Search results for: power quality recognition
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 16868

Search results for: power quality recognition

16268 Load Flow Analysis of 5-IEEE Bus Test System Using Matlab

Authors: H. Abaal, R. Skouri

Abstract:

A power flow analysis is a steady-state study of power grid. The goal of power flow analysis is to determine the voltages, currents, and real and reactive power flows in a system under a given load conditions. In this paper, the load flow analysis program by Newton Raphson polar coordinates Method is developed. The effectiveness of the developed program is evaluated through a simple 5-IEEE test system bus by simulations using MATLAB.

Keywords: power flow analysis, Newton Raphson polar coordinates method

Procedia PDF Downloads 603
16267 Efficient Use of Power Light-Emitting Diode Chips in the Main Lighting System and in Generating Heat in Intelligent Buildings

Authors: Siamak Eskandari, Neda Ebadi

Abstract:

Among common electronic parts which have been invented and have made a great revolution in the lighting system through the world, certainly LEDs have no rival. These small parts with their very low power consumption, very dazzling and powerful light and small size and with their extremely high lifetime- compared to incandescent bulbs and compact fluorescent lamp (CFLs) have undoubtedly revolutionized the lighting industry of the world. Based on conducted studies and experiments, in addition to their acceptable light and low power consumption -compared to incandescent bulbs and CFLs-, they have very low and in some cases zero environmental pollution and negative effects on human beings. Because of their longevity, in the case of using high-quality circuits and proper and consistent use of LEDs in conventional and intelligent buildings, there will be no need to replace the burnout lamps, for a long time (10 years). In this study which was conducted on 10-watt power LEDs with suitable heatsink/cooling, considerable amount of heat was generated during lighting after 5 minutes and 45 seconds. The temperature rose to above 99 degrees Celsius and this amount of heat can raise the water temperature to 60 degrees Celsius and more. Based on conducted experiments, this can provide the heat required for bathing, washing, radiators (in cold seasons) easily and only by imposing very low cost and it will be a big step in the optimization of energy consumption in the future.

Keywords: energy, light, water, optimization of power LED

Procedia PDF Downloads 153
16266 Approaches to Reduce the Complexity of Mathematical Models for the Operational Optimization of Large-Scale Virtual Power Plants in Public Energy Supply

Authors: Thomas Weber, Nina Strobel, Thomas Kohne, Eberhard Abele

Abstract:

In context of the energy transition in Germany, the importance of so-called virtual power plants in the energy supply continues to increase. The progressive dismantling of the large power plants and the ongoing construction of many new decentralized plants result in great potential for optimization through synergies between the individual plants. These potentials can be exploited by mathematical optimization algorithms to calculate the optimal application planning of decentralized power and heat generators and storage systems. This also includes linear or linear mixed integer optimization. In this paper, procedures for reducing the number of decision variables to be calculated are explained and validated. On the one hand, this includes combining n similar installation types into one aggregated unit. This aggregated unit is described by the same constraints and target function terms as a single plant. This reduces the number of decision variables per time step and the complexity of the problem to be solved by a factor of n. The exact operating mode of the individual plants can then be calculated in a second optimization in such a way that the output of the individual plants corresponds to the calculated output of the aggregated unit. Another way to reduce the number of decision variables in an optimization problem is to reduce the number of time steps to be calculated. This is useful if a high temporal resolution is not necessary for all time steps. For example, the volatility or the forecast quality of environmental parameters may justify a high or low temporal resolution of the optimization. Both approaches are examined for the resulting calculation time as well as for optimality. Several optimization models for virtual power plants (combined heat and power plants, heat storage, power storage, gas turbine) with different numbers of plants are used as a reference for the investigation of both processes with regard to calculation duration and optimality.

Keywords: CHP, Energy 4.0, energy storage, MILP, optimization, virtual power plant

Procedia PDF Downloads 178
16265 Improving the Statistics Nature in Research Information System

Authors: Rajbir Cheema

Abstract:

In order to introduce an integrated research information system, this will provide scientific institutions with the necessary information on research activities and research results in assured quality. Since data collection, duplication, missing values, incorrect formatting, inconsistencies, etc. can arise in the collection of research data in different research information systems, which can have a wide range of negative effects on data quality, the subject of data quality should be treated with better results. This paper examines the data quality problems in research information systems and presents the new techniques that enable organizations to improve their quality of research information.

