Search results for: image processing techniques

Authors: C. V. Aravinda, H. N. Prakash

Abstract:

In this paper, we tried to convey fusion and state of art pertaining to SIL character recognition systems. In the first step, the text is preprocessed and normalized to perform the text identification correctly. The second step involves extracting relevant and informative features. The third step implements the classification decision. The three stages which involved are Data acquisition and preprocessing, Feature extraction, and Classification. Here we concentrated on two techniques to obtain features, Feature Extraction & Feature Selection. Edge-hinge distribution is a feature that characterizes the changes in direction of a script stroke in handwritten text. The edge-hinge distribution is extracted by means of a windowpane that is slid over an edge-detected binary handwriting image. Whenever the mid pixel of the window is on, the two edge fragments (i.e. connected sequences of pixels) emerging from this mid pixel are measured. Their directions are measured and stored as pairs. A joint probability distribution is obtained from a large sample of such pairs. Despite continuous effort, handwriting identification remains a challenging issue, due to different approaches use different varieties of features, having different. Therefore, our study will focus on handwriting recognition based on feature selection to simplify features extracting task, optimize classification system complexity, reduce running time and improve the classification accuracy.

Keywords: word segmentation and recognition, character recognition, optical character recognition, hand written character recognition, South Indian languages

Procedia PDF Downloads 494

Authors: Meltem Işık, Fatma Gür, İbrahim Kılıç

Abstract:

This study aims to explore the effects of hemsball shooting techniques on the fine motor skill level of children with hearing disabilities. A total number of 26 children with hearing disabilities, ages ranging between 7 and 11 and which were equally divided into experimental group and control group participated in the study. In this context, an exercise training program dedicated to hemsball shooting techniques was introduced to the experimental group 3 days a week in one hour sessions for a period of 10 weeks. BOT-2 fine motor skills test which includes three dimensions (fine motor accuracy, fine motor task completion, and dexterity) was selected as the data collection method. Descriptive statistics along with two-factor ANOVA which was focused on repetitive measurements of the differences between pretest and posttest scores of both groups were used in the analysis of the data collected. The results of this study showed that hemsball shooting techniques have a statistically significant effect on the fine motor skill level.

Keywords: hemsball shooting techniques, BOT-2 test, fine motor skills, hearing disabilities

Procedia PDF Downloads 353

Authors: Jagroop Singh Sidhu, Buta Singh

Abstract:

A low computational deblocking filter including three frequency related modes (smooth mode, intermediate mode, and non-smooth mode for low-frequency, mid-frequency, and high frequency regions, respectively) is proposed. The suggested approach requires zero additions, zero subtractions, zero multiplications (for intermediate region), no divisions (for non-smooth region) and no comparison. The suggested method thus keeps the computation lower and thus suitable for image coding systems based on blocks. Comparison of average number of operations for smooth, non-smooth, intermediate (per pixel vector for each block) using filter suggested by Chen and the proposed method filter suggests that the proposed filter keeps the computation lower and is thus suitable for fast processing algorithms.

Keywords: blocking artifacts, computational complexity, non-smooth, intermediate, smooth

Procedia PDF Downloads 462

Authors: Dingding Chen, Kazuo Arakawa, Masakazu Uchino, Changheng Xu

Abstract:

Vacuum assisted resin transfer moulding (VARTM) is a promising manufacture process for making large and complex fiber reinforced composite structures. However, the complexity of the flow of the resin in the infusion stage usually leads to nonuniform property distribution of the produced composite part. In order to control the flow of the resin, the situation of flow should be mastered. For the safety of the usage of the produced composite in practice, the understanding of the property distribution is essential. In this paper, we did some trials on monitoring the resin infusion stage and evaluation for the fiber volume fraction distribution of the VARTM produced composite using the digital image correlation methods. The results show that 3D-DIC is valid on monitoring the resin infusion stage and it is possible to use 2D-DIC to estimate the distribution of the fiber volume fraction on a FRP plate.

