Search results for: image schema
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2859

Search results for: image schema

2139 Understanding the Nature of Conflicts in Africa: Analytical and Theoretical Explanations

Authors: Kingfahd Adewale Adedapo, Adekunle Ajisebiyawo

Abstract:

The focus of this paper is to explore the different theoretical perspectives that underline academic attempts at understanding and explaining the nature of conflicts in Africa. The African environment is riddled with the past history of conflicts among groups either for an economic outlet or imperial space, and most often, such past negative interactions have made it difficult even now for some of these groups to live harmoniously together within the present state system and to trust each other. The paper observed that no one theory or explanatory schema could offer a holistic explanation of conflict in Africa. At best, each of the possible theories can only offer a partial explanation of the causes and nature of conflict in a particular African society or state. This paper, therefore, attempted to synthesize the many sources of theories of conflicts and provided the intellectual background from which these different theories emanated. Therefore, if this paper has done anything at all, it is to offer the basis for assessing different theoretical strands aimed at offering cogent and reliable explanations for most of the conflicts in Africa and especially in the West African sub-region.

Keywords: conflict, functionalism, humanitarianism, structuralism, theory

Procedia PDF Downloads 105
2138 On the Implementation of The Pulse Coupled Neural Network (PCNN) in the Vision of Cognitive Systems

Authors: Hala Zaghloul, Taymoor Nazmy

Abstract:

One of the great challenges of the 21st century is to build a robot that can perceive and act within its environment and communicate with people, while also exhibiting the cognitive capabilities that lead to performance like that of people. The Pulse Coupled Neural Network, PCNN, is a relative new ANN model that derived from a neural mammal model with a great potential in the area of image processing as well as target recognition, feature extraction, speech recognition, combinatorial optimization, compressed encoding. PCNN has unique feature among other types of neural network, which make it a candid to be an important approach for perceiving in cognitive systems. This work show and emphasis on the potentials of PCNN to perform different tasks related to image processing. The main drawback or the obstacle that prevent the direct implementation of such technique, is the need to find away to control the PCNN parameters toward perform a specific task. This paper will evaluate the performance of PCNN standard model for processing images with different properties, and select the important parameters that give a significant result, also, the approaches towards find a way for the adaptation of the PCNN parameters to perform a specific task.

Keywords: cognitive system, image processing, segmentation, PCNN kernels

Procedia PDF Downloads 280
2137 Correlation Mapping for Measuring Platelet Adhesion

Authors: Eunseop Yeom

Abstract:

Platelets can be activated by the surrounding blood flows where a blood vessel is narrowed as a result of atherosclerosis. Numerous studies have been conducted to identify the relation between platelets activation and thrombus formation. To measure platelet adhesion, this study proposes an image analysis technique. Blood samples are delivered in the microfluidic channel, and then platelets are activated by a stenotic micro-channel with 90% severity. By applying proposed correlation mapping, which visualizes decorrelation of the streaming blood flow, the area of adhered platelets (APlatelet) was estimated without labeling platelets. In order to evaluate the performance of correlation mapping on the detection of platelet adhesion, the effect of tile size was investigated by calculating 2D correlation coefficients with binary images obtained by manual labeling and the correlation mapping method with different sizes of the square tile ranging from 3 to 50 pixels. The maximum 2D correlation coefficient is observed with the optimum tile size of 5×5 pixels. As the area of the platelet adhesion increases, the platelets plug the channel and there is only a small amount of blood flows. This image analysis could provide new insights for better understanding of the interactions between platelet aggregation and blood flows in various physiological conditions.

