruminal Environment in Dairy Cows during Heat Exposure
Authors: K. Reza-Yazdi, M. Fallah, M. Khodaparast, F. Kateb, M. Hosseini-Ghaffari
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The objective of this study was to determine effect of dietary essential oil (EO) compounds, which contained cinnamaldehyde, eugenol, peppermint, coriander, cumin, lemongrass, and an organic carrier on feed intake, milk composition, and rumen fermentation of dairy cows during heat exposure. Thirty-two Holstein cows (days in milk= 60 ± 5) were assigned to one of two treatment groups: a Control and EO fed. The experiment lasted 28 days. Dry matter intake (DMI) was measured daily while and milk production was measured weekly. Our result showed that DMI and milk yield was decreased (P < 0.01) in control cows relative to EO cows. Furthermore, supplementation with EO was associated with a decrease in the molar proportion of propionate (P < 0.05) and increase (P < 0.05) in acetate to propionate ratio. In conclusion, EO supplementations in diets can be useful nutritional modification to alleviate for the decrease DMI and milk production during heat exposure in lactating dairy cows.
Keywords: Dairy cow, feed additive, plant extract.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33711214 Comparison of Conventional and “ECO“Transportation Pavements in Cyprus using Life Cycle Approach
Authors: Constantia Achilleos, Diofantos G. Hadjimitsis
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Road industry has challenged the prospect of ecoconstruction. Pavements may fit within the framework of sustainable development. Hence, research implements assessments of conventional pavements impacts on environment in use of life cycle approach. To meet global, and often national, targets on pollution control, newly introduced pavement designs are under study. This is the case of Cyprus demonstration, which occurred within EcoLanes project work. This alternative pavement differs on concrete layer reinforced with tire recycling product. Processing of post-consumer tires produces steel fibers improving strength capacity against cracking. Thus maintenance works are relevantly limited in comparison to flexible pavement. This enables to be more ecofriendly, referenced to current study outputs. More specific, proposed concrete pavement life cycle processes emits 15 % less air pollutants and consumes 28 % less embodied energy than those of the asphalt pavement. In addition there is also a reduction on costs by 0.06 %.
Keywords: Environmental impact assessment, life cycle, tirerecycling, transportation pavement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21841213 Generative Design of Acoustical Diffuser and Absorber Elements Using Large-Scale Additive Manufacturing
Authors: S. Aziz, B. Alexander, C. Gengnagel, S. Weinzierl
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This paper explores a generative design, simulation, and optimization workflow for the integration of acoustical diffuser and/or absorber geometry with embedded coupled Helmholtz-resonators for full scale 3D printed building components. Large-scale additive manufacturing in conjunction with algorithmic CAD design tools enables a vast amount of control when creating geometry. This is advantageous regarding the increasing demands of comfort standards for indoor spaces and the use of more resourceful and sustainable construction methods and materials. The presented methodology highlights these new technological advancements and offers a multimodal and integrative design solution with the potential for an immediate application in the AEC-Industry. In principle, the methodology can be applied to a wide range of structural elements that can be manufactured by additive manufacturing processes. The current paper focuses on a case study of an application for a biaxial load-bearing beam grillage made of reinforced concrete, which allows for a variety of applications through the combination of additive prefabricated semi-finished parts and in-situ concrete supplementation. The semi-prefabricated parts or formwork bodies form the basic framework of the supporting structure and at the same time have acoustic absorption and diffusion properties that are precisely acoustically programmed for the space underneath the structure. To this end, a hybrid validation strategy is being explored using a digital and cross-platform simulation environment, verified with physical prototyping. The iterative workflow starts with the generation of a parametric design model for the acoustical geometry using the algorithmic visual scripting editor Grasshopper3D inside the Building Information Modeling (BIM) software Revit. Various geometric attributes (i.e., bottleneck and cavity dimensions) of the resonator are parameterized and fed to a numerical optimization algorithm which can modify the geometry with the goal of increasing absorption at resonance and increasing the bandwidth of the effective absorption range. Using Rhino.Inside and LiveLink for Revit the generative model was imported directly into the Multiphysics simulation environment COMSOL. The geometry was further modified and prepared for simulation in a semi-automated process. The incident and scattered pressure fields were simulated from which the surface normal absorption coefficients were calculated. This reciprocal process was repeated to further optimize the geometric parameters. Subsequently the numerical models were compared to a set of 3D concrete printed physical twin models which were tested in a .25 m x .25 m impedance tube. The empirical results served to improve the starting parameter settings of the initial numerical model. The geometry resulting from the numerical optimization was finally returned to grasshopper for further implementation in an interdisciplinary study.