Keywords: Research information systems (RIS), research information, heterogeneous sources, data quality, data cleansing, science system, standardization

Procedia PDF Downloads 158
16264 Performance Analysis of Different Power Electronics Structures for Electric Vehicles (EVs)

Authors: Sekkak Abdelmalek

Abstract:

The aim of this paper is to establish an energy balance of the drivetrain of a low power electric vehicle (around ten kilowatts). The study is based on two topologies of power electronics converter, the voltage source inverter and cascaded H-Bridge inverter. For each of these solutions, two voltage levels are studied for the drivetrain. At first a discussion of cascaded H-Bridge inverters will be performed on the potential benefits of this structure for its use to other functions such as macroscopic batteries management system. In a second step, the performances of the traction chain are compared according to the structure of the power converter and the voltage level of the traction chain.

Keywords: power electronics, static converters, cascaded H-Bridge, traction chain, efficiency, losses, batteries balancing

Procedia PDF Downloads 512
16263 Performance Comparison of a Low Cost Air Quality Sensor with a Commercial Electronic Nose

Authors: Ünal Kızıl, Levent Genç, Sefa Aksu, Ahmet Tapınç

Abstract:

The Figaro AM-1 sensor module which employs TGS 2600 model gas sensor in air quality assessment was used. The system was coupled with a microprocessor that enables sensor module to create warning message via telephone. This low cot sensor system’s performance was compared with a Diagnose II commercial electronic nose system. Both air quality sensor and electronic nose system employ metal oxide chemical gas sensors. In the study experimental setup, data acquisition methods for electronic nose system, and performance of the low cost air quality system were evaluated and explained.

Keywords: air quality, electronic nose, environmental quality, gas sensor

Procedia PDF Downloads 444
16262 Comparative Study of Line Voltage Stability Indices for Voltage Collapse Forecasting in Power Transmission System

Authors: H. H. Goh, Q. S. Chua, S. W. Lee, B. C. Kok, K. C. Goh, K. T. K. Teo

Abstract:

At present, the evaluation of voltage stability assessment experiences sizeable anxiety in the safe operation of power systems. This is due to the complications of a strain power system. With the snowballing of power demand by the consumers and also the restricted amount of power sources, therefore, the system has to perform at its maximum proficiency. Consequently, the noteworthy to discover the maximum ability boundary prior to voltage collapse should be undertaken. A preliminary warning can be perceived to evade the interruption of power system’s capacity. The effectiveness of line voltage stability indices (LVSI) is differentiated in this paper. The main purpose of the indices is used to predict the proximity of voltage instability of the electric power system. On the other hand, the indices are also able to decide the weakest load buses which are close to voltage collapse in the power system. The line stability indices are assessed using the IEEE 14 bus test system to validate its practicability. Results demonstrated that the implemented indices are practically relevant in predicting the manifestation of voltage collapse in the system. Therefore, essential actions can be taken to dodge the incident from arising.

Keywords: critical line, line outage, line voltage stability indices (LVSI), maximum loadability, voltage collapse, voltage instability, voltage stability analysis

Procedia PDF Downloads 360
16261 Thermodynamic Evaluation of Coupling APR-1400 with a Thermal Desalination Plant

Authors: M. Gomaa Abdoelatef, Robert M. Field, Lee, Yong-Kwan

Abstract:

