Search results for: simulator data
5527 Comparison of the H-Index of Researchers of Google Scholar and Scopus
Authors: Adian Fatchur Rochim, Abdul Muis, Riri Fitri Sari
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H-index has been widely used as a performance indicator of researchers around the world especially in Indonesia. The Government uses Scopus and Google scholar as indexing references in providing recognition and appreciation. However, those two indexing services yield to different H-index values. For that purpose, this paper evaluates the difference of the H-index from those services. Researchers indexed by Webometrics, are used as reference’s data in this paper. Currently, Webometrics only uses H-index from Google Scholar. This paper observed and compared corresponding researchers’ data from Scopus to get their H-index score. Subsequently, some researchers with huge differences in score are observed in more detail on their paper’s publisher. This paper shows that the H-index of researchers in Google Scholar is approximately 2.45 times of their Scopus H-Index. Most difference exists due to the existence of uncertified publishers, which is considered in Google Scholar but not in Scopus.Keywords: Google Scholar, H-index, Scopus.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21345526 Hand Gestures Based Emotion Identification Using Flex Sensors
Authors: S. Ali, R. Yunus, A. Arif, Y. Ayaz, M. Baber Sial, R. Asif, N. Naseer, M. Jawad Khan
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In this study, we have proposed a gesture to emotion recognition method using flex sensors mounted on metacarpophalangeal joints. The flex sensors are fixed in a wearable glove. The data from the glove are sent to PC using Wi-Fi. Four gestures: finger pointing, thumbs up, fist open and fist close are performed by five subjects. Each gesture is categorized into sad, happy, and excited class based on the velocity and acceleration of the hand gesture. Seventeen inspectors observed the emotions and hand gestures of the five subjects. The emotional state based on the investigators assessment and acquired movement speed data is compared. Overall, we achieved 77% accurate results. Therefore, the proposed design can be used for emotional state detection applications.
Keywords: Emotion identification, emotion models, gesture recognition, user perception.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9255525 CART Method for Modeling the Output Power of Copper Bromide Laser
Authors: Iliycho P. Iliev, Desislava S. Voynikova, Snezhana G. Gocheva-Ilieva
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This paper examines the available experiment data for a copper bromide vapor laser (CuBr laser), emitting at two wavelengths - 510.6 and 578.2nm. Laser output power is estimated based on 10 independent input physical parameters. A classification and regression tree (CART) model is obtained which describes 97% of data. The resulting binary CART tree specifies which input parameters influence considerably each of the classification groups. This allows for a technical assessment that indicates which of these are the most significant for the manufacture and operation of the type of laser under consideration. The predicted values of the laser output power are also obtained depending on classification. This aids the design and development processes considerably.
Keywords: Classification and regression trees (CART), Copper Bromide laser (CuBr laser), laser generation, nonparametric statistical model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18125524 The Application of an Ensemble of Boosted Elman Networks to Time Series Prediction: A Benchmark Study
Authors: Chee Peng Lim, Wei Yee Goh
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In this paper, the application of multiple Elman neural networks to time series data regression problems is studied. An ensemble of Elman networks is formed by boosting to enhance the performance of the individual networks. A modified version of the AdaBoost algorithm is employed to integrate the predictions from multiple networks. Two benchmark time series data sets, i.e., the Sunspot and Box-Jenkins gas furnace problems, are used to assess the effectiveness of the proposed system. The simulation results reveal that an ensemble of boosted Elman networks can achieve a higher degree of generalization as well as performance than that of the individual networks. The results are compared with those from other learning systems, and implications of the performance are discussed.
Keywords: AdaBoost, Elman network, neural network ensemble, time series regression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16755523 Energy Efficiency Analysis of Crossover Technologies in Industrial Applications
Authors: W. Schellong
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Industry accounts for one-third of global final energy demand. Crossover technologies (e.g. motors, pumps, process heat, and air conditioning) play an important role in improving energy efficiency. These technologies are used in many applications independent of the production branch. Especially electrical power is used by drives, pumps, compressors, and lightning. The paper demonstrates the algorithm of the energy analysis by some selected case studies for typical industrial processes. The energy analysis represents an essential part of energy management systems (EMS). Generally, process control system (PCS) can support EMS. They provide information about the production process, and they organize the maintenance actions. Combining these tools into an integrated process allows the development of an energy critical equipment strategy. Thus, asset and energy management can use the same common data to improve the energy efficiency.
