Search results for: Voting techniques.
1386 Differentiation of Heart Rate Time Series from Electroencephalogram and Noise
Authors: V. I. Thajudin Ahamed, P. Dhanasekaran, Paul Joseph K.
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Analysis of heart rate variability (HRV) has become a popular non-invasive tool for assessing the activities of autonomic nervous system. Most of the methods were hired from techniques used for time series analysis. Currently used methods are time domain, frequency domain, geometrical and fractal methods. A new technique, which searches for pattern repeatability in a time series, is proposed for quantifying heart rate (HR) time series. These set of indices, which are termed as pattern repeatability measure and pattern repeatability ratio are able to distinguish HR data clearly from noise and electroencephalogram (EEG). The results of analysis using these measures give an insight into the fundamental difference between the composition of HR time series with respect to EEG and noise.Keywords: Approximate entropy, heart rate variability, noise, pattern repeatability, and sample entropy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17341385 Wind Tunnel Investigation of the Turbulent Flow around the Panorama Giustinelli Building for VAWT Application
Authors: M. Raciti Castelli, S. Mogno, S. Giacometti, E. Benini
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A boundary layer wind tunnel facility has been adopted in order to conduct experimental measurements of the flow field around a model of the Panorama Giustinelli Building, Trieste (Italy). Information on the main flow structures has been obtained by means of flow visualization techniques and has been compared to the numerical predictions of the vortical structures spread on top of the roof, in order to investigate the optimal positioning for a vertical-axis wind energy conversion system, registering a good agreement between experimental measurements and numerical predictions.Keywords: Boundary layer wind tunnel, flow around buildings, atmospheric flow field, vertical-axis wind turbine (VAWT).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18031384 Lexicon-Based Sentiment Analysis for Stock Movement Prediction
Authors: Zane Turner, Kevin Labille, Susan Gauch
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Sentiment analysis is a broad and expanding field that aims to extract and classify opinions from textual data. Lexicon-based approaches are based on the use of a sentiment lexicon, i.e., a list of words each mapped to a sentiment score, to rate the sentiment of a text chunk. Our work focuses on predicting stock price change using a sentiment lexicon built from financial conference call logs. We present a method to generate a sentiment lexicon based upon an existing probabilistic approach. By using a domain-specific lexicon, we outperform traditional techniques and demonstrate that domain-specific sentiment lexicons provide higher accuracy than generic sentiment lexicons when predicting stock price change.
Keywords: Lexicon, sentiment analysis, stock movement prediction., computational finance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7791383 Particle Swarm Optimization for Design of Water Distribution Systems
Authors: A. Vasan
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Particle swarm optimization (PSO) technique is applied to design the water distribution pipeline network. A simulation-optimization model is formulated with the objective of minimizing cost and is applied to a benchmark water distribution system optimization problem. The benchmark problem taken for the application of PSO technique to optimize the pipe size of the water distribution network is New York City water supply system problem. The results from the analysis infer that PSO is a potential alternative optimization technique when compared to other heuristic techniques for optimal sizing of water distribution systems.