Growing human populations have placed increased demands on water supplies and a heightened interest in desalination infrastructure. Key elements of the economics of desalination projects are thermal and electrical inputs. With growing concerns over the use of fossil fuels to (indirectly) supply these inputs, coupling of desalination with nuclear power production represents a significant opportunity. Individually, nuclear and desalination technologies have a long history and are relatively mature. For desalination, Reverse Osmosis (RO) has the lowest energy inputs. However, the economically driven output quality of the water produced using RO, which uses only electrical inputs, is lower than the output water quality from thermal desalination plants. Therefore, modern desalination projects consider that RO should be coupled with thermal desalination technologies (MSF, MED, or MED-TVC) with attendant steam inputs to permit blending to produce various qualities of water. A large nuclear facility is well positioned to dispatch large quantities of both electrical and thermal power. This paper considers the supply of thermal energy to a large desalination facility to examine heat balance impact on the nuclear steam cycle. The APR1400 nuclear plant is selected as prototypical from both a capacity and turbine cycle heat balance perspective to examine steam supply and the impact on electrical output. Extraction points and quantities of steam are considered parametrically along with various types of thermal desalination technologies to form the basis for further evaluations of economically optimal approaches to the interface of nuclear power production with desalination projects. In our study, the thermodynamic evaluation will be executed by DE-TOP which is the IAEA desalination program, it is approved to be capable of analyzing power generation systems coupled to desalination systems through various steam extraction positions, taking into consideration the isolation loop between the APR-1400 and the thermal desalination plant for safety concern.

Keywords: APR-1400, desalination, DE-TOP, IAEA, MSF, MED, MED-TVC, RO

Procedia PDF Downloads 532
16260 Optimizing the Capacity of a Convolutional Neural Network for Image Segmentation and Pattern Recognition

Authors: Yalong Jiang, Zheru Chi

Abstract:

In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

Procedia PDF Downloads 154
16259 Flexible Alternative Current Transmission System Impact on Grid Stability and Power Markets

Authors: Abdulrahman M. Alsuhaibani, Martin Maken

Abstract:

FACTS devices have great influence on the grid stability and power markets price. Recently, there is intent to integrate a large scale of renewable energy sources to the power system which in turn push the power system to operate closer to the security limits. This paper discusses the power system stability and reliability improvement that could be achieved by using FACTS. There is a comparison between FACTS devices to evaluate their performance for different functions. A case study has also been made about its effect on reducing generation cost and minimizing transmission losses which have good impact on efficient and economic operation of electricity markets

Keywords: FACTS, grid stability, spot price, OPF

Procedia PDF Downloads 159
16258 Concept, Modules and Objectives of the Syllabus Course: Small Power Plants and Renewable Energy Sources

Authors: Rade M. Ciric, Nikola L. J. Rajakovic

Abstract:

This paper presents a curriculum of the subject small power plants and renewable energy sources, dealing with the concept of distributed generation, renewable energy sources, hydropower, wind farms, geothermal power plants, cogeneration plants, biogas plants of agriculture and animal origin, solar power and fuel cells. The course is taught the manner of connecting small power plants to the grid, the impact of small generators on the distribution system, as well as economic, environmental and legal aspects of operation of distributed generators.

Keywords: distributed generation, renewable energy sources, energy policy, curriculum

Procedia PDF Downloads 357
16257 Keypoint Detection Method Based on Multi-Scale Feature Fusion of Attention Mechanism

Authors: Xiaoxiao Li, Shuangcheng Jia, Qian Li

Abstract:

Keypoint detection has always been a challenge in the field of image recognition. This paper proposes a novelty keypoint detection method which is called Multi-Scale Feature Fusion Convolutional Network with Attention (MFFCNA). We verified that the multi-scale features with the attention mechanism module have better feature expression capability. The feature fusion between different scales makes the information that the network model can express more abundant, and the network is easier to converge. On our self-made street sign corner dataset, we validate the MFFCNA model with an accuracy of 97.8% and a recall of 81%, which are 5 and 8 percentage points higher than the HRNet network, respectively. On the COCO dataset, the AP is 71.9%, and the AR is 75.3%, which are 3 points and 2 points higher than HRNet, respectively. Extensive experiments show that our method has a remarkable improvement in the keypoint recognition tasks, and the recognition effect is better than the existing methods. Moreover, our method can be applied not only to keypoint detection but also to image classification and semantic segmentation with good generality.