Keywords: platelet activation, correlation coefficient, image analysis, shear rate

Procedia PDF Downloads 335
2136 An Experimental Study of Bolt Inclination in a Composite Single Bolted Joint

Authors: Youcef Faci, Djillali Allou, Ahmed Mebtouche, Badredine Maalem

Abstract:

The inclination of the bolt in a fastened joint of composite material during a tensile test can be influenced by several parameters, including material properties, bolt diameter and length, the type of composite material being used, the size and dimensions of the bolt, bolt preload, surface preparation, the design and configuration of the joint, and finally testing conditions. These parameters should be carefully considered and controlled to ensure accurate and reliable results during tensile testing of composite materials with fastened joints. Our work focuses on the effect of the stacking sequence and the geometry of specimens. An experimental test is carried out to obtain the inclination of a bolt during a tensile test of a composite material using acoustic emission and digital image correlation. Several types of damage were obtained during load. Digital image correlation techniques permit to obtain the inclination of bolt angle value during tensile test. We concluded that the inclination of the bolt during a tensile test of a composite material can be related to the damage that occurs in the material. It can cause stress concentrations and localized deformation in the material, leading to damage such as delamination, fiber breakage, matrix cracking, and other forms of failure.

Keywords: damage, digital image correlation, bolt inclination angle, joint

Procedia PDF Downloads 68
2135 Iris Recognition Based on the Low Order Norms of Gradient Components

Authors: Iman A. Saad, Loay E. George

Abstract:

Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.

Keywords: iris recognition, contrast stretching, gradient features, texture features, Euclidean metric

Procedia PDF Downloads 335
2134 Geographical Data Visualization Using Video Games Technologies

Authors: Nizar Karim Uribe-Orihuela, Fernando Brambila-Paz, Ivette Caldelas, Rodrigo Montufar-Chaveznava

Abstract:

In this paper, we present the advances corresponding to the implementation of a strategy to visualize geographical data using a Software Development Kit (SDK) for video games. We use multispectral images from Landsat 7 platform and Laser Imaging Detection and Ranging (LIDAR) data from The National Institute of Geography and Statistics of Mexican (INEGI). We select a place of interest to visualize from Landsat platform and make some processing to the image (rotations, atmospheric correction and enhancement). The resulting image will be our gray scale color-map to fusion with the LIDAR data, which was selected using the same coordinates than in Landsat. The LIDAR data is translated to 8-bit raw data. Both images are fused in a software developed using Unity (an SDK employed for video games). The resulting image is then displayed and can be explored moving around. The idea is the software could be used for students of geology and geophysics at the Engineering School of the National University of Mexico. They will download the software and images corresponding to a geological place of interest to a smartphone and could virtually visit and explore the site with a virtual reality visor such as Google cardboard.

Keywords: virtual reality, interactive technologies, geographical data visualization, video games technologies, educational material

Procedia PDF Downloads 246
2133 Performance Analysis of Search Medical Imaging Service on Cloud Storage Using Decision Trees

Authors: González A. Julio, Ramírez L. Leonardo, Puerta A. Gabriel

Abstract:

Telemedicine services use a large amount of data, most of which are diagnostic images in Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7) formats. Metadata is generated from each related image to support their identification. This study presents the use of decision trees for the optimization of information search processes for diagnostic images, hosted on the cloud server. To analyze the performance in the server, the following quality of service (QoS) metrics are evaluated: delay, bandwidth, jitter, latency and throughput in five test scenarios for a total of 26 experiments during the loading and downloading of DICOM images, hosted by the telemedicine group server of the Universidad Militar Nueva Granada, Bogotá, Colombia. By applying decision trees as a data mining technique and comparing it with the sequential search, it was possible to evaluate the search times of diagnostic images in the server. The results show that by using the metadata in decision trees, the search times are substantially improved, the computational resources are optimized and the request management of the telemedicine image service is improved. Based on the experiments carried out, search efficiency increased by 45% in relation to the sequential search, given that, when downloading a diagnostic image, false positives are avoided in management and acquisition processes of said information. It is concluded that, for the diagnostic images services in telemedicine, the technique of decision trees guarantees the accessibility and robustness in the acquisition and manipulation of medical images, in improvement of the diagnoses and medical procedures in patients.