Keywords: Water distribution systems, Optimization, Particle swarm optimization, Swarm intelligence, New York water supply system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15371382 Dynamic Model of a Buck Converter with a Sliding Mode Control
Authors: S. Chonsatidjamroen , K-N. Areerak, K-L. Areerak
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This paper presents the averaging model of a buck converter derived from the generalized state-space averaging method. The sliding mode control is used to regulate the output voltage of the converter and taken into account in the model. The proposed model requires the fast computational time compared with those of the full topology model. The intensive time-domain simulations via the exact topology model are used as the comparable model. The results show that a good agreement between the proposed model and the switching model is achieved in both transient and steady-state responses. The reported model is suitable for the optimal controller design by using the artificial intelligence techniques.Keywords: Generalized state-space averaging method, buck converter, sliding mode control, modeling, simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29901381 Analysis of Heart Beat Dynamics through Singularity Spectrum
Authors: Harish Kumar, Hussein Yahia, Oriol Pont, Michel Haissaguerre, Nicolas Derval, Meleze Hocini
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The analysis to detect arrhythmias and life-threatening conditions are highly essential in today world and this analysis can be accomplished by advanced non-linear processing methods for accurate analysis of the complex signals of heartbeat dynamics. In this perspective, recent developments in the field of multiscale information content have lead to the Microcanonical Multiscale Formalism (MMF). We show that such framework provides several signal analysis techniques that are especially adapted to the study of heartbeat dynamics. In this paper, we just show first hand results of whether the considered heartbeat dynamics signals have the multiscale properties by computing local preticability exponents (LPEs) and the Unpredictable Points Manifold (UPM), and thereby computing the singularity spectrum.Keywords: Microcanonical Multiscale Formalism (MMF), UnpredictablePoints Manifold (UPM), Heartbeat Dynamics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15181380 Comparison of Chemical Coagulation and Electrocoagulation for Boron Removal from Synthetic Wastewater Using Aluminium
Authors: Kartikaningsih Danis, Yao-Hui Huang
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Various techniques including conventional and advanced have been employed for the boron treatment from water and wastewater. The electrocoagulation involves an electrolytic reactor for coagulation/flotation with aluminium as anode and cathode. There is aluminium as coagulant to be used for removal which may induce secondary pollution in chemical coagulation. The purpose of this study is to investigate and compare the performance between electrocoagulation and chemical coagulation on boron removal from synthetic wastewater. The effect of different parameters, such as pH reaction, coagulant dosage, and initial boron concentration were examined. The results show that the boron removal using chemical coagulation was lower. At the optimum condition (e.g. pH 8 and 0.8 mol coagulant dosage), boron removal efficiencies for chemical coagulation and electrocoagulation were 61% and 91%, respectively. In addition, the electrocoagulation needs no chemical reagents and makes the boron treatment easy for application.
Keywords: Electrocoagulation, chemical coagulation, aluminum electrode, boron removal.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17391379 Determination of the Characteristics for Ferroresonance Phenomenon in Electric Power Systems
Authors: Sezen Yildirim, Tahir Çetin Akinci, Serhat Seker, Nazmi Ekren
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Ferroresonance is an electrical phenomenon in nonlinear character, which frequently occurs in power system due to transmission line faults and single or more-phase switching on the lines as well as usage of the saturable transformers. In this study, the ferroresonance phenomena are investigated under the modeling of the West Anatolian Electric Power Network of 380 kV in Turkey. The ferroresonance event is observed as a result of removing the loads at the end of the lines. In this sense, two different cases are considered. At first, the switching is applied at 2nd second and the ferroresonance affects are observed between 2nd and 4th seconds in the voltage variations of the phase-R. Hence the ferroresonance and nonferroresonance parts of the overall data are compared with each others using the Fourier transform techniques to show the ferroresonance affects.Keywords: Ferroresonance, West Anatolian Electric Power System, Power System Modeling, Switching, Spectral Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26911378 A System of Automatic Speech Recognition based on the Technique of Temporal Retiming
Authors: Samir Abdelhamid, Noureddine Bouguechal
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We report in this paper the procedure of a system of automatic speech recognition based on techniques of the dynamic programming. The technique of temporal retiming is a technique used to synchronize between two forms to compare. We will see how this technique is adapted to the field of the automatic speech recognition. We will expose, in a first place, the theory of the function of retiming which is used to compare and to adjust an unknown form with a whole of forms of reference constituting the vocabulary of the application. Then we will give, in the second place, the various algorithms necessary to their implementation on machine. The algorithms which we will present were tested on part of the corpus of words in Arab language Arabdic-10 [4] and gave whole satisfaction. These algorithms are effective insofar as we apply them to the small ones or average vocabularies.Keywords: Continuous speech recognition, temporal retiming, phonetic decoding, algorithms, vocal signal, dynamic programming.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13471377 Context-aware Recommender Systems using Data Mining Techniques