Keywords: Crossover technologies, data management, energy analysis, energy efficiency, process control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9465522 Exploring the Relationship between Building Construction Activity and Road-Related Expenditure in Victoria
Authors: Md. Aftabuzzaman, Md. Kamruzzaman
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Road-related expenditure and building construction activity are two significant drivers of the Victorian economy. This paper investigates the relationship between building construction activity and road-related expenditure. Data for construction activities were collected from Victorian Building Authority, and road-related expenditure data were explored by the Bureau of Infrastructure and Transport Research Economics. The trend between these two sectors was compared. The analysis found a strong relationship between road-related expenditure and the volume of construction activity, i.e., the more construction activities, the greater the requirement of road-related expenditure, or vice-versa. The road-related expenditure has a two-year lag period, suggesting that the road sector requires two years to respond to the growth in the building sector.
Keywords: Building construction activity, infrastructure, road expenditure, Victorian building authority.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3745521 Self Organizing Mixture Network in Mixture Discriminant Analysis: An Experimental Study
Authors: Nazif Çalış, Murat Erişoğlu, Hamza Erol, Tayfun Servi
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In the recent works related with mixture discriminant analysis (MDA), expectation and maximization (EM) algorithm is used to estimate parameters of Gaussian mixtures. But, initial values of EM algorithm affect the final parameters- estimates. Also, when EM algorithm is applied two times, for the same data set, it can be give different results for the estimate of parameters and this affect the classification accuracy of MDA. Forthcoming this problem, we use Self Organizing Mixture Network (SOMN) algorithm to estimate parameters of Gaussians mixtures in MDA that SOMN is more robust when random the initial values of the parameters are used [5]. We show effectiveness of this method on popular simulated waveform datasets and real glass data set.Keywords: Self Organizing Mixture Network, MixtureDiscriminant Analysis, Waveform Datasets, Glass Identification, Mixture of Multivariate Normal Distributions
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15055520 Scheduling a Flexible Flow Shops Problem using DEA
Authors: Fatemeh Dadkhah, Hossein Ali Akbarpour
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This paper considers a scheduling problem in flexible flow shops environment with the aim of minimizing two important criteria including makespan and cumulative tardiness of jobs. Since the proposed problem is known as an Np-hard problem in literature, we have to develop a meta-heuristic to solve it. We considered general structure of Genetic Algorithm (GA) and developed a new version of that based on Data Envelopment Analysis (DEA). Two objective functions assumed as two different inputs for each Decision Making Unit (DMU). In this paper we focused on efficiency score of DMUs and efficient frontier concept in DEA technique. After introducing the method we defined two different scenarios with considering two types of mutation operator. Also we provided an experimental design with some computational results to show the performance of algorithm. The results show that the algorithm implements in a reasonable time.Keywords: Data envelopment analysis, Efficiency, Flexible flow shops, Genetic algorithm
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18055519 Optimal Estimation of Surface Reflectance from Landsat TM Visible and Mid Infrared Data over Penang Island
Authors: H. S. Lim, M. Z. MatJafri, K. Abdullah, N. Mohd. Saleh
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Retrieval of the surface reflectance is important in the remotely sensed data analysis to obtain the atmospheric reflectance or atmospheric correction. The relationship between visible and mid infrared reflectance over land was investigated and developed in this study. The surface reflectances of the two visible bands were measured using a handheld spectroradiometer collected around Penang Island. In this study, we use the assumption that the 2.1 μm band is not affected by aerosol and it is transparent to most aerosol types (except dust). Therefore the satellite observed signal is the same as the surface signal in 2.1 μm band. The correlation between the surface reflectance measured by the spectroradiometer in the blue and red region and the 2.1 μm observed by the satellite has been established. We investigate five dates of Landsat TM scenes in this study. The finding obtained by this study indicates that the surface reflectance can be retrieved from the 2.1 μm band.Keywords: Surface Reflectance, Landsat TM, Aerosol, Spectroradiometer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11905518 Preservation of Isparta Yılan Kırkan (Yılan Kıran) Fountain within the Scope of Sustainability
Authors: Meryem Elif Çelebi Yakartepe, Ayşe Betül Gökarslan
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Sustainable architecture is an approach which accepts the climatic and tomographic data as a necessary preliminary data package by favoring the relationship between human and nature and which strives to use the sources economically. The reflection of sustainable architecture approach to preservation - restoration discipline is including the architectural inheritance to daily life with its unique or new function by restoring it.