Keywords: keypoint detection, feature fusion, attention, semantic segmentation

Procedia PDF Downloads 119
16256 Improved Feature Extraction Technique for Handling Occlusion in Automatic Facial Expression Recognition

Authors: Khadijat T. Bamigbade, Olufade F. W. Onifade

Abstract:

The field of automatic facial expression analysis has been an active research area in the last two decades. Its vast applicability in various domains has drawn so much attention into developing techniques and dataset that mirror real life scenarios. Many techniques such as Local Binary Patterns and its variants (CLBP, LBP-TOP) and lately, deep learning techniques, have been used for facial expression recognition. However, the problem of occlusion has not been sufficiently handled, making their results not applicable in real life situations. This paper develops a simple, yet highly efficient method tagged Local Binary Pattern-Histogram of Gradient (LBP-HOG) with occlusion detection in face image, using a multi-class SVM for Action Unit and in turn expression recognition. Our method was evaluated on three publicly available datasets which are JAFFE, CK, SFEW. Experimental results showed that our approach performed considerably well when compared with state-of-the-art algorithms and gave insight to occlusion detection as a key step to handling expression in wild.

Keywords: automatic facial expression analysis, local binary pattern, LBP-HOG, occlusion detection

Procedia PDF Downloads 170
16255 Optimized Brain Computer Interface System for Unspoken Speech Recognition: Role of Wernicke Area

Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

Abstract:

In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: brain-computer interface, speech recognition, artificial neural network, electroencephalography, EEG, wernicke area

Procedia PDF Downloads 272
16254 The Wear Recognition on Guide Surface Based on the Feature of Radar Graph

Authors: Youhang Zhou, Weimin Zeng, Qi Xie

Abstract:

Abstract: In order to solve the wear recognition problem of the machine tool guide surface, a new machine tool guide surface recognition method based on the radar-graph barycentre feature is presented in this paper. Firstly, the gray mean value, skewness, projection variance, flat degrees and kurtosis features of the guide surface image data are defined as primary characteristics. Secondly, data Visualization technology based on radar graph is used. The visual barycentre graphical feature is demonstrated based on the radar plot of multi-dimensional data. Thirdly, a classifier based on the support vector machine technology is used, the radar-graph barycentre feature and wear original feature are put into the classifier separately for classification and comparative analysis of classification and experiment results. The calculation and experimental results show that the method based on the radar-graph barycentre feature can detect the guide surface effectively.

Keywords: guide surface, wear defects, feature extraction, data visualization

Procedia PDF Downloads 519
16253 Investigation of Interlayer Shear Effects in Asphalt Overlay on Existing Rigid Airfield Pavement Using Digital Image Correlation

Authors: Yuechao Lei, Lei Zhang

Abstract:

The interface shear between asphalt overlay and existing rigid airport pavements occurs due to differences in the mechanical properties of materials subjected to aircraft loading. Interlayer contact influences the mechanical characteristics of the asphalt overlay directly. However, the effective interlayer relative displacement obtained accurately using existing displacement sensors of the loading apparatus remains challenging. This study aims to utilize digital image correlation technology to enhance the accuracy of interfacial contact parameters by obtaining effective interlayer relative displacements. Composite structure specimens were prepared, and fixtures for interlayer shear tests were designed and fabricated. Subsequently, a digital image recognition scheme for required markers was designed and optimized. Effective interlayer relative displacement values were obtained through image recognition and calculation of surface markers on specimens. Finite element simulations validated the mechanical response of composite specimens with interlayer shearing. Results indicated that an optimized marking approach using the wall mending agent for surface application and color coding enhanced the image recognition quality of marking points on the specimen surface. Further image extraction provided effective interlayer relative displacement values during interlayer shear, thereby improving the accuracy of interface contact parameters. For composite structure specimens utilizing Styrene-Butadiene-Styrene (SBS) modified asphalt as the tack coat, the corresponding maximum interlayer shear stress strength was 0.6 MPa, and fracture energy was 2917 J/m2. This research provides valuable insights for investigating the impact of interlayer contact in composite pavement structures on the mechanical characteristics of asphalt overlay.

