Search results for: Agricultural object detection
514 Medical Image Segmentation Using Deformable Models and Local Fitting Binary
Authors: B. Bagheri Nakhjavanlo, T. J. Ellis, P. Raoofi, J. Dehmeshki
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This paper presents a customized deformable model for the segmentation of abdominal and thoracic aortic aneurysms in CTA datasets. An important challenge in reliably detecting aortic aneurysm is the need to overcome problems associated with intensity inhomogeneities and image noise. Level sets are part of an important class of methods that utilize partial differential equations (PDEs) and have been extensively applied in image segmentation. A Gaussian kernel function in the level set formulation, which extracts the local intensity information, aids the suppression of noise in the extracted regions of interest and then guides the motion of the evolving contour for the detection of weak boundaries. The speed of curve evolution has been significantly improved with a resulting decrease in segmentation time compared with previous implementations of level sets. The results indicate the method is more effective than other approaches in coping with intensity inhomogeneities.Keywords: Abdominal and thoracic aortic aneurysms, intensityinhomogeneity, level sets, local fitting binary.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1806513 Performance Comparison of ADTree and Naive Bayes Algorithms for Spam Filtering
Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel
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Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.Keywords: Classification, data mining, spam filtering, naive Bayes, decision tree.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1485512 Urban Floods and Importance of Them in Cities Security Planning (Case Study: Dominant Watershed on Zavvareh City)
Authors: Jalil Emadi, Masoud Nasri, Ali Najafi, Yousef Moradi Shahgharyeh
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Development of cities and villages, agricultural farms and industrial regions in abutment and/or in the course of streams and rivers or in prone flood lands has been caused more notations in hydrology problems and city planning topics. In order to protection of cities against of flood damages, embankment construction is a desired and scientific method. The cities that located in arid zones may damage by floods periodically. Zavvareh city in Ardestan township(Isfahan province) with 7704 people located in Ardestan plain that has been damaged by floods that have flowed from dominant mountainous watersheds in past years with regard to return period. In this study, according to flowed floods toward Zavvareh city, was attempt to plan suitable hydraulic structures such as canals, bridges and collectors in order to collection, conduction and depletion of city surface runoff.Keywords: Flood, flood way, executive consideration, embankment, surface runoff network, Zavvareh.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1604511 On the Bootstrap P-Value Method in Identifying out of Control Signals in Multivariate Control Chart
Authors: O. Ikpotokin
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In any production process, every product is aimed to attain a certain standard, but the presence of assignable cause of variability affects our process, thereby leading to low quality of product. The ability to identify and remove this type of variability reduces its overall effect, thereby improving the quality of the product. In case of a univariate control chart signal, it is easy to detect the problem and give a solution since it is related to a single quality characteristic. However, the problems involved in the use of multivariate control chart are the violation of multivariate normal assumption and the difficulty in identifying the quality characteristic(s) that resulted in the out of control signals. The purpose of this paper is to examine the use of non-parametric control chart (the bootstrap approach) for obtaining control limit to overcome the problem of multivariate distributional assumption and the p-value method for detecting out of control signals. Results from a performance study show that the proposed bootstrap method enables the setting of control limit that can enhance the detection of out of control signals when compared, while the p-value method also enhanced in identifying out of control variables.
Keywords: Bootstrap control limit, p-value method, out-of-control signals, p-value, quality characteristics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1001510 Kinematic Parameters for Asa River Routing
Authors: A. O. Ogunlela, B. Adelodun
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Flood routing is used in estimating the travel time and attenuation of flood waves as they move downstream a river or channel. The routing procedure is usually classified as hydrologic or hydraulic. Hydraulic methods utilize the equations of continuity and motion. Kinematic routing, a hydraulic technique was used in routing Asa River at Ilorin. The river is of agricultural and industrial importance to Ilorin, the capital of Kwara State, Nigeria. This paper determines the kinematic parameters of kinematic wave velocity, time step, time required to traverse, weighting factor and change in length. Values obtained were 4.67 m/s, 19 secs, 21 secs, 0.75 and 100 m, respectively. These parameters adequately reflect the watershed and flow characteristics essential for the routing. The synthetic unit hydrograph was developed using the Natural Resources Conservation Service (NRCS) method. 24-hr 10yr, 25yr, 50yr and 100yr storm hydrographs were developed from the unit hydrograph using convolution procedures and the outflow hydrographs were obtained for each of 24-hr 10yr, 25yr, 50yr and 100yr indicating 0.11 m3/s, 0.10 m3/s, 0.10 m3/s and 0.10 m3/s attenuations respectively.