The restoration decisions of Yılan Kırkan Fountain in Isparta province of Turkey is a good example of the works of sustainable architecture and the preservation of architectural inheritance. It is aimed that Yılan Kırkan Fountain, which is desolate nowadays with no function, to be restored by the local authorities and university, included in the daily life and continue its function.
Keywords: Conservation and Restoration, Sustainable Architecture, Movement Technique, Isparta Yılan Kırkan Fountain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33465517 Door Fan Test in Data Processing Center at Portopalo Test Site
Authors: F. Noto, M. Castro, R. Garraffo, An. Mirabella, A. Rizzo, G. Cuttone
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The door fan test is a verification procedure on the tightness of a room, necessary following the installation of saturation extinguishing systems and made mandatory according to the UNI 15004-1: 2019 standard whenever a gas extinguishing system is designed and installed. The door fan test was carried out at the Portopalo di Capo Passero headquarters of the Southern National Laboratories and highlighted how the Data Processing Center (CED) is perfectly up to standard, passing the door fan test in an excellent way. The Southern National Laboratories constitute a solid research reality, well established in the international scientific panorama. The CED in the Portopalo site has been expanded, so the extinguishing system has been expanded according to a detailed design. After checking the correctness of the design to verify the absence of air leaks, we carried out the door fan test. The activities of the Laboratori Nazionali del Sud (LNS) are mainly aimed at basic research in the field of Nuclear Physics, Nuclear and Particle Astrophysics. The Portopalo site will host some of the largest submarine wired scientific research infrastructures built in Europe and in the world, such as KM3NeT and EMSO ERIC; in particular, the site research laboratory in Portopalo will host the power supply and data acquisition systems of the underwater infrastructures, and a technological backbone will be created, unique in the Mediterranean, capable of allowing the connection, at abyssal depths, of dozens of real-time surveying and research structures of the marine environment deep.
Keywords: KM3Net, fire protection, door fan test, CED.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2205516 Improving Activity Recognition Classification of Repetitious Beginner Swimming Using a 2-Step Peak/Valley Segmentation Method with Smoothing and Resampling for Machine Learning
Authors: Larry Powell, Seth Polsley, Drew Casey, Tracy Hammond
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Human activity recognition (HAR) systems have shown positive performance when recognizing repetitive activities like walking, running, and sleeping. Water-based activities are a reasonably new area for activity recognition. However, water-based activity recognition has largely focused on supporting the elite and competitive swimming population, which already has amazing coordination and proper form. Beginner swimmers are not perfect, and activity recognition needs to support the individual motions to help beginners. Activity recognition algorithms are traditionally built around short segments of timed sensor data. Using a time window input can cause performance issues in the machine learning model. The window’s size can be too small or large, requiring careful tuning and precise data segmentation. In this work, we present a method that uses a time window as the initial segmentation, then separates the data based on the change in the sensor value. Our system uses a multi-phase segmentation method that pulls all peaks and valleys for each axis of an accelerometer placed on the swimmer’s lower back. This results in high recognition performance using leave-one-subject-out validation on our study with 20 beginner swimmers, with our model optimized from our final dataset resulting in an F-Score of 0.95.