Keywords: interlayer contact, effective relative displacement, digital image correlation technology, composite pavement structure, asphalt overlay

Procedia PDF Downloads 48
16252 Host-Assisted Delivery of a Model Drug to Genomic DNA: Key Information From Ultrafast Spectroscopy and in Silico Study

Authors: Ria Ghosh, Soumendra Singh, Dipanjan Mukherjee, Susmita Mondal, Monojit Das, Uttam Pal, Aniruddha Adhikari, Aman Bhushan, Surajit Bose, Siddharth Sankar Bhattacharyya, Debasish Pal, Tanusri Saha-Dasgupta, Maitree Bhattacharyya, Debasis Bhattacharyya, Asim Kumar Mallick, Ranjan Das, Samir Kumar Pal

Abstract:

Drug delivery to a target without adverse effects is one of the major criteria for clinical use. Herein, we have made an attempt to explore the delivery efficacy of SDS surfactant in a monomer and micellar stage during the delivery of the model drug, Toluidine Blue (TB) from the micellar cavity to DNA. Molecular recognition of pre-micellar SDS encapsulated TB with DNA occurs at a rate constant of k1 ~652 s 1. However, no significant release of encapsulated TB at micellar concentration was observed within the experimental time frame. This originated from the higher binding affinity of TB towards the nano-cavity of SDS at micellar concentration which does not allow the delivery of TB from the nano-cavity of SDS micelles to DNA. Thus, molecular recognition controls the extent of DNA recognition by TB which in turn modulates the rate of delivery of TB from SDS in a concentration-dependent manner.

Keywords: DNA, drug delivery, micelle, pre-micelle, SDS, toluidine blue

Procedia PDF Downloads 113
16251 Simulation Based Performance Comparison of Different Control Methods of ZSI Feeding Industrial Drives

Authors: Parag Nihawan, Ravinder Singh Bhatia, Dinesh Kumar Jain

Abstract:

Industrial drives are source of serious power quality problems. In this, two typical industrial drives have been dealt with, namely, FOC induction motor drives and DTC induction motor drive. The Z-source inverter is an emerging topology of power electronic converters which is capable of buck boost characteristics. The performances of different control methods based Z-source inverters feeding these industrial drives have been investigated, in this work. The test systems have been modeled and simulated in MATLAB/SIMULINK. The results obtained after carrying out these simulations have been used to draw the conclusions.

Keywords: Z-source inverter, total harmonic distortion, direct torque control, field orientation control

Procedia PDF Downloads 582
16250 A Review of Strategies for Enhancing the Quality of Engineering Education in Zimbabwean Universities

Authors: Bhekisisa Nyoni, Nomakhosi Ndiweni, Annatoria Chinyama

Abstract:

The aim of this paper was to explore ways to enhance the quality of higher education with a bias towards engineering education in Zimbabwe universities. A search through relevant literature was conducted looking at both international and local scholars. It also involved reviewing the Dakar Framework for Action and Incheon Declaration and Framework for Action plans for education for sustainable development. Goals were set for 2030 as a standard for quality to be adopted by all countries in improving access as well as the quality of education from early childhood and through to adult learning. Despite the definition of quality being difficult to express due to diverse expectations from different stakeholders, the view of quality adopted is based on the World Education Forum’s propositions on quality education going beyond the classroom experience. It considers factors such as learning environment, governance and management, and teacher caliber. The study concludes by illustrating that the quality of engineering education in Zimbabwe has come a long way. It has made strides in increasing access and variety to education though at the expense of quality in its totality. To improve the quality of engineering education, programs have been introduced to promote the professionalism of lecturers, such as industrial secondment and professional development courses.