Keywords: digital image correlation, VARTM, FRP, fiber volume fraction

Procedia PDF Downloads 342

Authors: Sergio Tovar-Pérez, Sebastian Töpfer, Markus Gräfe

Abstract:

The work proposes a technique that decreases the detection acquisition time of quantum holography schemes down to one-third; this allows the possibility to image moving objects. Since its invention, quantum holography with undetected photon schemes has gained interest in the scientific community. This is mainly due to its ability to tailor the detected wavelengths according to the needs of the scheme implementation. Yet this wavelength flexibility grants the scheme a wide range of possible applications; an important matter was yet to be addressed. Since the scheme uses digital phase-shifting techniques to retrieve the information of the object out of the interference pattern, it is necessary to acquire a set of at least four images of the interference pattern along with well-defined phase steps to recover the full object information. Hence, the imaging method requires larger acquisition times to produce well-resolved images. As a consequence, the measurement of moving objects remains out of the reach of the imaging scheme. This work presents the use and implementation of a spatial light modulator along with a digital holographic technique called quasi-parallel phase-shifting. This technique uses the spatial light modulator to build a structured phase image consisting of a chessboard pattern containing the different phase steps for digitally calculating the object information. Depending on the reduction in the number of needed frames, the acquisition time reduces by a significant factor. This technique opens the door to the implementation of the scheme for moving objects. In particular, the application of this scheme in imaging alive specimens comes one step closer.

Keywords: quasi-parallel phase shifting, quantum imaging, quantum holography, quantum metrology

Procedia PDF Downloads 114

Authors: Parashram Jakappa Patil

Abstract:

India is the global leader in world cashew business and cashew-nut industry is one of the important food processing industries in world. However India is the largest producer, processor, exporter and importer eschew in the world. India is providing cashew to the rest of the world. India is meeting world demand of cashew. India has a tremendous potential of cashew production and export to other countries. Every year India earns more than 2000 cores rupees through cashew trade. Cashew industry is one of the important small scale industries in the country which is playing significant role in rural development. It is generating more than 400000 jobs at remote area and 95% cashew worker are women, it is giving income to poor cashew farmers, majority cashew processing units are small and cottage, it is helping to stop migration from young farmers for employment opportunities, it is motivation rural entrepreneurship development and it is also helping to environment protection etc. Hence India cashew business is very important agribusiness in India which has potential make inclusive development. World Bank and IMF recognized cashew-nut industry is one the important tool for poverty eradication at global level. It shows important of cashew business and its strong existence in India. In spite of such huge potential cashew processing industry is facing different problems such as lack of infrastructure ability, lack of supply of raw cashew, lack of availability of finance, collection of raw cashew, unavailability of warehouse, marketing of cashew kernels, lack of technical knowledge and especially processing technology and packaging of finished products. This industry has great prospects such as scope for more cashew cultivation and cashew production, employment generation, formation of cashew processing units, alcohols production from cashew apple, shield oil production, rural development, poverty elimination, development of social and economic backward class and environment protection etc. This industry has domestic as well as foreign market; India has tremendous potential in this regard. The cashew is a poor men’s crop but rich men’s food. The cashew is a source of income and livelihood for poor farmers. Cashew-nut industry may play very important role in the development of hilly region. The objectives of this paper are to identify problems of cashew processing and use of processing technology, problems of cashew kernel packaging, evolving of cashew processing technology over the year and its impact on final product and impact of good processing by adopting appropriate technology packaging on international trade of cashew-nut. The most important problem of cashew processing industry is that is processing and packaging. Bad processing reduce the quality of cashew kernel at large extent especially broken of cashew kernel which has very less price in market compare to whole cashew kernel and not eligible for export. On the other hand if there is no good packaging of cashew kernel will get moisture which destroy test of it. International trade of cashew-nut is depend of two things one is cashew processing and other is packaging. This study has strong relevance because cashew-nut industry is the labour oriented, where processing technology is not playing important role because 95% processing work is manual. Hence processing work was depending on physical performance of worker which makes presence of large workforce inevitable. There are many cashew processing units closed because they are not getting sufficient work force. However due to advancement in technology slowly this picture is changing and processing work get improve. Therefore it is interesting to explore all the aspects in context of cashew processing and packaging of cashew business.