Keywords: Time window, peak/valley segmentation, feature extraction, beginner swimming, activity recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1875515 A Model Predictive Control and Time Series Forecasting Framework for Supply Chain Management
Authors: Philip Doganis, Eleni Aggelogiannaki, Haralambos Sarimveis
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Model Predictive Control has been previously applied to supply chain problems with promising results; however hitherto proposed systems possessed no information on future demand. A forecasting methodology will surely promote the efficiency of control actions by providing insight on the future. A complete supply chain management framework that is based on Model Predictive Control (MPC) and Time Series Forecasting will be presented in this paper. The proposed framework will be tested on industrial data in order to assess the efficiency of the method and the impact of forecast accuracy on overall control performance of the supply chain. To this end, forecasting methodologies with different characteristics will be implemented on test data to generate forecasts that will serve as input to the Model Predictive Control module.Keywords: Forecasting, Model predictive control, production planning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19635514 Feature Based Unsupervised Intrusion Detection
Authors: Deeman Yousif Mahmood, Mohammed Abdullah Hussein
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The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of data mining is feature selection that helps in improving the efficiency, performance and prediction rate of proposed approach. This paper applies unsupervised K-means clustering algorithm with information gain (IG) for feature selection and reduction to build a network intrusion detection system. For our experimental analysis, we have used the new NSL-KDD dataset, which is a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. With a split of 60.0% for the training set and the remainder for the testing set, a 2 class classifications have been implemented (Normal, Attack). Weka framework which is a java based open source software consists of a collection of machine learning algorithms for data mining tasks has been used in the testing process. The experimental results show that the proposed approach is very accurate with low false positive rate and high true positive rate and it takes less learning time in comparison with using the full features of the dataset with the same algorithm.
Keywords: Information Gain (IG), Intrusion Detection System (IDS), K-means Clustering, Weka.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27625513 Urban Growth Analysis Using Multi-Temporal Satellite Images, Non-stationary Decomposition Methods and Stochastic Modeling
Authors: Ali Ben Abbes, ImedRiadh Farah, Vincent Barra
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Remotely sensed data are a significant source for monitoring and updating databases for land use/cover. Nowadays, changes detection of urban area has been a subject of intensive researches. Timely and accurate data on spatio-temporal changes of urban areas are therefore required. The data extracted from multi-temporal satellite images are usually non-stationary. In fact, the changes evolve in time and space. This paper is an attempt to propose a methodology for changes detection in urban area by combining a non-stationary decomposition method and stochastic modeling. We consider as input of our methodology a sequence of satellite images I1, I2, … In at different periods (t = 1, 2, ..., n). Firstly, a preprocessing of multi-temporal satellite images is applied. (e.g. radiometric, atmospheric and geometric). The systematic study of global urban expansion in our methodology can be approached in two ways: The first considers the urban area as one same object as opposed to non-urban areas (e.g. vegetation, bare soil and water). The objective is to extract the urban mask. The second one aims to obtain a more knowledge of urban area, distinguishing different types of tissue within the urban area. In order to validate our approach, we used a database of Tres Cantos-Madrid in Spain, which is derived from Landsat for a period (from January 2004 to July 2013) by collecting two frames per year at a spatial resolution of 25 meters. The obtained results show the effectiveness of our method.
Keywords: Multi-temporal satellite image, urban growth, Non-stationarity, stochastic modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14965512 Ensuring Consistency under the Snapshot Isolation
Authors: Carlos Roberto Valˆencio, F´abio Renato de Almeida, Thatiane Kawabata, Leandro Alves Neves, Julio Cesar Momente, Mario Luiz Tronco, Angelo Cesar Colombini
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By running transactions under the SNAPSHOT isolation we can achieve a good level of concurrency, specially in databases with high-intensive read workloads. However, SNAPSHOT is not immune to all the problems that arise from competing transactions and therefore no serialization warranty exists. We propose in this paper a technique to obtain data consistency with SNAPSHOT by using some special triggers that we named DAEMON TRIGGERS. Besides keeping the benefits of the SNAPSHOT isolation, the technique is specially useful for those database systems that do not have an isolation level that ensures serializability, like Firebird and Oracle. We describe all the anomalies that might arise when using the SNAPSHOT isolation and show how to preclude them with DAEMON TRIGGERS. Based on the methodology presented here, it is also proposed the creation of a new isolation level: DAEMON SNAPSHOT.