Keywords: Acoustical design, additive manufacturing, computational design, multimodal optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6031212 A New Color Image Database for Benchmarking of Automatic Face Detection and Human Skin Segmentation Techniques
Authors: Abdallah S. Abdallah, Mohamad A bou El-Nasr, A. Lynn Abbott
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This paper presents a new color face image database for benchmarking of automatic face detection algorithms and human skin segmentation techniques. It is named the VT-AAST image database, and is divided into four parts. Part one is a set of 286 color photographs that include a total of 1027 faces in the original format given by our digital cameras, offering a wide range of difference in orientation, pose, environment, illumination, facial expression and race. Part two contains the same set in a different file format. The third part is a set of corresponding image files that contain human colored skin regions resulting from a manual segmentation procedure. The fourth part of the database has the same regions converted into grayscale. The database is available on-line for noncommercial use. In this paper, descriptions of the database development, organization, format as well as information needed for benchmarking of algorithms are depicted in detail.Keywords: Image database, color image analysis, facedetection, skin segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25881211 Simulator Dynamic Positioning System with Azimuthal Thruster
Authors: Robson C. Santos, Christian N. Barreto, Gerson G. Cunha, Severino J. C. Neto
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This paper aims to project the construction of a prototype azimuthal thruster, mounted with materials of low cost and easy access, testing in a controlled environment to measure their performance, characteristics and feasibility of future projects. The construction of the simulation of dynamic positioning software, responsible for simulating a vessel and reposition it when necessary. Validation tests were performed in the form of partial or complete system. These tests validate the system manually or automatically. The system provides an interface to the user and simulates the conditions unfavorable positioning of a vessel, accurately calculates the azimuth angle, the direction of rotation of the helix and the time that this should be turned on so that the vessel back to position original. A serial communication connects the Simulation Dynamic Positioning System with Embedded System causing the usergenerated data to simulate the DP system arrives in the form of control signals to the motors of the propellant. This article addresses issues in the marine industry employees.Keywords: Azimuthal Thruster, Dynamic Positioning, Embedded System.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27781210 A Comprehensive Review on Different Mixed Data Clustering Ensemble Methods
Authors: S. Sarumathi, N. Shanthi, S. Vidhya, M. Sharmila
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An extensive amount of work has been done in data clustering research under the unsupervised learning technique in Data Mining during the past two decades. Moreover, several approaches and methods have been emerged focusing on clustering diverse data types, features of cluster models and similarity rates of clusters. However, none of the single clustering algorithm exemplifies its best nature in extracting efficient clusters. Consequently, in order to rectify this issue, a new challenging technique called Cluster Ensemble method was bloomed. This new approach tends to be the alternative method for the cluster analysis problem. The main objective of the Cluster Ensemble is to aggregate the diverse clustering solutions in such a way to attain accuracy and also to improve the eminence the individual clustering algorithms. Due to the massive and rapid development of new methods in the globe of data mining, it is highly mandatory to scrutinize a vital analysis of existing techniques and the future novelty. This paper shows the comparative analysis of different cluster ensemble methods along with their methodologies and salient features. Henceforth this unambiguous analysis will be very useful for the society of clustering experts and also helps in deciding the most appropriate one to resolve the problem in hand.
Keywords: Clustering, Cluster Ensemble Methods, Coassociation matrix, Consensus Function, Median Partition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21041209 Effect of Social Media on the Study Habits of Students of Alvan Ikoku Federal College of Education, Owerri
Authors: Perpetua O. Ezeji, Kelechi E. Ezeji
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There has been considerable anxiety in society that social media distracts from education and reduces the social skills of young people. Following this, educators have sought ways to mitigate its negative effects on educational attainment while incorporating its positive aspects into the learning process. This study sought to examine the impact of social media on the study habits of students of Alvan Ikoku Federal College of Education, Owerri. The research design involved survey technique where questionnaires were used to collect data from a sample of the student population. Statistical package for social sciences (SPSS) was used to analyse the data. Spearman’s Rho was the specific tool used for analysis. It was presented in frequency tables and bar charts. Findings from variables investigated showed that at p<0.5, social media usage had a significant impact on the study habits of students of Alvan Ikoku Federal College of Education, Owerri. This indicated the need for stakeholders in the community to employ counselling and other proactive measures to ensure that students maintained proper focus on their primary assignment for schooling.