Keywords: cashew, processing technology, packaging, international trade, change

Procedia PDF Downloads 422

Authors: L. Yu, W. K. Li, S. K. Ong, A. Y. C. Nee

Abstract:

In this paper, a scalable augmented reality framework for handheld devices is presented. The presented framework is enabled by using a server-client data communication structure, in which the search for tracking targets among a database of images is performed on the server-side while pixel-wise 3D tracking is performed on the client-side, which, in this case, is a handheld mobile device. Image search on the server-side adopts a residual-enhanced image descriptors representation that gives the framework a scalability property. The tracking algorithm on the client-side is based on a gravity-aligned feature descriptor which takes the advantage of a sensor-equipped mobile device and an optimized intensity-based image alignment approach that ensures the accuracy of 3D tracking. Automatic content streaming is achieved by using a key-frame selection algorithm, client working phase monitoring and standardized rules for content communication between the server and client. The recognition accuracy test performed on a standard dataset shows that the method adopted in the presented framework outperforms the Bag-of-Words (BoW) method that has been used in some of the previous systems. Experimental test conducted on a set of video sequences indicated the real-time performance of the tracking system with a frame rate at 15-30 frames per second. The presented framework is exposed to be functional in practical situations with a demonstration application on a campus walk-around.

Keywords: augmented reality framework, server-client model, vision-based tracking, image search

Procedia PDF Downloads 275

Authors: L. I. Izhar, T. Stathaki, K. Howell

Abstract:

Analyzing and interpreting of thermograms have been increasingly employed in the diagnosis and monitoring of diseases thanks to its non-invasive, non-harmful nature and low cost. In this paper, a novel system is proposed to improve diagnosis and monitoring of morphoea skin disorder based on integration with the published lines of Blaschko. In the proposed system, image registration based on global and local registration methods are found inevitable. This paper presents a modified normalized gradient cross-correlation (NGC) method to reduce large geometrical differences between two multimodal images that are represented by smooth gray edge maps is proposed for the global registration approach. This method is improved further by incorporating an iterative-based normalized cross-correlation coefficient (NCC) method. It is found that by replacing the final registration part of the NGC method where translational differences are solved in the spatial Fourier domain with the NCC method performed in the spatial domain, the performance and robustness of the NGC method can be greatly improved. It is shown in this paper that the hybrid NGC method not only outperforms phase correlation (PC) method but also improved misregistration due to translation, suffered by the modified NGC method alone for thermograms with ill-defined jawline. This also demonstrates that by using the gradients of the gray edge maps and a hybrid technique, the performance of the PC based image registration method can be greatly improved.

Keywords: Blaschko’s lines, image registration, morphoea, thermal imaging

Procedia PDF Downloads 310

Authors: Ayadi Aya, Ghorbel Oussama, M. Obeid Abdulfattah, Abid Mohamed

Abstract:

Nowadays, many wireless sensor networks have been distributed in the real world to collect valuable raw sensed data. The challenge is to extract high-level knowledge from this huge amount of data. However, the identification of outliers can lead to the discovery of useful and meaningful knowledge. In the field of wireless sensor networks, an outlier is defined as a measurement that deviates from the normal behavior of sensed data. Many detection techniques of outliers in WSNs have been extensively studied in the past decade and have focused on classic based algorithms. These techniques identify outlier in the real transaction dataset. This survey aims at providing a structured and comprehensive overview of the existing researches on classification based outlier detection techniques as applicable to WSNs. Thus, we have identified key hypotheses, which are used by these approaches to differentiate between normal and outlier behavior. In addition, this paper tries to provide an easier and a succinct understanding of the classification based techniques. Furthermore, we identified the advantages and disadvantages of different classification based techniques and we presented a comparative guide with useful paradigms for promoting outliers detection research in various WSN applications and suggested further opportunities for future research.

Keywords: bayesian networks, classification-based approaches, KPCA, neural networks, one-class SVM, outlier detection, wireless sensor networks

Procedia PDF Downloads 497

Authors: M. Jebali, M. Jemni

Abstract:

This work is the part of vision based hand gesture recognition system for Natural Human Computer Interface. Hand tracking and segmentation are the primary steps for any hand gesture recognition system. The aim of this paper is to develop robust and efficient hand segmentation algorithm such as an input to another system which attempt to bring the HCI performance nearby the human-human interaction, by modeling an intelligent sign language recognition system based on prediction in the context of dialogue between the system (avatar) and the interlocutor. For the purpose of hand segmentation, an overcoming occlusion approach has been proposed for superior results for detection of hand from an image.