Keywords: Data consistency, serialization, snapshot.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21105511 Comparison between Open and Closed System for Dewatering with Geotextile: Field and Comparative Study
Authors: Matheus Müller, Delma Vidal
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The present paper aims to expose two techniques of dewatering for sludge, analyzing its operations and dewatering processes, aiming at improving the conditions of disposal of residues with high liquid content. It describes the field tests performed on two geotextile systems, a closed geotextile tube and an open geotextile drying bed, both of which are submitted to two filling cycles. The sludge used in the filling cycles for the field trials is from the water treatment plant of the Technological Center of Aeronautics – CTA, in São José dos Campos, Brazil. Data about volume and height abatement due to the dewatering and consolidation were collected per time, until it was observed constancy. With the laboratory analysis of the sludge allied to the data collected in the field, it was possible to perform a critical comparative study between the observed and the scientific literature, in this way, this paper expresses the data obtained and compares them with the bibliography. The tests were carried out on three fronts: field tests, including the filling cycles of the systems with the sludge from CTA, taking measurements of filling time per cycle and maximum filling height per cycle, heights against the abatement by dewatering of the systems over time; tests carried out in the laboratory, including the characterization of the sludge and removal of material samples from the systems to ascertain the solids content within the systems per time and; comparing the data obtained in the field and laboratory tests with the scientific literature. Through the study, it was possible to perceive that the process of densification of the material inside a closed system, such as the geotextile tube, occurs faster than the observed in the drying bed system. This process of accelerated densification can be brought about by the pumping pressure of the sludge in its filling and by the confinement of the residue through the permeable geotextile membrane (allowing water to pass through), accelerating the process of densification and dewatering by its own weight after the filling with sludge.
Keywords: Consolidation, dewatering, geotextile drying bed, geotextile tube.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6705510 Binary Mixture of Copper-Cobalt Ions Uptake by Zeolite using Neural Network
Authors: John Kabuba, Antoine Mulaba-Bafubiandi, Kim Battle
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In this study a neural network (NN) was proposed to predict the sorption of binary mixture of copper-cobalt ions into clinoptilolite as ion-exchanger. The configuration of the backpropagation neural network giving the smallest mean square error was three-layer NN with tangent sigmoid transfer function at hidden layer with 10 neurons, linear transfer function at output layer and Levenberg-Marquardt backpropagation training algorithm. Experiments have been carried out in the batch reactor to obtain equilibrium data of the individual sorption and the mixture of coppercobalt ions. The obtained modeling results have shown that the used of neural network has better adjusted the equilibrium data of the binary system when compared with the conventional sorption isotherm models.Keywords: Adsorption isotherm, binary system, neural network; sorption
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20315509 Prediction of Oxygen Transfer and Gas Hold-Up in Pneumatic Bioreactors Containing Viscous Newtonian Fluids
Authors: Caroline E. Mendes, Alberto C. Badino
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Pneumatic reactors have been widely employed in various sectors of the chemical industry, especially where are required high heat and mass transfer rates. This study aimed to obtain correlations that allow the prediction of gas hold-up (Ԑ) and volumetric oxygen transfer coefficient (kLa), and compare these values, for three models of pneumatic reactors on two scales utilizing Newtonian fluids. Values of kLa were obtained using the dynamic pressure-step method, while e was used for a new proposed measure. Comparing the three models of reactors studied, it was observed that the mass transfer was superior to draft-tube airlift, reaching e of 0.173 and kLa of 0.00904s-1. All correlations showed good fit to the experimental data (R2≥94%), and comparisons with correlations from the literature demonstrate the need for further similar studies due to shortage of data available, mainly for airlift reactors and high viscosity fluids.