Keywords: engineering education, quality of education, professional development, industrial secondment

Procedia PDF Downloads 182
16249 Impact of Microwave and Air Velocity on Drying Kinetics and Rehydration of Potato Slices

Authors: Caiyun Liu, A. Hernandez-Manas, N. Grimi, E. Vorobiev

Abstract:

Drying is one of the most used methods for food preservation, which extend shelf life of food and makes their transportation, storage and packaging easier and more economic. The commonly dried method is hot air drying. However, its disadvantages are low energy efficiency and long drying times. Because of the high temperature during the hot air drying, the undesirable changes in pigments, vitamins and flavoring agents occur which result in degradation of the quality parameters of the product. Drying process can also cause shrinkage, case hardening, dark color, browning, loss of nutrients and others. Recently, new processes were developed in order to avoid these problems. For example, the application of pulsed electric field provokes cell membrane permeabilisation, which increases the drying kinetics and moisture diffusion coefficient. Microwave drying technology has also several advantages over conventional hot air drying, such as higher drying rates and thermal efficiency, shorter drying time, significantly improved product quality and nutritional value. Rehydration kinetics of dried product is a very important characteristic of dried products. Current research has indicated that the rehydration ratio and the coefficient of rehydration are dependent on the processing conditions of drying. The present study compares the efficiency of two processes (1: room temperature air drying, 2: microwave/air drying) in terms of drying rate, product quality and rehydration ratio. In this work, potato slices (≈2.2g) with a thickness of 2 mm and diameter of 33mm were placed in the microwave chamber and dried. Drying kinetics and drying rates of different methods were determined. The process parameters included inlet air velocity (1 m/s, 1.5 m/s, 2 m/s) and microwave power (50 W, 100 W, 200 W and 250 W) were studied. The evolution of temperature during microwave drying was measured. The drying power had a strong effect on drying rate, and the microwave-air drying resulted in 93% decrease in the drying time when the air velocity was 2 m/s and the power of microwave was 250 W. Based on Lewis model, drying rate constants (kDR) were determined. It was observed an increase from kDR=0.0002 s-1 to kDR=0.0032 s-1 of air velocity of 2 m/s and microwave/air (at 2m/s and 250W) respectively. The effective moisture diffusivity was calculated by using Fick's law. The results show an increase of effective moisture diffusivity from 7.52×10-11 to 2.64×10-9 m2.s-1 for air velocity of 2 m/s and microwave/air (at 2m/s and 250W) respectively. The temperature of the potato slices increased for higher microwaves power, but decreased for higher air velocity. The rehydration ratio, defined as the weight of the the sample after rehydration per the weight of dried sample, was determined at different water temperatures (25℃, 50℃, 75℃). The rehydration ratio increased with the water temperature and reached its maximum at the following conditions: 200 W for the microwave power, 2 m/s for the air velocity and 75°C for the water temperature. The present study shows the interest of microwave drying for the food preservation.

Keywords: drying, microwave, potato, rehydration

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16248 A Comparative Study of k-NN and MLP-NN Classifiers Using GA-kNN Based Feature Selection Method for Wood Recognition System

Authors: Uswah Khairuddin, Rubiyah Yusof, Nenny Ruthfalydia Rosli

Abstract:

This paper presents a comparative study between k-Nearest Neighbour (k-NN) and Multi-Layer Perceptron Neural Network (MLP-NN) classifier using Genetic Algorithm (GA) as feature selector for wood recognition system. The features have been extracted from the images using Grey Level Co-Occurrence Matrix (GLCM). The use of GA based feature selection is mainly to ensure that the database used for training the features for the wood species pattern classifier consists of only optimized features. The feature selection process is aimed at selecting only the most discriminating features of the wood species to reduce the confusion for the pattern classifier. This feature selection approach maintains the ‘good’ features that minimizes the inter-class distance and maximizes the intra-class distance. Wrapper GA is used with k-NN classifier as fitness evaluator (GA-kNN). The results shows that k-NN is the best choice of classifier because it uses a very simple distance calculation algorithm and classification tasks can be done in a short time with good classification accuracy.