Keywords: HCI, sign language recognition, object tracking, hand segmentation

Procedia PDF Downloads 412

Authors: Tatsuya Kato, Masanobu Nagata, Hidetoshi Nakashima, Kazunori Matsuo

Abstract:

Localization of mobile robots are important tasks for developing autonomous mobile robots. This paper proposes a method to estimate positions of a mobile robot using an omnidirectional camera on the robot. Landmarks for points of references are set up on a field where the robot works. The omnidirectional camera which can obtain 360 [deg] around images takes photographs of these landmarks. The positions of the robots are estimated from directions of these landmarks that are extracted from the images by image processing. This method can obtain the robot positions without accumulative position errors. Accuracy of the estimated robot positions by the proposed method are evaluated through some experiments. The results show that it can obtain the positions with small standard deviations. Therefore the method has possibilities of more accurate localization by tuning of appropriate offset parameters.

Keywords: mobile robots, localization, omnidirectional camera, estimating positions

Procedia PDF Downloads 442

Authors: M. T. Z. Butt, T. Ahmad, N. A. Siddiqui

Abstract:

Commercially SA 516 Grade 70 is frequently used for the manufacturing of pressure vessels, boilers and storage tanks etc. in fabrication industry. Heat input is the major parameter during welding that may bring significant changes in the microstructure as well as the mechanical properties. Different welding technique has different heat input rate per unit surface area. Materials with large thickness are dealt with different combination of welding techniques to achieve required mechanical properties. In the present research two schemes: Scheme 1: SMAW (Shielded Metal Arc Welding) & GTAW (Gas Tungsten Arc Welding) and Scheme 2: SMAW & SAW (Submerged Arc Welding) of hybrid welding techniques have been studied. The purpose of these schemes was to study hybrid welding effect on the microstructure and mechanical properties of the weldment, heat affected zone and base metal area. It is significant to note that the thickness of base plate was 12 mm, also welding conditions and parameters were set according to ASME Section IX. It was observed that two different hybrid welding techniques performed on two different plates demonstrated that the mechanical properties of both schemes are more or less similar. It means that the heat input, welding techniques and varying welding operating conditions & temperatures did not make any detrimental effect on the mechanical properties. Hence, the hybrid welding techniques mentioned in the present study are favorable to implicate for the industry using the plate thickness around 12 mm thick.

Keywords: grade 70, GTAW, hybrid welding, SAW, SMAW

Procedia PDF Downloads 339

Authors: Samaneh Nadali, Masrah Azrifah Azmi Murad, Nurfadhlina Mohammad Sharef

Abstract:

Sarcasm is a common phenomenon in social media which is a nuanced form of language for stating the opposite of what is implied. Due to the intentional ambiguity, analysis of sarcasm is a difficult task not only for a machine but even for a human. Although sarcasm detection has an important effect on sentiment, it is usually ignored in social media analysis because sarcasm analysis is too complicated. While there is a few systems exist which can detect sarcasm, almost no work has been carried out on a study and the review of the existing work in this area. This survey presents a nearly full image of sarcasm detection techniques and the related fields with brief details. The main contributions of this paper include the illustration of the recent trend of research in the sarcasm analysis and we highlight the gaps and propose a new framework that can be explored.

Keywords: sarcasm detection, sentiment analysis, social media, sarcasm analysis

Procedia PDF Downloads 458

Authors: P. L. D. N. M. de Silva, S. G. Edirisinghe, R. Weerasuriya

Abstract:

High peak-to-average power ratio (PAPR) is a concern of orthogonal frequency division multiplexing (OFDM) based visible light communication (VLC) systems. Discrete Fourier Transform spread (DFT-s) OFDM is an alternative single carrier modulation scheme which would address this concern. Employing channel coding techniques is another mechanism to reduce the PAPR. Previous research has been conducted to study the impact of these techniques separately. However, to the best of the knowledge of the authors, no study has been done so far to identify the improvement which can be harnessed by hybridizing these two techniques for VLC systems. Therefore, this is a novel study area under this research. In addition, channel coding techniques such as Polar codes and Turbo codes have been tested in the VLC domain. However, other efficient techniques such as Hamming coding and Convolutional coding have not been studied too. Therefore, the authors present the impact of the hybrid of DFT-s OFDM and Channel coding (Hamming coding and Convolutional coding) on PAPR in VLC systems using Matlab simulations.