Keywords: Asa River, Kinematic parameters, Routing
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2287509 Determination of Water Pollution and Water Quality with Decision Trees
Authors: Çiğdem Bakır, Mecit Yüzkat
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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software used in the study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: Preprocessing of the data used, feature detection and classification. We tried to determine the success of our study with different accuracy metrics and the results were presented comparatively. In addition, we achieved approximately 98% success with the decision tree.
Keywords: Decision tree, water quality, water pollution, machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 226508 Estimation of the Drought Index Based on the Climatic Projections of Precipitation of the Uruguay River Basin
Authors: José Leandro Melgar Néris, Claudinéia Brazil, Luciane Teresa Salvi, Isabel Cristina Damin
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The impact the climate change is not recent, the main variable in the hydrological cycle is the sequence and shortage of a drought, which has a significant impact on the socioeconomic, agricultural and environmental spheres. This study aims to characterize and quantify, based on precipitation climatic projections, the rainy and dry events in the region of the Uruguay River Basin, through the Standardized Precipitation Index (SPI). The database is the image that is part of the Intercomparison of Model Models, Phase 5 (CMIP5), which provides condition prediction models, organized according to the Representative Routes of Concentration (CPR). Compared to the normal set of climates in the Uruguay River Watershed through precipitation projections, seasonal precipitation increases for all proposed scenarios, with a low climate trend. From the data of this research, the idea is that this article can be used to support research and the responsible bodies can use it as a subsidy for mitigation measures in other hydrographic basins.
Keywords: Drought index, climatic projections, precipitation of the Uruguay River Basin, Standardized Precipitation Index.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 574507 Real-time Laser Monitoring based on Pipe Detective Operation
Authors: Mongkorn Klingajay, Tawatchai Jitson
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The pipe inspection operation is the difficult detective performance. Almost applications are mainly relies on a manual recognition of defective areas that have carried out detection by an engineer. Therefore, an automation process task becomes a necessary in order to avoid the cost incurred in such a manual process. An automated monitoring method to obtain a complete picture of the sewer condition is proposed in this work. The focus of the research is the automated identification and classification of discontinuities in the internal surface of the pipe. The methodology consists of several processing stages including image segmentation into the potential defect regions and geometrical characteristic features. Automatic recognition and classification of pipe defects are carried out by means of using an artificial neural network technique (ANN) based on Radial Basic Function (RBF). Experiments in a realistic environment have been conducted and results are presented.Keywords: Artificial neural network, Radial basic function, Curve fitting, CCTV, Image segmentation, Data acquisition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1804506 Detection of Max. Optical Gain by Erbium Doped Fiber Amplifier
Authors: Abdulamgid.T. Bouzed, Suleiman. M. Elhamali
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The technical realization of data transmission using glass fiber began after the development of diode laser in year 1962. The erbium doped fiber amplifiers (EDFA's) in high speed networks allow information to be transmitted over longer distances without using of signal amplification repeaters. These kinds of fibers are doped with erbium atoms which have energy levels in its atomic structure for amplifying light at 1550nm. When a carried signal wave at 1550nm enters the erbium fiber, the light stimulates the excited erbium atoms which pumped with laser beam at 980nm as additional light. The wavelength and intensity of the semiconductor lasers depend on the temperature of active zone and the injection current. The present paper shows the effect of the diode lasers temperature and injection current on the optical amplification. From the results of in- and output power one may calculate the max. optical gain by erbium doped fiber amplifier.Keywords: Amplifier, erbium doped fiber, gain, lasers, temperature.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2122505 The Effects of Detector Spacing on Travel Time Prediction on Freeways