Authors: Kyoung-jae Kim, Hyunchul Ahn, Sangwon Jeong
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This study proposes a novel recommender system to provide the advertisements of context-aware services. Our proposed model is designed to apply a modified collaborative filtering (CF) algorithm with regard to the several dimensions for the personalization of mobile devices – location, time and the user-s needs type. In particular, we employ a classification rule to understand user-s needs type using a decision tree algorithm. In addition, we collect primary data from the mobile phone users and apply them to the proposed model to validate its effectiveness. Experimental results show that the proposed system makes more accurate and satisfactory advertisements than comparative systems.Keywords: Location-based advertisement, Recommender system, Collaborative filtering, User needs type, Mobile user.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21741376 A Fast Directionally Constrained Minimization of Power Algorithm for Extracting a Speech Signal Perpendicular to a Microphone Array
Authors: Yasuhiko Okuma, Yuichi Suzuki, Takahiro Murakami, Yoshihisa Ishida
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In this paper, an extended method of the directionally constrained minimization of power (DCMP) algorithm for broadband signals is proposed. The DCMP algorithm is one of the useful techniques of extracting a target signal from observed signals of a microphone array system. In the DCMP algorithm, output power of the microphone array is minimized under a constraint of constant responses to directions of arrival (DOAs) of specific signals. In our algorithm, by limiting the directional constraint to the perpendicular direction to the sensor array system, the calculating time is reduced.Keywords: Beamformer, directionally constrained minimizationof power, direction of arrival, microphone array.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16621375 Lexicon-Based Sentiment Analysis for Stock Movement Prediction
Authors: Zane Turner, Kevin Labille, Susan Gauch
Abstract:
Sentiment analysis is a broad and expanding field that aims to extract and classify opinions from textual data. Lexicon-based approaches are based on the use of a sentiment lexicon, i.e., a list of words each mapped to a sentiment score, to rate the sentiment of a text chunk. Our work focuses on predicting stock price change using a sentiment lexicon built from financial conference call logs. We introduce a method to generate a sentiment lexicon based upon an existing probabilistic approach. By using a domain-specific lexicon, we outperform traditional techniques and demonstrate that domain-specific sentiment lexicons provide higher accuracy than generic sentiment lexicons when predicting stock price change.
Keywords: Computational finance, sentiment analysis, sentiment lexicon, stock movement prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11371374 Throughflow Effects on Thermal Convection in Variable Viscosity Ferromagnetic Liquids
Authors: G. N. Sekhar, P. G. Siddheshwar, G. Jayalatha, R. Prakash
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The problem of thermal convection in temperature and magnetic field sensitive Newtonian ferromagnetic liquid is studied in the presence of uniform vertical magnetic field and throughflow. Using a combination of Galerkin and shooting techniques the critical eigenvalues are obtained for stationary mode. The effect of Prandtl number (Pr > 1) on onset is insignificant and nonlinearity of non-buoyancy magnetic parameter M3 is found to have no influence on the onset of ferroconvection. The magnetic buoyancy number, M1 and variable viscosity parameter, V have destabilizing influences on the system. The effect of throughflow Peclet number, Pe is to delay the onset of ferroconvection and this effect is independent of the direction of flow.Keywords: Ferroconvection, throughflow, temperature dependent viscosity, magnetic field dependent viscosity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11471373 DeClEx-Processing Pipeline for Tumor Classification
Authors: Gaurav Shinde, Sai Charan Gongiguntla, Prajwal Shirur, Ahmed Hambaba
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Health issues are significantly increasing, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly. We introduce DeClEx, a pipeline which ensures that data mirrors real-world settings by incorporating gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state-of-the-art pre-trained models while achieving a threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification and explainability in a single pipeline called DeClEx.
Keywords: Machine learning, healthcare, classification, explainability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 661372 Evaluating the Performance of Offensive Lineman in the NFL
Authors: Nikhil Byanna, Abdolghani Ebrahimi, Diego Klabjan
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In this paper we objectively measure the performance of an individual offensive lineman in the NFL. The existing literature proposes various measures that rely on subjective assessments of game film, but has yet to develop an objective methodology to evaluate performance. Using a variety of statistics related to an offensive lineman’s performance, we develop a framework to objectively analyze the overall performance of an individual offensive lineman and determine specific linemen who are overvalued or undervalued relative to their salary. We identify eight players across the 2013-2014 and 2014-2015 NFL seasons that are considered to be overvalued or undervalued and corroborate the results with existing metrics that are based on subjective evaluation. To the best of our knowledge, the techniques set forth in this work have not been utilized in previous works to evaluate the performance of NFL players at any position, including offensive linemen.