Keywords: cloud storage, decision trees, diagnostic image, search, telemedicine

Procedia PDF Downloads 204
2132 The Origins of Representations: Cognitive and Brain Development

Authors: Athanasios Raftopoulos

Abstract:

In this paper, an attempt is made to explain the evolution or development of human’s representational arsenal from its humble beginnings to its modern abstract symbols. Representations are physical entities that represent something else. To represent a thing (in a general sense of “thing”) means to use in the mind or in an external medium a sign that stands for it. The sign can be used as a proxy of the represented thing when the thing is absent. Representations come in many varieties, from signs that perceptually resemble their representative to abstract symbols that are related to their representata through conventions. Relying the distinction among indices, icons, and symbols, it is explained how symbolic representations gradually emerged from indices and icons. To understand the development or evolution of our representational arsenal, the development of the cognitive capacities that enabled the gradual emergence of representations of increasing complexity and expressive capability should be examined. The examination of these factors should rely on a careful assessment of the available empirical neuroscientific and paleo-anthropological evidence. These pieces of evidence should be synthesized to produce arguments whose conclusions provide clues concerning the developmental process of our representational capabilities. The analysis of the empirical findings in this paper shows that Homo Erectus was able to use both icons and symbols. Icons were used as external representations, while symbols were used in language. The first step in the emergence of representations is that a sensory-motor purely causal schema involved in indices is decoupled from its normal causal sensory-motor functions and serves as a representation of the object that initially called it into play. Sensory-motor schemes are tied to specific contexts of the organism-environment interactions and are activated only within these contexts. For a representation of an object to be possible, this scheme must be de-contextualized so that the same object can be represented in different contexts; a decoupled schema loses its direct ties to reality and becomes mental content. The analysis suggests that symbols emerged due to selection pressures of the social environment. The need to establish and maintain social relationships in ever-enlarging groups that would benefit the group was a sufficient environmental pressure to lead to the appearance of the symbolic capacity. Symbols could serve this need because they can express abstract relationships, such as marriage or monogamy. Icons, by being firmly attached to what can be observed, could not go beyond surface properties to express abstract relations. The cognitive capacities that are required for having iconic and then symbolic representations were present in Homo Erectus, which had a language that started without syntactic rules but was structured so as to mirror the structure of the world. This language became increasingly complex, and grammatical rules started to appear to allow for the construction of more complex expressions required to keep up with the increasing complexity of social niches. This created evolutionary pressures that eventually led to increasing cranial size and restructuring of the brain that allowed more complex representational systems to emerge.

Keywords: mental representations, iconic representations, symbols, human evolution

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2131 A Distinct Method Based on Mamba-Unet for Brain Tumor Image Segmentation

Authors: Djallel Bouamama, Yasser R. Haddadi

Abstract:

Accurate brain tumor segmentation is crucial for diagnosis and treatment planning, yet it remains a challenging task due to the variability in tumor shapes and intensities. This paper introduces a distinct approach to brain tumor image segmentation by leveraging an advanced architecture known as Mamba-Unet. Building on the well-established U-Net framework, Mamba-Unet incorporates distinct design enhancements to improve segmentation performance. Our proposed method integrates a multi-scale attention mechanism and a hybrid loss function to effectively capture fine-grained details and contextual information in brain MRI scans. We demonstrate that Mamba-Unet significantly enhances segmentation accuracy compared to conventional U-Net models by utilizing a comprehensive dataset of annotated brain MRI scans. Quantitative evaluations reveal that Mamba-Unet surpasses traditional U-Net architectures and other contemporary segmentation models regarding Dice coefficient, sensitivity, and specificity. The improvements are attributed to the method's ability to manage class imbalance better and resolve complex tumor boundaries. This work advances the state-of-the-art in brain tumor segmentation and holds promise for improving clinical workflows and patient outcomes through more precise and reliable tumor detection.