Authors: Piyali Chaudhuri, Peter T. Martin, Aleksandar Z. Stevanovic, Chongkai Zhu
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Loop detectors report traffic characteristics in real time. They are at the core of traffic control process. Intuitively, one would expect that as density of detection increases, so would the quality of estimates derived from detector data. However, as detector deployment increases, the associated operating and maintenance cost increases. Thus, traffic agencies often need to decide where to add new detectors and which detectors should continue receiving maintenance, given their resource constraints. This paper evaluates the effect of detector spacing on freeway travel time estimation. A freeway section (Interstate-15) in Salt Lake City metropolitan region is examined. The research reveals that travel time accuracy does not necessarily deteriorate with increased detector spacing. Rather, the actual location of detectors has far greater influence on the quality of travel time estimates. The study presents an innovative computational approach that delivers optimal detector locations through a process that relies on Genetic Algorithm formulation.Keywords: Detector, Freeway, Genetic algorithm, Travel timeestimate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1655504 Visualization of Latent Sweat Fingerprints Deposit on Paper by Infrared Radiation and Blue Light
Authors: Xiaochun Huang, Xuejun Zhao, Yun Zou, Feiyu Yang, Wenbin Liu, Nan Deng, Ming Zhang, Nengbin Cai
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A simple device termed infrared radiation (IR) was developed for rapid visualization of sweat fingerprints deposit on paper with blue light (450 nm, 11 W). In this approach, IR serves as the pretreatment device before the sweat fingerprints was illuminated by blue light. An annular blue light source was adopted for visualizing latent sweat fingerprints. Sample fingerprints were examined under various conditions after deposition, and experimental results indicate that the recovery rate of the latent sweat fingerprints is in the range of 50%-100% without chemical treatments. A mechanism for the observed visibility is proposed based on transportation and re-impregnation of fluorescer in paper at the region of water. And further exploratory experimental results gave the full support to the visible mechanism. Therefore, such a method as IR-pretreated in detecting latent fingerprints may be better for examination in the case where biological information of samples is needed for consequent testing.
Keywords: Forensic science, visualization, infrared radiation, blue light, latent sweat fingerprints, detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1454503 Biometric Steganography Using Variable Length Embedding
Authors: Souvik Bhattacharyya, Indradip Banerjee, Anumoy Chakraborty, Gautam Sanyal
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Recent growth in digital multimedia technologies has presented a lot of facilities in information transmission, reproduction and manipulation. Therefore, the concept of information security is one of the superior articles in the present day situation. The biometric information security is one of the information security mechanisms. It has the advantages as well as disadvantages. The biometric system is at risk to a range of attacks. These attacks are anticipated to bypass the security system or to suspend the normal functioning. Various hazards have been discovered while using biometric system. Proper use of steganography greatly reduces the risks in biometric systems from the hackers. Steganography is one of the fashionable information hiding technique. The goal of steganography is to hide information inside a cover medium like text, image, audio, video etc. through which it is not possible to detect the existence of the secret information. Here in this paper a new security concept has been established by making the system more secure with the help of steganography along with biometric security. Here the biometric information has been embedded to a skin tone portion of an image with the help of proposed steganographic technique.