Keywords: convolutional coding, discrete Fourier transform spread orthogonal frequency division multiplexing, hamming coding, peak-to-average power ratio, visible light communications

Procedia PDF Downloads 154

Authors: Victor A. Okenyi, Kehinde A. Alawode

Abstract:

Corrosion of reinforcement in concrete structures remains a durability issue in structural engineering with the increasing cost of repair and maintenance. The mechanism and factors influencing reinforcement corrosion in concrete with various electrochemical monitoring techniques including non-destructive, destructive techniques and the roles of sensors have been reviewed with the aim of determining the monitoring technique that proved most effective in determining corrosion parameters and more practicable for the assessment of concrete durability. Electrochemical impedance spectroscopy (EIS) and linear polarization resistance (LPR) techniques showed great performance in evaluating corrosion kinetics and corrosion rate, respectively, while the gravimetric weight loss (GWL) technique provided accurate measurements. However, no single monitoring technique showed to be the ultimate technique, and this calls for more research work in the development of more dynamic monitoring tools capable of considering all possible corrosion factors in the corrosion monitoring process.

Keywords: corrosion, concrete structures, durability, non-destructive technique, sensor

Procedia PDF Downloads 182

Authors: Walid Cherif

Abstract:

Data mining has, over recent years, seen big advances because of the spread of internet, which generates everyday a tremendous volume of data, and also the immense advances in technologies which facilitate the analysis of these data. In particular, classification techniques are a subdomain of Data Mining which determines in which group each data instance is related within a given dataset. It is used to classify data into different classes according to desired criteria. Generally, a classification technique is either statistical or machine learning. Each type of these techniques has its own limits. Nowadays, current data are becoming increasingly heterogeneous; consequently, current classification techniques are encountering many difficulties. This paper defines new measure functions to quantify the resemblance between instances and then combines them in a new approach which is different from actual algorithms by its reliability computations. Results of the proposed approach exceeded most common classification techniques with an f-measure exceeding 97% on the IRIS Dataset.

Keywords: data mining, knowledge discovery, machine learning, similarity measurement, supervised classification

Procedia PDF Downloads 465

Authors: Aymen Bouzid, Jihen Ben Smida

Abstract:

In this paper, we propose to prove the importance of the application of blind source separation methods on remote sensing data in order to index multispectral images. The proposed method starts with Gabor Filtering and the application of a Blind Source Separation to get a more effective representation of the information contained on the observation images. After that, a feature vector is extracted from each image in order to index them. Experimental results show the superior performance of this approach.

Keywords: blind source separation, content based image retrieval, feature extraction multispectral, satellite images

Procedia PDF Downloads 403

Authors: M. Ahmadi, M. Kafil, H. Ebrahimi

Abstract:

Nowadays, induction motors have a significant role in industries. Condition monitoring (CM) of this equipment has gained a remarkable importance during recent years due to huge production losses, substantial imposed costs and increases in vulnerability, risk, and uncertainty levels. Motor current signature analysis (MCSA) is one of the most important techniques in CM. This method can be used for rotor broken bars detection. Signal processing methods such as Fast Fourier transformation (FFT), Wavelet transformation and Empirical Mode Decomposition (EMD) are used for analyzing MCSA output data. In this study, these signal processing methods are used for broken bar problem detection of Mobarakeh steel company induction motors. Based on wavelet transformation method, an index for fault detection, CF, is introduced which is the variation of maximum to the mean of wavelet transformation coefficients. We find that, in the broken bar condition, the amount of CF factor is greater than the healthy condition. Based on EMD method, the energy of intrinsic mode functions (IMF) is calculated and finds that when motor bars become broken the energy of IMFs increases.

Keywords: broken bar, condition monitoring, diagnostics, empirical mode decomposition, fourier transform, wavelet transform

Procedia PDF Downloads 150

Authors: Ayad Dalloo, Sulaf Dalloo

Abstract:

Electrocardiogram (ECG) recording is prone to complications, on analysis by physicians, due to noise and artifacts, thus creating ambiguity leading to possible error of diagnosis. Such drawbacks may be overcome with the advent of high resolution Methods, such as Discrete Wavelet Analysis and Digital Signal Processing (DSP) techniques. This ECG signal analysis is implemented in three stages: ECG preprocessing, features extraction and classification with the aim of realizing high resolution ECG diagnosis and improved detection of abnormal conditions in the heart. The preprocessing stage involves removing spurious artifacts (noise), due to such factors as muscle contraction, motion, respiration, etc. ECG features are extracted by applying DSP and suggested sloping method techniques. These measured features represent peak amplitude values and intervals of P, Q, R, S, R’, and T waves on ECG, and other features such as ST elevation, QRS width, heart rate, electrical axis, QR and QT intervals. The classification is preformed using these extracted features and the criteria for cardiovascular diseases. The ECG diagnostic system is successfully applied to 12-lead ECG recordings for 12 cases. The system is provided with information to enable it diagnoses 15 different diseases. Physician’s and computer’s diagnoses are compared with 90% agreement, with respect to physician diagnosis, and the time taken for diagnosis is 2 seconds. All of these operations are programmed in Matlab environment.