Keywords: feature selection, genetic algorithm, optimization, wood recognition system

Procedia PDF Downloads 545
16247 Speech Detection Model Based on Deep Neural Networks Classifier for Speech Emotions Recognition

Authors: A. Shoiynbek, K. Kozhakhmet, P. Menezes, D. Kuanyshbay, D. Bayazitov

Abstract:

Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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16246 Potential Micro Hydro at Irrigation Canal in the Gorontalo Province and Modeling Setling Basin for Reduction of Sedimentation Effect

Authors: Arifin Matoka, Nadjamuddin Harun, Salama Manjang, M. Arsyad Thaha

Abstract:

Along irrigation canals in certain areas falling water level height is have potential for micro hydro power plant (MHP), which generally MHP potential valley away from society consumer of electricity and needed a long conductor cable, so that with the MHP Irrigation is ideal are typical with an Open Flume type turbines. This study is divided into two phases research phase of the potential power that exist in irrigation channels at the Gorontalo Province and stages solution sedimentation effects. The total power generated in the irrigation channel of the results of this study at 781.83 Kw, it is quite significant for the 1737 rural households on average consumes 450 watt per household. In the field of observation, sedimentation lifting effect on the quality of electric power, at which time the turbid sediment concentrations occur significant voltage fluctuations causing damage to some household electrical appliances such as electronic equipment and lighting. This problem is solution by modeling the sedimentation tub (setling basin) to reduce sedimentation thus olso can reduce the regulation load control equipment which can minimize the cost of investment and maintenance.

Keywords: irrigation canals, microhydro powerplant, sedimentation, Gorontalo Province

Procedia PDF Downloads 581
16245 Experimental and Computational Fluid Dynamics Analysis of Horizontal Axis Wind Turbine

Authors: Saim Iftikhar Awan, Farhan Ali

Abstract:

Wind power has now become one of the most important resources of renewable energy. The machine which extracts kinetic energy from wind is wind turbine. This work is all about the electrical power analysis of horizontal axis wind turbine to check the efficiency of different configurations of wind turbines to get maximum output and comparison of experimental and Computational Fluid Dynamics (CFD) results. Different experiments have been performed to obtain that configuration with the help of which we can get the maximum electrical power output by changing the different parameters like the number of blades, blade shape, wind speed, etc. in first step experimentation is done, and then the similar configuration is designed in 3D CAD software. After a series of experiments, it has been found that the turbine with four blades at an angle of 75° gives maximum power output and increase in wind speed increases the power output. The models designed on CAD software are imported on ANSYS-FLUENT to predict mechanical power. This mechanical power is then converted into electrical power, and the results were approximately the same in both cases. In the end, a comparison has been done to compare the results of experiments and ANSYS-FLUENT.

Keywords: computational analysis, power efficiency, wind energy, wind turbine

Procedia PDF Downloads 159
16244 A Supervised Learning Data Mining Approach for Object Recognition and Classification in High Resolution Satellite Data

Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

Abstract:

Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

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16243 Highly Accurate Target Motion Compensation Using Entropy Function Minimization

Authors: Amin Aghatabar Roodbary, Mohammad Hassan Bastani

Abstract:

One of the defects of stepped frequency radar systems is their sensitivity to target motion. In such systems, target motion causes range cell shift, false peaks, Signal to Noise Ratio (SNR) reduction and range profile spreading because of power spectrum interference of each range cell in adjacent range cells which induces distortion in High Resolution Range Profile (HRRP) and disrupt target recognition process. Thus Target Motion Parameters (TMPs) effects compensation should be employed. In this paper, such a method for estimating TMPs (velocity and acceleration) and consequently eliminating or suppressing the unwanted effects on HRRP based on entropy minimization has been proposed. This method is carried out in two major steps: in the first step, a discrete search method has been utilized over the whole acceleration-velocity lattice network, in a specific interval seeking to find a less-accurate minimum point of the entropy function. Then in the second step, a 1-D search over velocity is done in locus of the minimum for several constant acceleration lines, in order to enhance the accuracy of the minimum point found in the first step. The provided simulation results demonstrate the effectiveness of the proposed method.