Keywords: Bubble column, internal loop airlift, gas hold-up, kLa.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15145508 Analyses for Primary Coolant Pump Coastdown Phenomena for Jordan Research and Training Reactor
Authors: Yazan M. Alatrash, Han-ok Kang, Hyun-gi Yoon, Shen Zhang, Juhyeon Yoon
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Flow coastdown phenomena are very important to secure nuclear fuel integrity during loss of off-site power accidents. In this study, primary coolant flow coastdown phenomena are investigated for the Jordan Research and Training Reactor (JRTR) using a simulation software package, Modular Modeling System (MMS). Two MMS models are built. The first one is a simple model to investigate the characteristics of the primary coolant pump only. The second one is a model for a simulation of the Primary Coolant System (PCS) loop, in which all the detailed design data of the JRTR PCS system are modeled, including the geometrical arrangement data. The same design data for a PCS pump are used for both models. Coastdown curves obtained from the two models are compared to study the PCS loop coolant inertia effect on a flow coastdown. Results showed that the loop coolant inertia effect is found to be small in the JRTR PCS loop, i.e., about one second increases in a coastdown half time required to halve the coolant flow rate. The effects of different flywheel inertia on the flow coastdown are also investigated. It is demonstrated that the coastdown half time increases with the flywheel inertia linearly. The designed coastdown half time is proved to be well above the design requirement for the fuel integrity.
Keywords: Flow Coastdown, Loop Coolant Inertia, Modeling, Research Reactor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37845507 The Relationship between Military Expenditure, Military Personnel, Economic Growth, and the Environment
Authors: El Harbi Sana, Ben Afia Neila
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In this paper, we study the relationship between the military effort and pollution. A distinction is drawn between the direct and indirect impact of the military effort (military expenditure and military personnel) on pollution, which operates through the impact of military effort on per capita income and the resultant impact of income on pollution. Using the data of 121 countries covering the period 1980–2011, both the direct and indirect impacts of military effort on air pollution emissions are estimated. Our results show that the military effort is estimated to have a positive direct impact on per capita emissions. Indirect effects are found to be positive, the total effect of military effort on emissions is positive for all countries.Keywords: Military expenditure, military personnel, income, emissions of CO2 and panel data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19575506 Understanding and Political Participation in Constitutional Monarchy of Dusit District Residents
Authors: Sudaporn Arundee
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The purposes of this research were to study in three areas: 1) to study political understanding and participating of the constitutional monarchy, 2) to study the level of participation. This paper drew upon data collected from 395 Dusit residents by using questionnaire. In addition, a simple random sampling was utilized to collect data.
The findings revealed that 94 percent of respondents had a very good understanding of constitution monarchy with a mean of 4.8. However, the respondents overall had a very low level of participation with the mean score of 1.69 and standard deviation of .719.
Keywords: Constitution Monarchy, Political Understanding, Political Participating.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17645505 A method for Music Classification Based On Perceived Mood Detection for Indian Bollywood Music
Authors: Vallabha Hampiholi
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A lot of research has been done in the past decade in the field of audio content analysis for extracting various information from audio signal. One such significant information is the "perceived mood" or the "emotions" related to a music or audio clip. This information is extremely useful in applications like creating or adapting the play-list based on the mood of the listener. This information could also be helpful in better classification of the music database. In this paper we have presented a method to classify music not just based on the meta-data of the audio clip but also include the "mood" factor to help improve the music classification. We propose an automated and efficient way of classifying music samples based on the mood detection from the audio data. We in particular try to classify the music based on mood for Indian bollywood music. The proposed method tries to address the following problem statement: Genre information (usually part of the audio meta-data) alone does not help in better music classification. For example the acoustic version of the song "nothing else matters by Metallica" can be classified as melody music and thereby a person in relaxing or chill out mood might want to listen to this track. But more often than not this track is associated with metal / heavy rock genre and if a listener classified his play-list based on the genre information alone for his current mood, the user shall miss out on listening to this track. Currently methods exist to detect mood in western or similar kind of music. Our paper tries to solve the issue for Indian bollywood music from an Indian cultural context
Keywords: Mood, music classification, music genre, rhythm, music analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34575504 Streamflow Modeling for a Small Watershed Using Limited Hydrological Data
Authors: S. Chuenchooklin