Keywords: ECG diagnostic system, QRS detection, ECG baseline removal, cardiovascular diseases

Procedia PDF Downloads 297

Authors: Amanpreet Kaur

Abstract:

Wavelet transform (WT) is a powerful statistical tool used in applied mathematics for signal and image processing. The different mother, wavelet basis function, has been compared to select the optimal wavelet function that represents the electromyogram signal characteristics of upper limb amputees. Four different EMG electrode has placed on different location of shoulder muscles. Twenty one wavelet functions from different wavelet families were investigated. These functions included Daubechies (db1-db10), Symlets (sym1-sym5), Coiflets (coif1-coif5) and Discrete Meyer. Using mean square error value, the significance of the mother wavelet functions has been determined for teres, pectorals, and infraspinatus around shoulder muscles. The results show that the best mother wavelet is the db3 from the Daubechies family for efficient classification of the signal.

Keywords: Daubechies, upper limb amputation, shoulder muscles, Symlets, Coiflets

Procedia PDF Downloads 235

Authors: Sergei Aleinik, Yuri Matveev

Abstract:

In this paper a novel method for the detection of clipping in speech signals is described. It is shown that the new method has better performance than known clipping detection methods, is easy to implement, and is robust to changes in signal amplitude, size of data, etc. Statistical simulation results are presented.

Keywords: clipping, clipped signal, speech signal processing, digital signal processing

Procedia PDF Downloads 393

Authors: Kübra Taşkıran, Bahattin Türetken

Abstract:

In this paper, a microstrip array antenna with circular polarization at 2.4 GHz frequency has been designed using the in order to provide image and telemetric data transmission in Unmanned Aerial Vehicle and Armed Unmanned Aerial Vehicle Systems. In addition to the antenna design, the power divider design was made and the antennas were fed in phase. As a result of the analysis, it was observed that the antenna operates at a frequency of 2.4016 GHz with 12.2 dBi directing gain. In addition, this designed array antenna was transformed into a form compatible with the rocket surface used in A-UAV Systems, and analyzes were made. As a result of these analyzes, it has been observed that the antenna operates on the surface of the missile at a frequency of 2.372 GHz with a directivity gain of 10.2 dBi.

Keywords: cicrostrip array antenna, circular polarization, 2.4 GHz, image and telemetric data, transmission, surface compatible, UAV and armed UAV

Procedia PDF Downloads 104

Authors: Andre Peres Ramos, Franklin Cesar Flores

Abstract:

Colorization is the process of add colors to a monochromatic image or video. Usually, the process involves to segment the image in regions of interest and then apply colors to each one, for videos, this process is repeated for each frame, which makes it a tedious and time-consuming job. We propose a new assisted method for video colorization; the user only has to colorize one frame, and then the colors are propagated to following frames. The user can intervene at any time to correct eventual errors in color assignment. The method consists of to extract intensity and texture descriptors from the frames and then perform a feature matching to determine the best color for each segment. To reduce computation time and give a better spatial coherence we narrow the area of search and give weights for each feature to emphasize texture descriptors. To give a more natural result, we use an optimization algorithm to make the color propagation. Experimental results in several image sequences, compared to others existing methods, demonstrates that the proposed method perform a better colorization with less time and user interference.

