Search results for: corporate image
2612 Application of Improved Semantic Communication Technology in Remote Sensing Data Transmission
Authors: Tingwei Shu, Dong Zhou, Chengjun Guo
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Semantic communication is an emerging form of communication that realize intelligent communication by extracting semantic information of data at the source and transmitting it, and recovering the data at the receiving end. It can effectively solve the problem of data transmission under the situation of large data volume, low SNR and restricted bandwidth. With the development of Deep Learning, semantic communication further matures and is gradually applied in the fields of the Internet of Things, Uumanned Air Vehicle cluster communication, remote sensing scenarios, etc. We propose an improved semantic communication system for the situation where the data volume is huge and the spectrum resources are limited during the transmission of remote sensing images. At the transmitting, we need to extract the semantic information of remote sensing images, but there are some problems. The traditional semantic communication system based on Convolutional Neural Network cannot take into account the global semantic information and local semantic information of the image, which results in less-than-ideal image recovery at the receiving end. Therefore, we adopt the improved vision-Transformer-based structure as the semantic encoder instead of the mainstream one using CNN to extract the image semantic features. In this paper, we first perform pre-processing operations on remote sensing images to improve the resolution of the images in order to obtain images with more semantic information. We use wavelet transform to decompose the image into high-frequency and low-frequency components, perform bilinear interpolation on the high-frequency components and bicubic interpolation on the low-frequency components, and finally perform wavelet inverse transform to obtain the preprocessed image. We adopt the improved Vision-Transformer structure as the semantic coder to extract and transmit the semantic information of remote sensing images. The Vision-Transformer structure can better train the huge data volume and extract better image semantic features, and adopt the multi-layer self-attention mechanism to better capture the correlation between semantic features and reduce redundant features. Secondly, to improve the coding efficiency, we reduce the quadratic complexity of the self-attentive mechanism itself to linear so as to improve the image data processing speed of the model. We conducted experimental simulations on the RSOD dataset and compared the designed system with a semantic communication system based on CNN and image coding methods such as BGP and JPEG to verify that the method can effectively alleviate the problem of excessive data volume and improve the performance of image data communication.Keywords: semantic communication, transformer, wavelet transform, data processing
Procedia PDF Downloads 702611 Comparative Analysis of Islamic Bank in Indonesia and Malaysia with Risk Profile, Good Corporate Governance, Earnings, and Capital Method: Performance of Business Function and Social Function Perspective
Authors: Achsania Hendratmi, Nisful Laila, Fatin Fadhilah Hasib, Puji Sucia Sukmaningrum
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This study aims to compare and see the differences between Islamic bank in Indonesia and Islamic bank in Malaysia using RGEC method (Risk Profile, Good Corporate Governance, Earnings, and Capital). This study examines the comparison in business and social performance of eleven Islamic banks in Indonesia and fifteen Islamic banks in Malaysia. This research used quantitative approach and the collections of data was done by collecting all the annual reports of banks that has been created as a sample over the period 2011-2015. The test result of the Independent Samples T-test and Mann-Whitney Test showed there were differences in the business performance of Islamic Bank in Indonesia and Malaysia as seen from the aspect of Risk profile (FDR), GCG, and Earnings (ROA). Also, there were differences of business and social performance as seen from Earnings (ROE), Capital (CAR), and Sharia Conformity Indicator (PSR and ZR) aspects.Keywords: business performance, Islamic banks, RGEC, social performance
Procedia PDF Downloads 2862610 A Novel Probabilistic Spatial Locality of Reference Technique for Automatic Cleansing of Digital Maps
Authors: A. Abdullah, S. Abushalmat, A. Bakshwain, A. Basuhail, A. Aslam
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GIS (Geographic Information System) applications require geo-referenced data, this data could be available as databases or in the form of digital or hard-copy agro-meteorological maps. These parameter maps are color-coded with different regions corresponding to different parameter values, converting these maps into a database is not very difficult. However, text and different planimetric elements overlaid on these maps makes an accurate image to database conversion a challenging problem. The reason being, it is almost impossible to exactly replace what was underneath the text or icons; thus, pointing to the need for inpainting. In this paper, we propose a probabilistic inpainting approach that uses the probability of spatial locality of colors in the map for replacing overlaid elements with underlying color. We tested the limits of our proposed technique using non-textual simulated data and compared text removing results with a popular image editing tool using public domain data with promising results.Keywords: noise, image, GIS, digital map, inpainting
Procedia PDF Downloads 3412609 Noise Removal Techniques in Medical Images
Authors: Amhimmid Mohammed Saffour, Abdelkader Salama