Keywords: offensive lineman, player performance, NFL, machine learning
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5341371 A New OvS Approach in an Assembly Line Balancing Problem
Authors: P. Azimi, B. Behtoiy
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One of the most famous techniques which affect the efficiency of a production line is the assembly line balancing (ALB) technique. This paper examines the balancing effect of a whole production line of a real auto glass manufacturer in three steps. In the first step, processing time of each activity in the workstations is generated according to a practical approach. In the second step, the whole production process is simulated and the bottleneck stations have been identified, and finally in the third step, several improvement scenarios are generated to optimize the system throughput, and the best one is proposed. The main contribution of the current research is the proposed framework which combines two famous approaches including Assembly Line Balancing and Optimization via Simulation technique (OvS). The results show that the proposed framework could be applied in practical environments, easily.Keywords: Assembly line balancing problem, optimization via simulation, production planning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18051370 Synthesis and Characterization of Gallosilicate Sodalite Containing NO2- Ions
Authors: Ashok V. Borhade, Sanjay G. Wakchaure
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Pure phase gallosilicate nitrite sodalite has been synthesized in a single step by low temperature (373 oK) hydrothermal technique. The product obtained was characterized using a combination of techniques including X-ray powder diffraction, IR, Raman spectroscopy, SEM, MAS NMR spectroscopy as well as thermogravimetry. Sodalite with an ideal composition was obtained after synthesis at 3730K and seven days duration using alkaline medium. The structural features of the Na8[GaSiO4]6(NO2)2 sodalite were investigated by IR, MAS NMR spectroscopy of 29Si and 23Na nuclei and by Reitveld refinement of X-ray powder diffraction data. The crystal structure of this sodalite has been refined in the space group P 4 3n; with a cell parameter 8.98386Å, V= 726.9 Å, (Rwp= 0.077 and Rp=0.0537) and Si-O-Ga angle is found to be 132.920 . MAS NMR study confirms complete ordering of Si and Ga in the gallosilicate framework. The surface area of single entity with stoichiometry Na8[GaSiO4]6(NO2)2 was found to be 8.083 x10-15 cm2/g.
Keywords: Gallosilicate, hydrothermal, nitrite, Reitveldrefinement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16221369 Genetic Characterization of Barley Genotypes via Inter-Simple Sequence Repeat
Authors: Mustafa Yorgancılar, Emine Atalay, Necdet Akgün, Ali Topal
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In this study, polymerase chain reaction based Inter-simple sequence repeat (ISSR) from DNA fingerprinting techniques were used to investigate the genetic relationships among barley crossbreed genotypes in Turkey. It is important that selection based on the genetic base in breeding programs via ISSR, in terms of breeding time. 14 ISSR primers generated a total of 97 bands, of which 81 (83.35%) were polymorphic. The highest total resolution power (RP) value was obtained from the F2 (0.53) and M16 (0.51) primers. According to the ISSR result, the genetic similarity index changed between 0.64–095; Lane 3 with Line 6 genotypes were the closest, while Line 36 were the most distant ones. The ISSR markers were found to be promising for assessing genetic diversity in barley crossbreed genotypes.
Keywords: Barley, crossbreed, genetic similarity, ISSR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9191368 An Experimental Study and Influence of BHF and Die Radius in Deep Drawing Process on the Springback
Authors: A. Soualem
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A lot of research made during these last 15 years showed that the quantification of the springback has a significant role in the industry of sheet metal forming. These studies were made with the objective of finding techniques and methods to minimize or completely avoid this permanent physical variation. Moreover, the use of steel and aluminum alloys in the car industry and aviation poses every day the problem of the springback. The determination in advance of the quantity of the springback allows consequently the design and manufacture of the tool. The aim of this paper is to study experimentally the influence of the blank holder force BHF and the radius of curvature of the die on the springback and their influence on the strain in various zone of specimen. The original of our purpose consist on tests which are ensured by adapting a U-type stretching-bending device on a tensile testing machine, where we studied and quantified the variation of the springback according to displacement.Keywords: Blank holder force, Deep-Drawing, Die radius, Forming, Springback.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16951367 Characterization and Modeling of Piezoelectric Integrated Micro Speakers for Audio Acoustic Actuation
Authors: J. Mendoza-López, S. Sánchez-Solano, J. L. Huertas-Díaz
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An array of piezoelectric micro actuators can be used for radiation of an ultrasonic carrier signal modulated in amplitude with an acoustic signal, which yields audio frequency applications as the air acts as a self-demodulating medium. This application is known as the parametric array. We propose a parametric array with array elements based on existing piezoelectric micro ultrasonic transducer (pMUT) design techniques. In order to reach enough acoustic output power at a desired operating frequency, a proper ratio between number of array elements and array size needs to be used, with an array total area of the order of one cm square. The transducers presented are characterized via impedance, admittance, noise figure, transducer gain and frequency responses.Keywords: Pizeoelectric, Microspeaker, MEMS, pMUT, Parametric Array
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22481366 Managerial Styles of Asian Executives: The Case of Thailand
Authors: Teerayout Wattanasupachoke
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This research project is developed in order to study managerial styles of modern Thai executives. The thorough understanding will lead to continuous improvement and efficient performance of Thai business organizations. Regarding managerial skills, Thai executives focus heavily upon human skills. Also, the negotiator roles are most emphasis in their management. In addition, Thai executives pay most attention to the fundamental management principles including Harmony and Unity of Direction of the organizations. Moreover, the management techniques, consisting of Team work and Career Planning are of their main concern. Finally, Thai executives wish to enhance their firms- image and employees- morale through conducting the ethical and socially responsible activities. The major tactic deployed to stimulate employees- ethical behaviors and mindset is Code of Ethics development.Keywords: Management, Managerial Styles, Asian Executives, Thailand.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17161365 Water End-Use Classification with Contemporaneous Water-Energy Data and Deep Learning Network
Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang
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‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.