Keywords: automatic target recognition (ATR), high resolution range profile (HRRP), motion compensation, stepped frequency waveform technique (SFW), target motion parameters (TMPs)

Procedia PDF Downloads 152
16242 Mastering Digitization: A Quality-Adapted Digital Transformation Model

Authors: Franziska Schaefer, Marlene Kuhn, Heiner Otten

Abstract:

In the very near future, digitization will be the main challenge a company has to master to survive in a highly competitive market. Developing the right transformation strategy by considering all relevant aspects determines the success or failure of a company. Especially the digital focus on the customer plays a key role in creating sustainable competitive advantages, also leading to new tasks within the quality management. Therefore, quality management needs to be particularly addressed to support the upcoming digital change. In this paper, we present an analysis of existing digital transformation approaches and derive a transformation strategy from a quality management perspective. We identify and classify different transformation dimensions and assess their relevance to quality management tasks, resulting in a quality-adapted digital transformation model. Furthermore, we introduce applicable and customized quality management methods to support the presented digital transformation tasks. With our developed model we provide a digital transformation guideline from a quality perspective to master future disruptive changes.

Keywords: digital transformation, digitization, quality management, strategy

Procedia PDF Downloads 480
16241 Modeling and Design of Rectenna for Low Power Medical Implants

Authors: Madhav Pant, Khem N. Poudel

Abstract:

Wireless power transfer is continuously becoming more powerful and compact in medical implantable devices and the wide range of applications. A rectenna is designed for wireless power transfer technique that can be applied to medical implant devices. The experiment is performed using ANSYS HFSS, a full wave electromagnetic simulation. The dipole antenna combinations operating at 2.4 GHz are used for wireless power transfer and the maximum DC voltage reception by the implant considering International Commission on Non-Ionizing Radiation Protection (ICNIRP) regulation. The power receiving dipole antenna is placed inside the cylindrical geometry having the similar properties of the human body at the frequency of 2.4 GHz. Our design can provide the power at the depth of 5 mm skin and 5mm of bone for the implant. The voltage doubler/quadrupler rectifier in ANSYS Simplorer is used to calculate the exact DC current utilized by implant inside the human body. The qualitative design and analysis of this wireless power transfer method could also be used for other biomedical implants systems such as cardiac pacemaker, insulin pump, and retinal implants.

Keywords: dipole antenna, medical implants, wireless power transfer, rectifier

Procedia PDF Downloads 172
16240 The Analogue of a Property of Pisot Numbers in Fields of Formal Power Series

Authors: Wiem Gadri

Abstract:

This study delves into the intriguing properties of Pisot and Salem numbers within the framework of formal Laurent series over finite fields, a domain where these numbers’ spectral charac-teristics, Λm(β) and lm(β), have yet to be fully explored. Utilizing a methodological approach that combines algebraic number theory with the analysis of power series, we extend the foundational work of Erdos, Joo, and Komornik to this new setting. Our research uncovers bounds for lm(β), revealing how these depend on the degree of the minimal polynomial of β and thus offering a novel characterization of Pisot and Salem formal power series. The findings significantly contribute to our understanding of these numbers, highlighting their distribution and properties in the context of formal power series. This investigation not only bridges number theory with formal power series analysis but also sets the stage for further interdisciplinary research in these areas.

Keywords: Pisot numbers, Salem numbers, formal power series, over a finite field

Procedia PDF Downloads 51
16239 A Study on Water Quality Parameters of Pond Water for Better Management of Pond

Authors: Dona Grace Jeyaseeli

Abstract:

Water quality conditions in a pond are controlled by both natural processes and human influences. Natural factors such as the source of the pond water and the types of rock and soil in the pond watershed will influence some water quality characteristics. These factors are difficult to control but usually cause few problems. Instead, most serious water quality problems originate from land uses or other activities near or in the pond. The effects of these activities can often be minimized through proper management and early detection of problems through testing. In the present study a survey of three ponds in Coimbatore city, Tamilnadu, India were analyzed and found that water quality problems in their ponds, ranging from muddy water to fish kills. Unfortunately, most pond owners have never tested their ponds, and water quality problems are usually only detected after they cause a problem. Hence the present study discusses some common water quality parameters that may cause problems in ponds and how to detect through testing for better management of pond.

Keywords: water quality, pond, test, problem

Procedia PDF Downloads 506