Keywords: brain tumor classification, image segmentation, CNN, U-NET

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2130 Random Subspace Neural Classifier for Meteor Recognition in the Night Sky

Authors: Carlos Vera, Tetyana Baydyk, Ernst Kussul, Graciela Velasco, Miguel Aparicio

Abstract:

This article describes the Random Subspace Neural Classifier (RSC) for the recognition of meteors in the night sky. We used images of meteors entering the atmosphere at night between 8:00 p.m.-5: 00 a.m. The objective of this project is to classify meteor and star images (with stars as the image background). The monitoring of the sky and the classification of meteors are made for future applications by scientists. The image database was collected from different websites. We worked with RGB-type images with dimensions of 220x220 pixels stored in the BitMap Protocol (BMP) format. Subsequent window scanning and processing were carried out for each image. The scan window where the characteristics were extracted had the size of 20x20 pixels with a scanning step size of 10 pixels. Brightness, contrast and contour orientation histograms were used as inputs for the RSC. The RSC worked with two classes and classified into: 1) with meteors and 2) without meteors. Different tests were carried out by varying the number of training cycles and the number of images for training and recognition. The percentage error for the neural classifier was calculated. The results show a good RSC classifier response with 89% correct recognition. The results of these experiments are presented and discussed.

Keywords: contour orientation histogram, meteors, night sky, RSC neural classifier, stars

Procedia PDF Downloads 139
2129 Towards Long-Range Pixels Connection for Context-Aware Semantic Segmentation

Authors: Muhammad Zubair Khan, Yugyung Lee

Abstract:

Deep learning has recently achieved enormous response in semantic image segmentation. The previously developed U-Net inspired architectures operate with continuous stride and pooling operations, leading to spatial data loss. Also, the methods lack establishing long-term pixels connection to preserve context knowledge and reduce spatial loss in prediction. This article developed encoder-decoder architecture with bi-directional LSTM embedded in long skip-connections and densely connected convolution blocks. The network non-linearly combines the feature maps across encoder-decoder paths for finding dependency and correlation between image pixels. Additionally, the densely connected convolutional blocks are kept in the final encoding layer to reuse features and prevent redundant data sharing. The method applied batch-normalization for reducing internal covariate shift in data distributions. The empirical evidence shows a promising response to our method compared with other semantic segmentation techniques.

Keywords: deep learning, semantic segmentation, image analysis, pixels connection, convolution neural network

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2128 Effect of Migrant Influx toward Betterment of Aging and Low Fertility Rate: Statistical Analyses in Japan

Authors: Sari K. Ishii

Abstract:

This study considers a wider viewpoint to connect migration studies with questions about financial capitalism, which seeks cheap, disposable labour transnationally. This study offers insight into whether the current state of immigration acceptance contributes to stabilizing the aging society of the nation in the long term or merely fulfills the ephemeral requirements of industries. The analyses in this study focused on three aspects. First, it examined how many migrants in Japan joined the labour market. Second, it analyzed the number of migrants that are aging. Third, it determined the number of dependent migrants accepted through labour migrants. The study findings raise further questions for future empirical studies to verify the schema of financial capitalism through the lens of migration. The scheme of seeking cheap, disposable labour transnationally may result in the descendants of both locals and mobilized labour becoming more unstable than the prior generations.

Keywords: migration, aging society, low fertility rate, Japan

Procedia PDF Downloads 42
2127 Automatic Segmentation of Lung Pleura Based On Curvature Analysis

Authors: Sasidhar B., Bhaskar Rao N., Ramesh Babu D. R., Ravi Shankar M.

Abstract:

Segmentation of lung pleura is a preprocessing step in Computer-Aided Diagnosis (CAD) which helps in reducing false positives in detection of lung cancer. The existing methods fail in extraction of lung regions with the nodules at the pleura of the lungs. In this paper, a new method is proposed which segments lung regions with nodules at the pleura of the lungs based on curvature analysis and morphological operators. The proposed algorithm is tested on 06 patient’s dataset which consists of 60 images of Lung Image Database Consortium (LIDC) and the results are found to be satisfactory with 98.3% average overlap measure (AΩ).

Keywords: curvature analysis, image segmentation, morphological operators, thresholding

Procedia PDF Downloads 596
2126 Pushover Experiment of Traditional Dieh-Dou Timber Frame

Authors: Ren Zuo Wang

Abstract:

In this paper, in order to investigate the joint behaviors of the Dieh-Dou structure. A pushover experiment of Dieh-Dou Jia-Dong is implemented. NDI, LVDT and image measurement system are used to measure displacements of joints and deformations of Dieh-Dou Jia-Dong. In addition, joint rotation-moment relationships of column restoring force, purlin-supporting, Dou-Shu, Dou-Gong brackets, primary beam-Gua Tong, secondary beam-Gua Tong, Tertiary beam are builied. From Jia-Dong experiments, formulations of joint rotation are proposed.