Keywords: Biometrics, Skin tone detection, Series, Polynomial, Cover Image, Stego Image.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2651502 Genetic Content-Based MP3 Audio Watermarking in MDCT Domain
Authors: N. Moghadam, H. Sadeghi
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In this paper a novel scheme for watermarking digital audio during its compression to MPEG-1 Layer III format is proposed. For this purpose we slightly modify some of the selected MDCT coefficients, which are used during MPEG audio compression procedure. Due to the possibility of modifying different MDCT coefficients, there will be different choices for embedding the watermark into audio data, considering robustness and transparency factors. Our proposed method uses a genetic algorithm to select the best coefficients to embed the watermark. This genetic selection is done according to the parameters that are extracted from the perceptual content of the audio to optimize the robustness and transparency of the watermark. On the other hand the watermark security is increased due to the random nature of the genetic selection. The information of the selected MDCT coefficients that carry the watermark bits, are saves in a database for future extraction of the watermark. The proposed method is suitable for online MP3 stores to pursue illegal copies of musical artworks. Experimental results show that the detection ratio of the watermarks at the bitrate of 128kbps remains above 90% while the inaudibility of the watermark is preserved.Keywords: Content-Based Audio Watermarking, Genetic AudioWatermarking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1506501 Effects of Different Plant Densities on the Yield and Quality of Second Crop Sesame
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Sesame is one of the oldest and most important oil crops as main crop and second crop agriculture. This study was carried out to determine the effects of different inter- and intra-row spacings on the yield and yield components on second crop sesame; was set up in Antalya West Mediterranean Agricultural Research Institue in 2009. Muganlı 57 sesame cultivar was used as plant material. The field experiment was set up in a split plot design and row spacings (30, 40, 50, 60 and 70 cm) were assigned to the main plots and and intra-row spacings (5, 10, 20 and 30 cm) were assigned to the subplots. Seed yield, oil ratio, oil yield, protein ratio and protein yield were investigated. In general, wided inter row spacings and intra-row spacings, resulted in decreased seed yield, oil yield and protein yield. The highest seed yield, oil yield and protein yield (respectively, 1115.0 kg ha-1, 551.3 kg ha-1, 224.7 kg ha-1) were obtained from 30x5 cm plant density while the lowest seed yield, oil yield and protein yield (respectively, 677.0 kg ha-1, 327.0 kg ha-1, 130.0 kg ha-1) were recorded from 70x30 cm plant density. As a result, in terms of oil yield for second crop sesame agriculture, 30 cm row spacing, and 5 cm intra row spacing are the most suitable plant densities.Keywords: Sesamum indicum L., oil ratio, oil yield, protein ratio, protein yield
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4015500 Sparse Coding Based Classification of Electrocardiography Signals Using Data-Driven Complete Dictionary Learning
Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul
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In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.Keywords: Electrocardiogram, dictionary learning, sparse coding, classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2078499 Effect of Core Puncture Diameter on Bio-Char Kiln Efficiency
Authors: W. Intagun, T. Khamdaeng, P. Prom-ngarm, N. Panyoyai
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Biochar has been used as a soil amendment since it has high porous structure and has proper nutrients and chemical properties for plants. Product yields produced from biochar kiln are dependent on process parameters and kiln types used. The objective of this research is to investigate the effect of core puncture diameter on biochar kiln efficiency, i.e., yields of biochar and produced gas. Corncobs were used as raw material to produce biochar. Briquettes from agricultural wastes were used as fuel. Each treatment was performed by changing the core puncture diameter. From the experiment, it is revealed that the yield of biochar at the core puncture diameter of 3.18 mm, 4.76 mm, and 6.35 mm was 10.62 wt. %, 24.12 wt. %, and 12.24 wt. %, of total solid yields, respectively. The yield of produced gas increased with increasing the core puncture diameter. The maximum percentage by weight of the yield of produced gas was 81.53 wt. % which was found at the core puncture diameter of 6.35 mm. The core puncture diameter was furthermore found to affect the temperature distribution inside the kiln and its thermal efficiency. In conclusion, the high efficient biochar kiln can be designed and constructed by using the proper core puncture diameter.
Keywords: Anila stove, biochar, soil conditioning materials, temperature distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 939498 Automatic Detection of Proliferative Cells in Immunohistochemically Images of Meningioma Using Fuzzy C-Means Clustering and HSV Color Space
Authors: Vahid Anari, Mina Bakhshi
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Visual search and identification of immunohistochemically stained tissue of meningioma was performed manually in pathologic laboratories to detect and diagnose the cancers type of meningioma. This task is very tedious and time-consuming. Moreover, because of cell's complex nature, it still remains a challenging task to segment cells from its background and analyze them automatically. In this paper, we develop and test a computerized scheme that can automatically identify cells in microscopic images of meningioma and classify them into positive (proliferative) and negative (normal) cells. Dataset including 150 images are used to test the scheme. The scheme uses Fuzzy C-means algorithm as a color clustering method based on perceptually uniform hue, saturation, value (HSV) color space. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images.