Keywords: Deep learning network, smart metering, water end use, water-energy data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13631364 Coding Considerations for Standalone Molecular Dynamics Simulations of Atomistic Structures
Authors: R. O. Ocaya, J. J. Terblans
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The laws of Newtonian mechanics allow ab-initio molecular dynamics to model and simulate particle trajectories in material science by defining a differentiable potential function. This paper discusses some considerations for the coding of ab-initio programs for simulation on a standalone computer and illustrates the approach by C language codes in the context of embedded metallic atoms in the face-centred cubic structure. The algorithms use velocity-time integration to determine particle parameter evolution for up to several thousands of particles in a thermodynamical ensemble. Such functions are reusable and can be placed in a redistributable header library file. While there are both commercial and free packages available, their heuristic nature prevents dissection. In addition, developing own codes has the obvious advantage of teaching techniques applicable to new problems.Keywords: C-language, molecular dynamics, simulation, embedded atom method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14081363 The Interaction between Human and Environment on the Perspective of Environmental Ethics
Authors: Mella Ismelina Farma Rahayu
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Environmental problems could not be separated from unethical human perspectives and behaviors toward the environment. There is a fundamental error in the philosophy of people’s perspective about human and nature and their relationship with the environment, which in turn will create an inappropriate behavior in relation to the environment. The aim of this study is to investigate and to understand the ethics of the environment in the context of humans interacting with the environment by using the hermeneutic approach. The related theories and concepts collected from literature review are used as data, which were analyzed by using interpretation, critical evaluation, internal coherence, comparisons, and heuristic techniques. As a result of this study, there will be a picture related to the interaction of human and environment in the perspective of environmental ethics, as well as the problems of the value of ecological justice in the interaction of humans and environment. We suggest that the interaction between humans and environment need to be based on environmental ethics, in a spirit of mutual respect between humans and the natural world.
Keywords: The environment, environmental ethics, the interaction, value.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15981362 Choosing Search Algorithms in Bayesian Optimization Algorithm
Authors: Hao Wu, Jonathan L. Shapiro
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The Bayesian Optimization Algorithm (BOA) is an algorithm based on the estimation of distributions. It uses techniques from modeling data by Bayesian networks to estimating the joint distribution of promising solutions. To obtain the structure of Bayesian network, different search algorithms can be used. The key point that BOA addresses is whether the constructed Bayesian network could generate new and useful solutions (strings), which could lead the algorithm in the right direction to solve the problem. Undoubtedly, this ability is a crucial factor of the efficiency of BOA. Varied search algorithms can be used in BOA, but their performances are different. For choosing better ones, certain suitable method to present their ability difference is needed. In this paper, a greedy search algorithm and a stochastic search algorithm are used in BOA to solve certain optimization problem. A method using Kullback-Leibler (KL) Divergence to reflect their difference is described.