Keywords: pushover experiment, Dieh-Dou timber frame, image measurement system, joint rotation-moment relationships

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2125 Comparing Image Processing and AI Techniques for Disease Detection in Plants

Authors: Luiz Daniel Garay Trindade, Antonio De Freitas Valle Neto, Fabio Paulo Basso, Elder De Macedo Rodrigues, Maicon Bernardino, Daniel Welfer, Daniel Muller

Abstract:

Agriculture plays an important role in society since it is one of the main sources of food in the world. To help the production and yield of crops, precision agriculture makes use of technologies aiming at improving productivity and quality of agricultural commodities. One of the problems hampering quality of agricultural production is the disease affecting crops. Failure in detecting diseases in a short period of time can result in small or big damages to production, causing financial losses to farmers. In order to provide a map of the contributions destined to the early detection of plant diseases and a comparison of the accuracy of the selected studies, a systematic literature review of the literature was performed, showing techniques for digital image processing and neural networks. We found 35 interesting tool support alternatives to detect disease in 19 plants. Our comparison of these studies resulted in an overall average accuracy of 87.45%, with two studies very closer to obtain 100%.

Keywords: pattern recognition, image processing, deep learning, precision agriculture, smart farming, agricultural automation

Procedia PDF Downloads 379
2124 Offline Signature Verification in Punjabi Based On SURF Features and Critical Point Matching Using HMM

Authors: Rajpal Kaur, Pooja Choudhary

Abstract:

Biometrics, which refers to identifying an individual based on his or her physiological or behavioral characteristics, has the capabilities to the reliably distinguish between an authorized person and an imposter. The Signature recognition systems can categorized as offline (static) and online (dynamic). This paper presents Surf Feature based recognition of offline signatures system that is trained with low-resolution scanned signature images. The signature of a person is an important biometric attribute of a human being which can be used to authenticate human identity. However the signatures of human can be handled as an image and recognized using computer vision and HMM techniques. With modern computers, there is need to develop fast algorithms for signature recognition. There are multiple techniques are defined to signature recognition with a lot of scope of research. In this paper, (static signature) off-line signature recognition & verification using surf feature with HMM is proposed, where the signature is captured and presented to the user in an image format. Signatures are verified depended on parameters extracted from the signature using various image processing techniques. The Off-line Signature Verification and Recognition is implemented using Mat lab platform. This work has been analyzed or tested and found suitable for its purpose or result. The proposed method performs better than the other recently proposed methods.

Keywords: offline signature verification, offline signature recognition, signatures, SURF features, HMM

Procedia PDF Downloads 384
2123 Biimodal Biometrics System Using Fusion of Iris and Fingerprint

Authors: Attallah Bilal, Hendel Fatiha

Abstract:

This paper proposes the bimodal biometrics system for identity verification iris and fingerprint, at matching score level architecture using weighted sum of score technique. The features are extracted from the pre processed images of iris and fingerprint. These features of a query image are compared with those of a database image to obtain matching scores. The individual scores generated after matching are passed to the fusion module. This module consists of three major steps i.e., normalization, generation of similarity score and fusion of weighted scores. The final score is then used to declare the person as genuine or an impostor. The system is tested on CASIA database and gives an overall accuracy of 91.04% with FAR of 2.58% and FRR of 8.34%.

Keywords: iris, fingerprint, sum rule, fusion

Procedia PDF Downloads 368
2122 A Comparative Study of Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV) for Airflow Measurement

Authors: Sijie Fu, Pascal-Henry Biwolé, Christian Mathis

Abstract:

Among modern airflow measurement methods, Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV), as visualized and non-instructive measurement techniques, are playing more important role. This paper conducts a comparative experimental study for airflow measurement employing both techniques with the same condition. Velocity vector fields, velocity contour fields, voticity profiles and turbulence profiles are selected as the comparison indexes. The results show that the performance of both PIV and PTV techniques for airflow measurement is satisfied, but some differences between the both techniques are existed, it suggests that selecting the measurement technique should be based on a comprehensive consideration.