Keywords: Positive cell, color segmentation, HSV color space, immunohistochemistry, meningioma, thresholding, fuzzy c-means.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 678497 The Effect of Seed Inoculation (Pseudomonas putida+Bacillus lentus) and Different Levels of Fertilizers on Yield and Yield Components of Wheat (Triticum aestivum L.) Cultivars
Authors: Hamid Abbasdokht , Ahmad Gholami
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In order to study of The Effect of seed inoculation with Pseudomonas putida+Bacillus lentus on yield and yield components of wheat (Triticum aestivum L.) cultivars, an experiment was carried out as factorial based on Randomized Complete Block Design (RCBD) in Agricultural Research Station of Shahrood University of Technology. Results showed that inoculation with Pseudomonas putida+Bacillus lentus promoted seed germination. Also, inoculation with Pseudomonas putida+Bacillus lentus significantly affected grain yield, Number of spikes per m2, Number of grain per spike and 1000-seed weight and There was not statistically significant difference between Chamran and Pishtaz cultivars . Finally, the dosages of chemical fertilizers currently applied in commercial wheat field in Iran (Shahrood region) could be reduced through proper combination of Pseudomonas putida+Bacillus lentus inoculation plus fertilization.Keywords: Seed inoculation, wheat, yield, yield components
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2148496 A Bi-Objective Preventive Healthcare Facility Network Design with Incorporating Cost and Time Saving
Authors: Mehdi Seifbarghy, Keyvan Roshan
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Main goal of preventive healthcare problems are at decreasing the likelihood and severity of potentially life-threatening illnesses by protection and early detection. The levels of establishment and staffing costs along with summation of the travel and waiting time that clients spent are considered as objectives functions of the proposed nonlinear integer programming model. In this paper, we have proposed a bi-objective mathematical model for designing a network of preventive healthcare facilities so as to minimize aforementioned objectives, simultaneously. Moreover, each facility acts as M/M/1 queuing system. The number of facilities to be established, the location of each facility, and the level of technology for each facility to be chosen are provided as the main determinants of a healthcare facility network. Finally, to demonstrate performance of the proposed model, four multi-objective decision making techniques are presented to solve the model.Keywords: Preventive healthcare problems, Non-linear integer programming models, Multi-objective decision making techniques
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1760495 Automatic Method for Exudates and Hemorrhages Detection from Fundus Retinal Images
Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar
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Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.Keywords: Diabetic retinopathy, fundus, CHT, exudates, hemorrhages.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2628494 Automatic Vehicle Identification by Plate Recognition
Authors: Serkan Ozbay, Ergun Ercelebi
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Automatic Vehicle Identification (AVI) has many applications in traffic systems (highway electronic toll collection, red light violation enforcement, border and customs checkpoints, etc.). License Plate Recognition is an effective form of AVI systems. In this study, a smart and simple algorithm is presented for vehicle-s license plate recognition system. The proposed algorithm consists of three major parts: Extraction of plate region, segmentation of characters and recognition of plate characters. For extracting the plate region, edge detection algorithms and smearing algorithms are used. In segmentation part, smearing algorithms, filtering and some morphological algorithms are used. And finally statistical based template matching is used for recognition of plate characters. The performance of the proposed algorithm has been tested on real images. Based on the experimental results, we noted that our algorithm shows superior performance in car license plate recognition.Keywords: Character recognizer, license plate recognition, plate region extraction, segmentation, smearing, template matching.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7572493 Thailand and Procession of Trafficking Human Beings (Women and Children)
Authors: Kawinphat Lertpongmanee
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The problems of trafficking human beings were continuously violent in Thailand. The problems occurred from a variety of factors such as unemployment, agricultural workers’ urban immigration, sex tour, attitude of materialism society, divorced family, unsavourily effected law, and officers’ ignorance. The purposes of this study were to study the structure, connection, a number of trafficking human beings in Thailand. Qualitative and quantitative and results of previous research were used in this research. The previous procurers, interested persons, experienced people, human beings-aiding organization, and women-children rights organization were interviewed in depth. The field was used in a variety of regions. The findings showed that the structure and connection of trafficking human beings and their values are $8,750 million. There are 240,000 people in trafficked human beings. The trend of trafficking human beings grows continuously. It is changed according to economic circumstance, society and culture, and law. The state must be aware of its problem. The law is enacted by adding high penalty for serious fear.