Keywords: Education, social media, study habits, technology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 88311208 Statistical Analysis and Predictive Learning of Mechanical Parameters for TiO2 Filled GFRP Composite
Authors: S. Srinivasa Moorthy, K. Manonmani
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The new, polymer composites consisting of e-glass fiber reinforcement with titanium oxide filler in the double bonded unsaturated polyester resin matrix were made. The glass fiber and titanium oxide reinforcement composites were made in three different fiber lengths (3cm, 5cm, and 7cm), filler content (2 wt%, 4 wt%, and 6 wt%) and fiber content (20 wt%, 40 wt%, and 60 wt%). 27 different compositions were fabricated and a sequence of experiments were carried out to determine tensile strength and impact strength. The vital influencing factors fiber length, fiber content and filler content were chosen as 3 factors in 3 levels of Taguchi’s L9 orthogonal array. The influences of parameters were determined for tensile strength and impact strength by Analysis of variance (ANOVA) and S/N ratio. Using Artificial Neural Network (ANN) an expert system was devised to predict the properties of hybrid reinforcement GFRP composites. The predict models were experimentally proved with the maximum coincidence.
Keywords: Analysis of variance (ANOVA), Artificial neural network (ANN), Polymer composites, Taguchi’s orthogonal array.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24001207 Cooling-Rate Induced Fiber Birefringence Variation in Regenerated High Birefringent Fiber
Authors: M. H. Lai, D. S. Gunawardena, K. S. Lim, H. Ahmad
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In this paper, we have reported birefringence manipulation in regenerated high birefringent fiber Bragg grating (RPMG) by using CO2 laser annealing method. The results indicate that the birefringence of RPMG remains unchanged after CO2 laser annealing followed by slow cooling process, but reduced after fast cooling process (~5.6×10-5). After a series of annealing procedures with different cooling rates, the obtained results show that slower the cooling rate, higher the birefringence of RPMG. The volume, thermal expansion coefficient (TEC) and glass transition temperature (Tg) change of stress applying part in RPMG during cooling process are responsible for the birefringence change. Therefore, these findings are important to the RPMG sensor in high and dynamic temperature environment. The measuring accuracy, range and sensitivity of RPMG sensor is greatly affected by its birefringence value. This work also opens up a new application of CO2 laser for fiber annealing and birefringence modification.Keywords: Birefringence, CO2 laser annealing, regenerated gratings, thermal stress.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15411206 Financial Portfolio Optimization in Electricity Markets: Evaluation via Sharpe Ratio
Authors: F. Gökgöz, M. E. Atmaca
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Electricity plays an indispensable role in human life and the economy. It is a unique product or service that must be balanced instantaneously, as electricity is not stored, generation and consumption should be proportional. Effective and efficient use of electricity is very important not only for society, but also for the environment. A competitive electricity market is one of the best ways to provide a suitable platform for effective and efficient use of electricity. On the other hand, it carries some risks that should be carefully managed by the market players. Risk management is an essential part in market players’ decision making. In this paper, risk management through diversification is applied with the help of Markowitz’s Mean-variance, Down-side and Semi-variance methods for a case study. Performance of optimal electricity sale solutions are measured and evaluated via Sharpe-Ratio, and the optimal portfolio solutions are improved. Two years of historical weekdays’ price data of the Turkish Day Ahead Market are used to demonstrate the approach.
Keywords: Electricity market, portfolio optimization, risk management in electricity market, Sharpe ratio.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14851205 Design Improvement of Dental Implant-Based on Bone Remodelling
Authors: Solehuddin Shuib, Koay Boon Aik, Zainul Ahmad Rajion
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There are many types of mechanical failure on the dental implant. In this project, the failure that needs to take into consideration is the bone resorption on the dental implant. Human bone has its ability to remodel after the implantation. As the dental implant is installed into the bone, the bone will detect and change the bone structure to achieve new biomechanical environment. This phenomenon is known as bone remodeling. The objective of the project is to improve the performance of dental implant by using different types of design. These designs are used to analyze and predict the failure of the dental implant by using finite element analysis (FEA) namely ANSYS. The bone is assumed to be fully attached to the implant or cement. Hence, results are then compared with other researchers. The results were presented in the form of Von Mises stress, normal stress, shear stress analysis, and displacement. The selected design will be analyzed further based on a theoretical calculation of bone remodeling on the dental implant. The results have shown that the design constructed passed the failure analysis. Therefore, the selected design is proven to have a stable performance at the recovery stage.Keywords: Dental implant, FEA, bone remodeling, osseointegration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10531204 Replicating Data Objects in Large-scale Distributed Computing Systems using Extended Vickrey Auction
Authors: Samee Ullah Khan, Ishfaq Ahmad