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This research was conducted in the Pua Watershed whereas located in the Upper Nan River Basin in Nan province, Thailand. Nan River basin originated in Nan province that comprises of many tributary streams to produce as inflow to the Sirikit dam provided huge reservoir with the storage capacity of 9510 million cubic meters. The common problems of most watersheds were found i.e. shortage water supply for consumption and agriculture utilizations, deteriorate of water quality, flood and landslide including debris flow, and unstable of riverbank. The Pua Watershed is one of several small river basins that flow through the Nan River Basin. The watershed includes 404 km2 representing the Pua District, the Upper Nan Basin, or the whole Nan River Basin, of 61.5%, 18.2% or 1.2% respectively. The Pua River is a main stream producing all year streamflow supplying the Pua District and an inflow to the Upper Nan Basin. Its length approximately 56.3 kilometers with an average slope of the channel by 1.9% measured. A diversion weir namely Pua weir bound the plain and mountainous areas with a very steep slope of the riverbed to 2.9% and drainage area of 149 km2 as upstream watershed while a mild slope of the riverbed to 0.2% found in a river reach of 20.3 km downstream of this weir, which considered as a gauged basin. However, the major branch streams of the Pua River are ungauged catchments namely: Nam Kwang and Nam Koon with the drainage area of 86 and 35 km2 respectively. These upstream watersheds produce runoff through the 3-streams downstream of Pua weir, Jao weir, and Kang weir, with an averaged annual runoff of 578 million cubic meters. They were analyzed using both statistical data at Pua weir and simulated data resulted from the hydrologic modeling system (HEC–HMS) which applied for the remaining ungauged basins. Since the Kwang and Koon catchments were limited with lack of hydrological data included streamflow and rainfall. Therefore, the mathematical modeling: HEC-HMS with the Snyder-s hydrograph synthesized and transposed methods were applied for those areas using calibrated hydrological parameters from the upstream of Pua weir with continuously daily recorded of streamflow and rainfall data during 2008-2011. The results showed that the simulated daily streamflow and sum up as annual runoff in 2008, 2010, and 2011 were fitted with observed annual runoff at Pua weir using the simple linear regression with the satisfied correlation R2 of 0.64, 062, and 0.59, respectively. The sensitivity of simulation results were come from difficulty using calibrated parameters i.e. lag-time, coefficient of peak flow, initial losses, uniform loss rates, and missing some daily observed data. These calibrated parameters were used to apply for the other 2-ungauged catchments and downstream catchments simulated.
Keywords: Streamflow, hydrological model, ungauged catchments.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19775503 Ignition Delay Correlation for a Direct Injection Diesel Engine Fuelled with Automotive Diesel and Water Diesel Emulsion
Authors: K.Alkhulaifi, M. Hamdalla
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Most of ignition delay correlations studies have been developed in a constant volume bombs which cannot capture the dynamic variation in pressure and temperature during the ignition delay as in real engines. Watson, Assanis et. al. and Hardenberg and Hase correlations have been developed based on experimental data of diesel engines. However, they showed limited predictive ability of ignition delay when compared to experimental results. The objective of the study was to investigate the dependency of ignition delay time on engine brake power. An experimental investigation of the effect of automotive diesel and water diesel emulsion fuels on ignition delay under steady state conditions of a direct injection diesel engine was conducted. A four cylinder, direct injection naturally aspirated diesel engine was used in this experiment over a wide range of engine speeds and two engine loads. The ignition delay experimental data were compared with predictions of Assanis et. al. and Watson ignition delay correlations. The results of the experimental investigation were then used to develop a new ignition delay correlation. The newly developed ignition delay correlation has shown a better agreement with the experimental data than Assanis et. al. and Watson when using automotive diesel and water diesel emulsion fuels especially at low to medium engine speeds at both loads. In addition, the second derivative of cylinder pressure which is the most widely used method in determining the start of combustion was investigated.Keywords: gnition delay correlation, water diesel emulsion, direct injection diesel engine
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 57975502 A Review of Coverage and Routing for Wireless Sensor Networks
Authors: Hamid Barati, Ali Movaghar, Ali Barati, Arash Azizi Mazreah
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The special constraints of sensor networks impose a number of technical challenges for employing them. In this review, we study the issues and existing protocols in three areas: coverage and routing. We present two types of coverage problems: to determine the minimum number of sensor nodes that need to perform active sensing in order to monitor a certain area; and to decide the quality of service that can be provided by a given sensor network. While most routing protocols in sensor networks are data-centric, there are other types of routing protocols as well, such as hierarchical, location-based, and QoS-aware. We describe and compare several protocols in each group. We present several multipath routing protocols and single-path with local repair routing protocols, which are proposed for recovering from sensor node crashes. We also discuss some transport layer schemes for reliable data transmission in lossy wireless channels.Keywords: Sensor networks, Coverage, Routing, Robustness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16695501 Rule Insertion Technique for Dynamic Cell Structure Neural Network
Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin
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This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.