Keywords: Human Trade, Prostitution trafficking, trafficking in women and children.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1611492 Emission of Volatile Organic Compounds from the Residential Combustion of Pyrenean Oak and Black Poplar
Authors: M. Evtyugina, C. A. Alves, A. I. Calvo, T. Nunes, L. Tarelho, M. Duarte, S. O. Prozil
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Smoke from domestic wood burning has been identified as a major contributor to air pollution, motivating detailed emission measurements under controlled conditions. A series of experiments was performed to characterise the emissions from wood combustion in a fireplace and in a woodstove of two common species of trees grown in Spain: Pyrenean oak (Quercus pyrenaica) and black poplar (Populus nigra). Volatile organic compounds (VOCs) in the exhaust emissions were collected in Tedlar bags, re-sampled in sorbent tubes and analysed by thermal desorption-gas chromatography-flame ionisation detection. Pyrenean oak presented substantially higher emissions in the woodstove than in the fireplace, for the majority of compounds. The opposite was observed for poplar. Among the 45 identified species, benzene and benzenerelated compounds represent the most abundant group, followed by oxygenated VOCs and aliphatics. Emission factors obtained in this study are generally of the same order than those reported for residential experiments in the USA.Keywords: Fireplace, VOC emissions, woodstove.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1755491 ADABeV: Automatic Detection of Abnormal Behavior in Video-surveillance
Authors: Nour Charara, Iman Jarkass, Maria Sokhn, Elena Mugellini, Omar Abou Khaled
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Intelligent Video-Surveillance (IVS) systems are being more and more popular in security applications. The analysis and recognition of abnormal behaviours in a video sequence has gradually drawn the attention in the field of IVS, since it allows filtering out a large number of useless information, which guarantees the high efficiency in the security protection, and save a lot of human and material resources. We present in this paper ADABeV, an intelligent video-surveillance framework for event recognition in crowded scene to detect the abnormal human behaviour. This framework is attended to be able to achieve real-time alarming, reducing the lags in traditional monitoring systems. This architecture proposal addresses four main challenges: behaviour understanding in crowded scenes, hard lighting conditions, multiple input kinds of sensors and contextual-based adaptability to recognize the active context of the scene.Keywords: Behavior recognition, Crowded scene, Data fusion, Pattern recognition, Video-surveillance
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3624490 New Regression Model and I-Kaz Method for Online Cutting Tool Wear Monitoring
Authors: Jaharah A. Ghani, Muhammad Rizal, Ahmad Sayuti, Mohd Zaki Nuawi, Mohd Nizam Ab. Rahman, Che Hassan Che Haron
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This study presents a new method for detecting the cutting tool wear based on the measured cutting force signals using the regression model and I-kaz method. The detection of tool wear was done automatically using the in-house developed regression model and 3D graphic presentation of I-kaz 3D coefficient during machining process. The machining tests were carried out on a CNC turning machine Colchester Master Tornado T4 in dry cutting condition, and Kistler 9255B dynamometer was used to measure the cutting force signals, which then stored and displayed in the DasyLab software. The progression of the cutting tool flank wear land (VB) was indicated by the amount of the cutting force generated. Later, the I-kaz was used to analyze all the cutting force signals from beginning of the cut until the rejection stage of the cutting tool. Results of the IKaz analysis were represented by various characteristic of I-kaz 3D coefficient and 3D graphic presentation. The I-kaz 3D coefficient number decreases when the tool wear increases. This method can be used for real time tool wear monitoring.Keywords: mathematical model, I-kaz method, tool wear
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2387489 Discussing Embedded versus Central Machine Learning in Wireless Sensor Networks
Authors: Anne-Lena Kampen, Øivind Kure
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Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.