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This paper proposes a novel game theoretical technique to address the problem of data object replication in largescale distributed computing systems. The proposed technique draws inspiration from computational economic theory and employs the extended Vickrey auction. Specifically, players in a non-cooperative environment compete for server-side scarce memory space to replicate data objects so as to minimize the total network object transfer cost, while maintaining object concurrency. Optimization of such a cost in turn leads to load balancing, fault-tolerance and reduced user access time. The method is experimentally evaluated against four well-known techniques from the literature: branch and bound, greedy, bin-packing and genetic algorithms. The experimental results reveal that the proposed approach outperforms the four techniques in both the execution time and solution quality.Keywords: Auctions, data replication, pricing, static allocation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14651203 Developing an Audit Quality Model for an Emerging Market
Authors: Bita Mashayekhi, Azadeh Maddahi, Arash Tahriri
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The purpose of this paper is developing a model for audit quality, with regard to the contextual and environmental attributes of the audit profession in Iran. For this purpose, using an exploratory approach, and because of the special attributes of the auditing profession in Iran in terms of the legal environment, regulatory and supervisory mechanisms, audit firms size, and etc., we used grounded theory approach as a qualitative research method. Therefore, we got the opinions of the experts in the auditing and capital market areas through unstructured interviews. As a result, the authors revealed the determinants of audit quality, and by using these determinants, developed an Integrated Audit Quality Model, including causal conditions, intervening conditions, context, as well as action strategies related to AQ and their consequences. In this research, audit quality is studied using a systemic approach. According to this approach, the quality of inputs, processes, and outputs of auditing determines the quality of auditing, therefore, the quality of all different parts of this system is considered.Keywords: Audit quality, integrated audit quality model, audit supply, demand for audit service, grounded theory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12821202 Photo Mosaic Smartphone Application in Client-Server Based Large-Scale Image Databases
Authors: Sang-Hun Lee, Bum-Soo Kim, Yang-Sae Moon, Jinho Kim
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In this paper we present a photo mosaic smartphone application in client-server based large-scale image databases. Photo mosaic is not a new concept, but there are very few smartphone applications especially for a huge number of images in the client-server environment. To support large-scale image databases, we first propose an overall framework working as a client-server model. We then present a concept of image-PAA features to efficiently handle a huge number of images and discuss its lower bounding property. We also present a best-match algorithm that exploits the lower bounding property of image-PAA. We finally implement an efficient Android-based application and demonstrate its feasibility.Keywords: smartphone applications; photo mosaic; similarity search; data mining; large-scale image databases.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16711201 A Cohesive Lagrangian Swarm and Its Application to Multiple Unicycle-like Vehicles
Authors: Jito Vanualailai, Bibhya Sharma
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Swarm principles are increasingly being used to design controllers for the coordination of multi-robot systems or, in general, multi-agent systems. This paper proposes a two-dimensional Lagrangian swarm model that enables the planar agents, modeled as point masses, to swarm whilst effectively avoiding each other and obstacles in the environment. A novel method, based on an extended Lyapunov approach, is used to construct the model. Importantly, the Lyapunov method ensures a form of practical stability that guarantees an emergent behavior, namely, a cohesive and wellspaced swarm with a constant arrangement of individuals about the swarm centroid. Computer simulations illustrate this basic feature of collective behavior. As an application, we show how multiple planar mobile unicycle-like robots swarm to eventually form patterns in which their velocities and orientations stabilize.
Keywords: Attractive-repulsive swarm model, individual-based swarm model, Lagrangian swarm model, Lyapunov stability, Lyapunov-like function, practical stability, unicycle.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15391200 An Improved k Nearest Neighbor Classifier Using Interestingness Measures for Medical Image Mining
Authors: J. Alamelu Mangai, Satej Wagle, V. Santhosh Kumar
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The exponential increase in the volume of medical image database has imposed new challenges to clinical routine in maintaining patient history, diagnosis, treatment and monitoring. With the advent of data mining and machine learning techniques it is possible to automate and/or assist physicians in clinical diagnosis. In this research a medical image classification framework using data mining techniques is proposed. It involves feature extraction, feature selection, feature discretization and classification. In the classification phase, the performance of the traditional kNN k nearest neighbor classifier is improved using a feature weighting scheme and a distance weighted voting instead of simple majority voting. Feature weights are calculated using the interestingness measures used in association rule mining. Experiments on the retinal fundus images show that the proposed framework improves the classification accuracy of traditional kNN from 78.57 % to 92.85 %.
Keywords: Medical Image Mining, Data Mining, Feature Weighting, Association Rule Mining, k nearest neighbor classifier.
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