Keywords: Neural network, rule extraction, rule insertion, self-organizing map.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5105500 Contact Drying Simulation of Particulate Materials: A Comprehensive Approach
Authors: Marco Intelvi, Apolinar Picado, Joaquín Martínez
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In this work, simulation algorithms for contact drying of agitated particulate materials under vacuum and at atmospheric pressure were developed. The implementation of algorithms gives a predictive estimation of drying rate curves and bulk bed temperature during contact drying. The calculations are based on the penetration model to describe the drying process, where all process parameters such as heat and mass transfer coefficients, effective bed properties, gas and liquid phase properties are estimated with proper correlations. Simulation results were compared with experimental data from the literature. In both cases, simulation results were in good agreement with experimental data. Few deviations were identified and the limitations of the predictive capabilities of the models are discussed. The programs give a good insight of the drying behaviour of the analysed powders.Keywords: Agitated bed, Atmospheric pressure, Penetrationmodel, Vacuum
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22285499 Reference Architecture for Intelligent Enterprise Solutions
Authors: Shankar Kambhampaty, Harish Rohan Kambhampaty
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Data in IT systems in enterprises have been growing at phenomenal pace. This has provided opportunities to run analytics to gather intelligence on key business parameters that enable them to provide better products and services to customers. While there are several Artificial Intelligence/Machine Learning (AI/ML) and Business Intelligence (BI) tools and technologies available in marketplace to run analytics, there is a need for an integrated view when developing intelligent solutions in enterprises. This paper progressively elaborates a reference model for enterprise solutions, builds an integrated view of data, information and intelligence components and presents a reference architecture for intelligent enterprise solutions. Finally, it applies the reference architecture to an insurance organization. The reference architecture is the outcome of experience and insights gathered from developing intelligent solutions for several organizations.
Keywords: Architecture, model, intelligence, artificial intelligence, business intelligence, AI, BI, ML, analytics, enterprise.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12945498 EEG Signal Processing Methods to Differentiate Mental States
Authors: Sun H. Hwang, Young E. Lee, Yunhan Ga, Gilwon Yoon
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EEG is a very complex signal with noises and other bio-potential interferences. EOG is the most distinct interfering signal when EEG signals are measured and analyzed. It is very important how to process raw EEG signals in order to obtain useful information. In this study, the EEG signal processing techniques such as EOG filtering and outlier removal were examined to minimize unwanted EOG signals and other noises. The two different mental states of resting and focusing were examined through EEG analysis. A focused state was induced by letting subjects to watch a red dot on the white screen. EEG data for 32 healthy subjects were measured. EEG data after 60-Hz notch filtering were processed by a commercially available EOG filtering and our presented algorithm based on the removal of outliers. The ratio of beta wave to theta wave was used as a parameter for determining the degree of focusing. The results show that our algorithm was more appropriate than the existing EOG filtering.
Keywords: EEG, focus, mental state, outlier, signal processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1527