Keywords: airflow measurement, comparison, PIV, PTV

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2121 Security Analysis and Implementation of Achterbahn-128 for Images Encryption

Authors: Aissa Belmeguenai, Oulaya Berrak, Khaled Mansouri

Abstract:

In this work, efficiency implementation and security evaluation of the keystream generator of Achterbahn-128 for images encryption and decryption was introduced. The implementation for this simulated project is written with MATLAB.7.5. First of all, two different original images are used to validate the proposed design. The developed program is used to transform the original images data into digital image file. Finally, the proposed program is implemented to encrypt and decrypt images data. Several tests are done to prove the design performance, including visual tests and security evaluation.

Keywords: Achterbahn-128, keystream generator, stream cipher, image encryption, security analysis

Procedia PDF Downloads 315
2120 Using Satellite Images Datasets for Road Intersection Detection in Route Planning

Authors: Fatma El-Zahraa El-Taher, Ayman Taha, Jane Courtney, Susan Mckeever

Abstract:

Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions, is critical to decisions such as crossing roads or selecting the safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer the state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset is examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of the detection of intersections in satellite images is evaluated.

Keywords: satellite images, remote sensing images, data acquisition, autonomous vehicles

Procedia PDF Downloads 144
2119 Using Set Up Candid Clips as Viral Marketing via New Media

Authors: P. Suparada, D. Eakapotch

Abstract:

This research’s objectives were to analyze the using of new media in the form of set up candid clip that affects the product and presenter, to study the effectiveness of using new media in the form of set up candid clip in order to increase the circulation and audience satisfaction and to use the earned information and knowledge to develop the communication for publicizing and advertising via new media. This research is qualitative research based on questionnaire from 50 random sampling representative samples and in-depth interview from experts in publicizing and advertising fields. The findings indicated the positive and negative effects to the brands’ image and presenters’ image of product named “Scotch 100” and “Snickers” that used set up candid clips via new media for publicizing and advertising in Thailand. It will be useful for fields of publicizing and advertising in the new media forms.

Keywords: candid clip, effect, new media, social network

Procedia PDF Downloads 223
2118 Comparative Analysis of Classical and Parallel Inpainting Algorithms Based on Affine Combinations of Projections on Convex Sets

Authors: Irina Maria Artinescu, Costin Radu Boldea, Eduard-Ionut Matei

Abstract:

The paper is a comparative study of two classical variants of parallel projection methods for solving the convex feasibility problem with their equivalents that involve variable weights in the construction of the solutions. We used a graphical representation of these methods for inpainting a convex area of an image in order to investigate their effectiveness in image reconstruction applications. We also presented a numerical analysis of the convergence of these four algorithms in terms of the average number of steps and execution time in classical CPU and, alternatively, in parallel GPU implementation.

Keywords: convex feasibility problem, convergence analysis, inpainting, parallel projection methods

Procedia PDF Downloads 174
2117 Radar Charts Analysis to Compare the Level of Innovation in Mexico with Most Innovative Countries in Triple Helix Schema Economic and Human Factor Dimension

Authors: M. Peña Aguilar Juan, Valencia Luis, Pastrana Alberto, Nava Estefany, A. Martinez, M. Vivanco, A. Castañeda

Abstract:

This paper seeks to compare the innovation of Mexico from an economic and human perspective, with the seven most innovative countries according to the Global Innovation Index 2013, done by the World Intellectual Property Organization (WIPO). The above analysis suggests nine dimensions: Expenditure on R & D, intellectual property, appropriate environment to conduct business, economic stability, and triple helix for R & D, ICT Infrastructure, education, human resources and quality of life. Each dimension is represented by an indicator which is later used to construct a radial graph that compares the innovative capacity of the countries analysed. As a result, it is proposed a new indicator of innovation called The Area of Innovation. Observations are made from the results, and finally as a conclusion, those items or dimensions in which Mexico suffers lag in innovation are identify.