Keywords: Bayesian optimization algorithm, greedy search, KL divergence, stochastic search.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16981361 Analysis of Image Segmentation Techniques for Diagnosis of Dental Caries in X-ray Images
Authors: V. Geetha, K. S. Aprameya
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Early diagnosis of dental caries is essential for maintaining dental health. In this paper, method for diagnosis of dental caries is proposed using Laplacian filter, adaptive thresholding, texture analysis and Support Vector Machine (SVM) classifier. Analysis of the proposed method is compared with Otsu thresholding, watershed segmentation and active contouring method. Adaptive thresholding has comparatively better performance with 96.9% accuracy and 96.1% precision. The results are validated using statistical method, two-way ANOVA, at significant level of 5%, that shows the interaction of proposed method on performance parameter measures are significant. Hence the proposed technique could be used for detection of dental caries in automated computer assisted diagnosis system.
Keywords: Computer assisted diagnosis, dental caries, dental radiography, image segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11541360 Improving Cache Memory Utilization
Authors: Sami I. Serhan, Hamed M. Abdel-Haq
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In this paper, an efficient technique is proposed to manage the cache memory. The proposed technique introduces some modifications on the well-known set associative mapping technique. This modification requires a little alteration in the structure of the cache memory and on the way by which it can be referenced. The proposed alteration leads to increase the set size virtually and consequently to improve the performance and the utilization of the cache memory. The current mapping techniques have accomplished good results. In fact, there are still different cases in which cache memory lines are left empty and not used, whereas two or more processes overwrite the lines of each other, instead of using those empty lines. The proposed algorithm aims at finding an efficient way to deal with such problem.
Keywords: Modified Set Associative Mapping, Locality of Reference, Miss Ratio, Hit Ratio, Cache Memory, Clustered Behavior, Index Address, Tag Field, Status Field, and Complement of Index Address.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19271359 A Survey in Techniques for Imbalanced Intrusion Detection System Datasets
Authors: Najmeh Abedzadeh, Matthew Jacobs
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An intrusion detection system (IDS) is a software application that monitors malicious activities and generates alerts if any are detected. However, most network activities in IDS datasets are normal, and the relatively few numbers of attacks make the available data imbalanced. Consequently, cyber-attacks can hide inside a large number of normal activities, and machine learning algorithms have difficulty learning and classifying the data correctly. In this paper, a comprehensive literature review is conducted on different types of algorithms for both implementing the IDS and methods in correcting the imbalanced IDS dataset. The most famous algorithms are machine learning (ML), deep learning (DL), synthetic minority over-sampling technique (SMOTE), and reinforcement learning (RL). Most of the research use the CSE-CIC-IDS2017, CSE-CIC-IDS2018, and NSL-KDD datasets for evaluating their algorithms.
Keywords: IDS, intrusion detection system, imbalanced datasets, sampling algorithms, big data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11251358 Predicting Groundwater Areas Using Data Mining Techniques: Groundwater in Jordan as Case Study
Authors: Faisal Aburub, Wael Hadi
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Data mining is the process of extracting useful or hidden information from a large database. Extracted information can be used to discover relationships among features, where data objects are grouped according to logical relationships; or to predict unseen objects to one of the predefined groups. In this paper, we aim to investigate four well-known data mining algorithms in order to predict groundwater areas in Jordan. These algorithms are Support Vector Machines (SVMs), Naïve Bayes (NB), K-Nearest Neighbor (kNN) and Classification Based on Association Rule (CBA). The experimental results indicate that the SVMs algorithm outperformed other algorithms in terms of classification accuracy, precision and F1 evaluation measures using the datasets of groundwater areas that were collected from Jordanian Ministry of Water and Irrigation.Keywords: Classification, data mining, evaluation measures, groundwater.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25951357 Skin Detection using Histogram depend on the Mean Shift Algorithm
Authors: Soo- Young Ye, Ki-Gon Nam, Ki-Won Byun
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In this paper, we were introduces a skin detection method using a histogram approximation based on the mean shift algorithm. The proposed method applies the mean shift procedure to a histogram of a skin map of the input image, generated by comparison with standard skin colors in the CbCr color space, and divides the background from the skin region by selecting the maximum value according to brightness level. The proposed method detects the skin region using the mean shift procedure to determine a maximum value that becomes the dividing point, rather than using a manually selected threshold value, as in existing techniques. Even when skin color is contaminated by illumination, the procedure can accurately segment the skin region and the background region. The proposed method may be useful in detecting facial regions as a pretreatment for face recognition in various types of illumination.Keywords: Skin region detection, mean shift, histogram approximation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2264