Keywords: colorization, feature matching, texture descriptors, video segmentation

Procedia PDF Downloads 162

Authors: Jianlun Zhang, Christine Lim

Abstract:

Local food is one of the most attractive elements to tourists. The role of local cuisine in destination branding is very important because it is the distinctive identity that helps tourists remember the destination. The objectives of this study are: (1) Test the direct relation between the cognitive image of destination food and tourists’ intention to eat local food. (2) Examine the mediating effect of tourists’ desire to try destination food on the relationship between the cognitive image of local food and tourists’ intention to eat destination food. (3) Study the moderating effect of tourists’ perceived difficulties in finding local food on the relationship between tourists’ desire to try destination food and tourists’ intention to eat local food. To achieve the goals of this study, Macanese cuisine is selected as the destination food. Macau is located in Southeastern China and is a former colonial city of Portugal. The taste and texture of Macanese cuisine are unique because it is a fusion of cuisine from many countries and regions of mainland China. As people travel to seek authentically exotic experience, it is important to investigate if the food image of Macau leaves a good impression on tourists and motivate them to try local cuisine. A total of 449 Chinese tourists were involved in this study. To analyze the data collected, partial least square-structural equation modelling (PLS-SEM) technique is employed. Results suggest that the cognitive image of Macanese cuisine has a direct effect on tourists’ intention to eat Macanese cuisine. Tourists’ desire to try Macanese cuisine mediates the cognitive image-intention relationship. Tourists’ perceived difficulty of finding Macanese cuisine moderates the desire-intention relationship. The lower tourists’ perceived difficulty in finding Macanese cuisine is, the stronger the desire-intention relationship it will be. There are several practical implications of this study. First, the government tourism website can develop an authentic storyline about the evolvement of local cuisine, which provides an opportunity for tourists to taste the history of the destination and create a novel experience for them. Second, the government should consider the development of food events, restaurants, and hawker businesses. Third, to lower tourists’ perceived difficulty in finding local cuisine, there should be locations of restaurants and hawker stalls with clear instructions for finding them on the websites of the government tourism office, popular tourism sites, and public transportation stations in the destination. Fourth, in the post-COVID-19 era, travel risk will be a major concern for tourists. Therefore, when promoting local food, the government tourism website should post images that show food safety and hygiene.

Keywords: cognitive image of destination food, desire to try destination food, intention to eat food in the destination, perceived difficulties of finding local cuisine, PLS-SEM

Procedia PDF Downloads 189

Authors: Ali Hamza

Abstract:

Accurate segmentation of breast ultrasound images is of paramount importance in enhancing the diagnostic capabilities of breast cancer detection. This study presents an approach utilizing the U-Net architecture for segmenting breast ultrasound images aimed at improving the accuracy and reliability of mass identification within the breast tissue. The proposed method encompasses a multi-stage process. Initially, preprocessing techniques are employed to refine image quality and diminish noise interference. Subsequently, the U-Net architecture, a deep learning convolutional neural network (CNN), is employed for pixel-wise segmentation of regions of interest corresponding to potential breast masses. The U-Net's distinctive architecture, characterized by a contracting and expansive pathway, enables accurate boundary delineation and detailed feature extraction. To evaluate the effectiveness of the proposed approach, an extensive dataset of breast ultrasound images is employed, encompassing diverse cases. Quantitative performance metrics such as the Dice coefficient, Jaccard index, sensitivity, specificity, and Hausdorff distance are employed to comprehensively assess the segmentation accuracy. Comparative analyses against traditional segmentation methods showcase the superiority of the U-Net architecture in capturing intricate details and accurately segmenting breast masses. The outcomes of this study emphasize the potential of the U-Net-based segmentation approach in bolstering breast ultrasound image analysis. The method's ability to reliably pinpoint mass boundaries holds promise for aiding radiologists in precise diagnosis and treatment planning. However, further validation and integration within clinical workflows are necessary to ascertain their practical clinical utility and facilitate seamless adoption by healthcare professionals. In conclusion, leveraging the U-Net architecture for breast ultrasound image segmentation showcases a robust framework that can significantly enhance diagnostic accuracy and advance the field of breast cancer detection. This approach represents a pivotal step towards empowering medical professionals with a more potent tool for early and accurate breast cancer diagnosis.

Keywords: mage segmentation, U-Net, deep learning, breast cancer detection, diagnostic accuracy, mass identification, convolutional neural network

Procedia PDF Downloads 84

Authors: Anuruddha Jagoda, Samiddhi Samarakoon, Anil Jasinghe

Abstract:

In an emergency department ‘where every second count for patient’s management’ timely availability of X- rays play a vital role in early diagnosis and management of patients. Trauma care centers rely heavily on timely radiologic imaging for patient care and radiology plays a crucial role in the emergency department (ED) operations. A research study was carried out to assess timeliness of availability of X-rays and total turnaround time at the Accident Service of National Hospital of Sri Lanka which is the premier trauma center in the country. Digital Radiology system was implemented as an intervention to improve the timeliness of availability of X-rays. Post-implementation assessment was carried out to assess the effectiveness of the intervention. Reduction in all three aspects of waiting times namely waiting for initial examination by doctors, waiting until X –ray is performed and waiting for image availability was observed after implementation of the intervention. However, the most significant improvement was seen in waiting time for image availability and reduction in time for image availability had indirect impact on reducing waiting time for initial examination by doctors and waiting until X –ray is performed. The most significant reduction in time for image availability was observed when performing 4-5 X rays with DR system. The least improvement in timeliness was seen in patients who are categorized as critical.