Keywords: dimension, measure, innovation level, economy, radar chart

Procedia PDF Downloads 472
2116 Customer Data Analysis Model Using Business Intelligence Tools in Telecommunication Companies

Authors: Monica Lia

Abstract:

This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.

Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes

Procedia PDF Downloads 430
2115 Anatomical Survey for Text Pattern Detection

Authors: S. Tehsin, S. Kausar

Abstract:

The ultimate aim of machine intelligence is to explore and materialize the human capabilities, one of which is the ability to detect various text objects within one or more images displayed on any canvas including prints, videos or electronic displays. Multimedia data has increased rapidly in past years. Textual information present in multimedia contains important information about the image/video content. However, it needs to technologically testify the commonly used human intelligence of detecting and differentiating the text within an image, for computers. Hence in this paper feature set based on anatomical study of human text detection system is proposed. Subsequent examination bears testimony to the fact that the features extracted proved instrumental to text detection.

Keywords: biologically inspired vision, content based retrieval, document analysis, text extraction

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2114 The Trajectory of the Ball in Football Game

Authors: Mahdi Motahari, Mojtaba Farzaneh, Ebrahim Sepidbar

Abstract:

Tracking of moving and flying targets is one of the most important issues in image processing topic. Estimating of trajectory of desired object in short-term and long-term scale is more important than tracking of moving and flying targets. In this paper, a new way of identifying and estimating of future trajectory of a moving ball in long-term scale is estimated by using synthesis and interaction of image processing algorithms including noise removal and image segmentation, Kalman filter algorithm in order to estimating of trajectory of ball in football game in short-term scale and intelligent adaptive neuro-fuzzy algorithm based on time series of traverse distance. The proposed system attain more than 96% identify accuracy by using aforesaid methods and relaying on aforesaid algorithms and data base video in format of synthesis and interaction. Although the present method has high precision, it is time consuming. By comparing this method with other methods we realize the accuracy and efficiency of that.

Keywords: tracking, signal processing, moving targets and flying, artificial intelligent systems, estimating of trajectory, Kalman filter

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2113 Low Light Image Enhancement with Multi-Stage Interconnected Autoencoders Integration in Pix to Pix GAN

Authors: Muhammad Atif, Cang Yan

Abstract:

The enhancement of low-light images is a significant area of study aimed at enhancing the quality of captured images in challenging lighting environments. Recently, methods based on convolutional neural networks (CNN) have gained prominence as they offer state-of-the-art performance. However, many approaches based on CNN rely on increasing the size and complexity of the neural network. In this study, we propose an alternative method for improving low-light images using an autoencoder-based multiscale knowledge transfer model. Our method leverages the power of three autoencoders, where the encoders of the first two autoencoders are directly connected to the decoder of the third autoencoder. Additionally, the decoder of the first two autoencoders is connected to the encoder of the third autoencoder. This architecture enables effective knowledge transfer, allowing the third autoencoder to learn and benefit from the enhanced knowledge extracted by the first two autoencoders. We further integrate the proposed model into the PIX to PIX GAN framework. By integrating our proposed model as the generator in the GAN framework, we aim to produce enhanced images that not only exhibit improved visual quality but also possess a more authentic and realistic appearance. These experimental results, both qualitative and quantitative, show that our method is better than the state-of-the-art methodologies.

Keywords: low light image enhancement, deep learning, convolutional neural network, image processing

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2112 Quest for Literary Past: A Study of Byatt’s Possession

Authors: Chen Jun

Abstract:

Antonia Susan Byatt’s Possession: A Romance has been misread as a postmodern pastiche novel since its publication because there are epics, epigraphs, lyrics, fairy tales, epistles, and even critical articles swollen in this work. The word ‘pastiche’ suggests messy, disorganized, and chaotic, which buries its artistic excellence while overlooking its subtitle, A Romance. The center of romance is the quest that the hero sets forth to conquer the adversity, hardship, and danger to accomplish a task to prove his identity or social worth. This paper argues that Byatt’s Possession is not a postmodern pastiche novel but rather a postmodern romance in which the characters in the academic world set forth their quest into the Victorian literary past that is nostalgically identified by Byatt as the Golden Age of English literature. In doing so, these five following issues are addressed: first, the origin of the protagonist Roland, and consequently, the nature of his quest; second, the central image of the dragon created by the fictional Victorian poet Henry Ash; third, Melusine as an image of female serpent created by the fictional Victorian poet Christabel LaMotte; fourth, the images of the two ladies; last, the image of water that links the dragon and the serpent. In Possession, the past is reinvented not as an unfortunate fall but as a Golden Age presented in the imaginative academic adventure. The dragon, a stereotypical symbol of evil, becomes the symbol of life in Byatt’s work, which parallels with the image of the mythical phoenix that can resurrect from its own ash. At the same time, the phoenix symbolizes Byatt’s efforts to revive the Victorian poetic art that is supposed to be dead in the post-capitalism society when the novel is the dominating literary genre and poetry becomes the minority. The fictional Victorian poet Ash is in fact Byatt’s own poetic mask through which she breathes life into the lost poetic artistry in the postmodern era.

Keywords: Byatt, possession, postmodern romance, literary past

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2111 The Importance of Upholding Corporate Governance: A Case Study of Government Pension Funds

Authors: Pichamon Chansuchai

Abstract:

This qualitative research paper aimed to study the best practice regulation of the Government Pension Fund of Thailand or GPF to explore the importance of good corporate governance and to identify and compare impacts towards the organizational operation and image before and after adopting the corporate good governance practice. The study employed the six principles of good corporate governance and best practice including accountability, responsibility, equitable treatment, transparency, value creation and ethics. The study pointed out that the GPF was a good example of the organization that regained public trust and receiving a positive image and credibility after implementing corporate good governance in all aspects of its organizational management.

Keywords: corporate governance, government, pension funds, organizational operation

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2110 National Branding through Education: South Korean Image in Romania through the Language Textbooks for Foreigners

Authors: Raluca-Ioana Antonescu

Abstract:

The paper treats about the Korean public diplomacy and national branding strategies, and how the Korean language textbooks were used in order to construct the Korean national image. The field research of the paper stands at the intersection between Linguistics and Political Science, while the problem of the research is the role of language and culture in national branding process. The research goal is to contribute to the literature situated at the intersection between International Relations and Applied Linguistics, while the objective is to conceptualize the idea of national branding by emphasizing a dimension which is not much discussed, and that would be the education as an instrument of the national branding and public diplomacy strategies. In order to examine the importance of language upon the national branding strategies, the paper will answer one main question, How is the Korean language used in the construction of national branding?, and two secondary questions, How are explored in literature the relations between language and national branding construction? and What kind of image of South Korea the language textbooks for foreigners transmit? In order to answer the research questions, the paper starts from one main hypothesis, that the language is an essential component of the culture, which is used in the construction of the national branding influenced by traditional elements (like Confucianism) but also by modern elements (like Western influence), and from two secondary hypothesis, the first one is that in the International Relations literature there are little explored the connections between language and national branding, while the second hypothesis is that the South Korean image is constructed through the promotion of a traditional society, but also a modern one. In terms of methodology, the paper will analyze the textbooks used in Romania at the universities which provide Korean Language classes during the three years program B.A., following the dialogs, the descriptive texts and the additional text about the Korean culture. The analysis will focus on the rank status difference, the individual in relation to the collectivity, the respect for the harmony, and the image of the foreigner. The results of the research show that the South Korean image projected in the textbooks convey the Confucian values and it does not emphasize the changes suffered by the society due to the modernity and globalization. The Westernized aspect of the Korean society is conveyed more in an informative way about the Korean international companies, Korean internal development (like the transport or other services), but it does not show the cultural changed the society underwent. Even if the paper is using the textbooks which are used in Romania as a teaching material, it could be used and applied at least to other European countries, since the textbooks are the ones issued by the South Korean language schools, which other European countries are using also.

Keywords: confucianism, modernism, national branding, public diplomacy, traditionalism

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