Keywords: Central ML, embedded machine learning, energy consumption, local ML, Wireless Sensor Networks, WSN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 814488 Fault Diagnosis of Nonlinear Systems Using Dynamic Neural Networks
Authors: E. Sobhani-Tehrani, K. Khorasani, N. Meskin
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This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems. Unlike most FD techniques, the proposed solution simultaneously accomplishes fault detection, isolation, and identification (FDII) within a unified diagnostic module. At the core of this solution is a bank of adaptive neural parameter estimators (NPE) associated with a set of singleparameter fault models. The NPEs continuously estimate unknown fault parameters (FP) that are indicators of faults in the system. Two NPE structures including series-parallel and parallel are developed with their exclusive set of desirable attributes. The parallel scheme is extremely robust to measurement noise and possesses a simpler, yet more solid, fault isolation logic. On the contrary, the series-parallel scheme displays short FD delays and is robust to closed-loop system transients due to changes in control commands. Finally, a fault tolerant observer (FTO) is designed to extend the capability of the NPEs to systems with partial-state measurement.
Keywords: Hybrid fault diagnosis, Dynamic neural networks, Nonlinear systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2212487 Design of Electromagnetic Drive Module for Micro-gyroscope
Authors: Nan-Chyuan Tsai, Jiun-Sheng Liou, Chih-Che Lin, Tuan Li
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For micro-gyroscopes, the angular rate detection components have to oscillate forwards and backwards alternatively. An innovative design of micro-electromagnetic drive module is proposed to make a Π-type disc reciprocally and efficiently rotate within a certain of angular interval. Twelve Electromagnetic poles enclosing the thin disc are designed to provide the magnetic drive power. Isotropic etching technique is employed to fabricate the high-aspect-ratio trench, so that the contact angle of wire against trench can be increased and the potential defect of cavities and pores within the wire can be prevented. On the other hand, a Π-type thin disc is designed to conduct the pitch motion as an angular excitation, in addition to spinning, is exerted on the gyroscope. The efficacy of the micro-magnetic drive module is verified by the commercial software, Ansoft Maxewll. In comparison with the conventional planar windings in micro-scale systems, the magnetic drive force is increased by 150%.
Keywords: Micro-gyroscope, micro-electromagnetic, micro actuator.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1473486 Can Smart Meters Create Smart Behaviour?
Authors: Candice Moy, Damien Guirco, Thomas Boyle
Abstract:
Intelligent technologies are increasingly facilitating sustainable water management strategies in Australia. While this innovation can present clear cost benefits to utilities through immediate leak detection and deference of capital costs, the impact of this technology on households is less distinct. By offering real-time engagement and detailed end-use consumption breakdowns, there is significant potential for demand reduction as a behavioural response to increased information. Despite this potential, passive implementation without well-planned residential engagement strategies is likely to result in a lost opportunity. This paper begins this research process by exploring the effect of smart water meters through the lens of three behaviour change theories. The Theory of Planned Behaviour (TPB), Belief Revision theory (BR) and Practice Theory emphasise different variables that can potentially influence and predict household water engagements. In acknowledging the strengths of each theory, the nuances and complexity of household water engagement can be recognised which can contribute to effective planning for residential smart meter engagement strategies.
Keywords: Behaviour, information, household, smart meters, water.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1854485 An Inductive Coupling Based CMOS Wireless Powering Link for Implantable Biomedical Applications
Authors: Lei Yao, Jia Hao Cheong, Rui-Feng Xue, Minkyu Je
Abstract:
A closed-loop controlled wireless power transmission circuit block for implantable biomedical applications is described in this paper. The circuit consists of one front-end rectifier, power management sub-block including bandgap reference and low drop-out regulators (LDOs) as well as transmission power detection / feedback circuits. Simulation result shows that the front-end rectifier achieves 80% power efficiency with 750-mV single-end peak-to-peak input voltage and 1.28-V output voltage under load current of 4 mA. The power management block can supply 1.8mA average load current under 1V consuming only 12μW power, which is equivalent to 99.3% power efficiency. The wireless power transmission block described in this paper achieves a maximum power efficiency of 80%. The wireless power transmission circuit block is designed and implemented using UMC 65-nm CMOS/RF process. It occupies 1 mm × 1.2 mm silicon area.
Keywords: Implantable biomedical devices, wireless power transfer, LDO, rectifier, closed-loop power control
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2277