Keywords: emergency department, digital radilogy, timeliness, trauma care

Procedia PDF Downloads 265

Authors: Abrahão S. Fontes, Carlos A. V. Cardoso, Levi P. B. Oliveira

Abstract:

The induction motors are used worldwide in various industries. Several maintenance techniques are applied to increase the operating time and the lifespan of these motors. Among these, the predictive maintenance techniques such as Motor Current Signature Analysis (MCSA), Motor Square Current Signature Analysis (MSCSA), Park's Vector Approach (PVA) and Park's Vector Square Modulus (PVSM) are used to detect and diagnose faults in electric motors, characterized by patterns in the stator current frequency spectrum. In this article, these techniques are applied and compared on a real motor, which has the fault of eccentricity in the air-gap. It was used as a theoretical model of an electric induction motor without fault in order to assist comparison between the stator current frequency spectrum patterns with and without faults. Metrics were purposed and applied to evaluate the sensitivity of each technique fault detection. The results presented here show that the above techniques are suitable for the fault of eccentricity in the air gap, whose comparison between these showed the suitability of each one.

Keywords: eccentricity in the air-gap, fault diagnosis, induction motors, predictive maintenance

Procedia PDF Downloads 350

Authors: Saifullah Karimullah

Abstract:

Additive manufacturing techniques are becoming more common with the latest technological advancements. It is composed to bring a revolution in the way products are designed, planned, manufactured, and distributed to end users. Fused deposition modeling (FDM) based 3D printing is one of those promising aspects that have revolutionized the prototyping processes. The purpose of this design and study project is to design a customized laboratory-scale FDM-based 3D printer from locally available sources. The primary goal is to design and fabricate the FDM-based 3D printer. After the fabrication, a tensile test specimen would be designed in Solid Works or [Creo computer-aided design (CAD)] software. A .stl file is generated of the tensile test specimen through slicing software and the G-codes are inserted via a computer for the test specimen to be printed. Different parameters were under studies like printing speed, layer thickness and infill density of the printed object. Some parameters were kept constant such as temperature, extrusion rate, raster orientation etc. Different tensile test specimens were printed for a different sets of parameters of the FDM-based 3d printer. The tensile test specimen were subjected to tensile tests using a universal testing machine (UTM). Design Expert software has been used for analyses, So Different results were obtained from the different tensile test specimens. The best, average and worst specimen were also observed under a compound microscope to investigate the layer bonding in between.

Keywords: additive manufacturing techniques, 3D printing, CAD software, UTM machine

Procedia PDF Downloads 103

Authors: Belgherbi Aicha, Bessaid Abdelhafid

Abstract:

In the recent years a great deal of research work has been devoted to the development of semi-automatic and automatic techniques for the analysis of abdominal CT images. The first and fundamental step in all these studies is the semi-automatic liver and spleen segmentation that is still an open problem. In this paper, a semi-automatic liver and spleen segmentation method by the mathematical morphology based on watershed algorithm has been proposed. Our algorithm is currency in two parts. In the first, we seek to determine the region of interest by applying the morphological to extract the liver and spleen. The second step consists to improve the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce the over-segmentation problem by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. The aim of this work is to develop a method for semi-automatic segmentation liver and spleen based on watershed algorithm, improve the accuracy and the robustness of the liver and spleen segmentation and evaluate a new semi-automatic approach with the manual for liver segmentation. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work. The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts. Liver segmentation has achieved the sensitivity and specificity; sens Liver=96% and specif Liver=99% respectively. Spleen segmentation achieves similar, promising results sens Spleen=95% and specif Spleen=99%.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

Procedia PDF Downloads 325

Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

Abstract:

Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: artificial neural network, data mining, electroencephalogram, epilepsy, feature extraction, seizure detection, signal processing

Procedia PDF Downloads 188