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Filtering is a part of image enhancement techniques, it is used to enhance certain details such as edges in the image that are relevant to the application. Additionally, filtering can even be used to eliminate unwanted components of noise. Medical images typically contain salt and pepper noise and Poisson noise. This noise appears to the presence of minute grey scale variations within the image. In this paper, different filters techniques namely (Median, Wiener, Rank order3, Rank order5, and Average) were applied on CT medical images (Brain and chest). We using all these filters to remove salt and pepper noise from these images. This type of noise consists of random pixels being set to black or white. Peak Signal to Noise Ratio (PSNR), Mean Square Error r(MSE) and Histogram were used to evaluated the quality of filtered images. The results, which we have achieved shows that, these filters, are more useful and they prove to be helpful for general medical practitioners to analyze the symptoms of the patients with no difficulty.Keywords: CT imaging, median filter, adaptive filter and average filter, MATLAB
Procedia PDF Downloads 3072608 Image Reconstruction Method Based on L0 Norm
Authors: Jianhong Xiang, Hao Xiang, Linyu Wang
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Compressed sensing (CS) has a wide range of applications in sparse signal reconstruction. Aiming at the problems of low recovery accuracy and long reconstruction time of existing reconstruction algorithms in medical imaging, this paper proposes a corrected smoothing L0 algorithm based on compressed sensing (CSL0). First, an approximate hyperbolic tangent function (AHTF) that is more similar to the L0 norm is proposed to approximate the L0 norm. Secondly, in view of the "sawtooth phenomenon" in the steepest descent method and the problem of sensitivity to the initial value selection in the modified Newton method, the use of the steepest descent method and the modified Newton method are jointly optimized to improve the reconstruction accuracy. Finally, the CSL0 algorithm is simulated on various images. The results show that the algorithm proposed in this paper improves the reconstruction accuracy of the test image by 0-0. 98dB.Keywords: smoothed L0, compressed sensing, image processing, sparse reconstruction
Procedia PDF Downloads 1102607 A t-SNE and UMAP Based Neural Network Image Classification Algorithm
Authors: Shelby Simpson, William Stanley, Namir Naba, Xiaodi Wang
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Both t-SNE and UMAP are brand new state of art tools to predominantly preserve the local structure that is to group neighboring data points together, which indeed provides a very informative visualization of heterogeneity in our data. In this research, we develop a t-SNE and UMAP base neural network image classification algorithm to embed the original dataset to a corresponding low dimensional dataset as a preprocessing step, then use this embedded database as input to our specially designed neural network classifier for image classification. We use the fashion MNIST data set, which is a labeled data set of images of clothing objects in our experiments. t-SNE and UMAP are used for dimensionality reduction of the data set and thus produce low dimensional embeddings. Furthermore, we use the embeddings from t-SNE and UMAP to feed into two neural networks. The accuracy of the models from the two neural networks is then compared to a dense neural network that does not use embedding as an input to show which model can classify the images of clothing objects more accurately.Keywords: t-SNE, UMAP, fashion MNIST, neural networks
Procedia PDF Downloads 1892606 A Neural Network Classifier for Estimation of the Degree of Infestation by Late Blight on Tomato Leaves
Authors: Gizelle K. Vianna, Gabriel V. Cunha, Gustavo S. Oliveira
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Foliage diseases in plants can cause a reduction in both quality and quantity of agricultural production. Intelligent detection of plant diseases is an essential research topic as it may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. This work investigates ways to recognize the late blight disease from the analysis of tomato digital images, collected directly from the field. A pair of multilayer perceptron neural network analyzes the digital images, using data from both RGB and HSL color models, and classifies each image pixel. One neural network is responsible for the identification of healthy regions of the tomato leaf, while the other identifies the injured regions. The outputs of both networks are combined to generate the final classification of each pixel from the image and the pixel classes are used to repaint the original tomato images by using a color representation that highlights the injuries on the plant. The new images will have only green, red or black pixels, if they came from healthy or injured portions of the leaf, or from the background of the image, respectively. The system presented an accuracy of 97% in detection and estimation of the level of damage on the tomato leaves caused by late blight.Keywords: artificial neural networks, digital image processing, pattern recognition, phytosanitary
Procedia PDF Downloads 3212605 Modeling Visual Memorability Assessment with Autoencoders Reveals Characteristics of Memorable Images
Authors: Elham Bagheri, Yalda Mohsenzadeh
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Image memorability refers to the phenomenon where certain images are more likely to be remembered by humans than others. It is a quantifiable and intrinsic attribute of an image. Understanding how visual perception and memory interact is important in both cognitive science and artificial intelligence. It reveals the complex processes that support human cognition and helps to improve machine learning algorithms by mimicking the brain's efficient data processing and storage mechanisms. To explore the computational underpinnings of image memorability, this study examines the relationship between an image's reconstruction error, distinctiveness in latent space, and its memorability score. A trained autoencoder is used to replicate human-like memorability assessment inspired by the visual memory game employed in memorability estimations. This study leverages a VGG-based autoencoder that is pre-trained on the vast ImageNet dataset, enabling it to recognize patterns and features that are common to a wide and diverse range of images. An empirical analysis is conducted using the MemCat dataset, which includes 10,000 images from five broad categories: animals, sports, food, landscapes, and vehicles, along with their corresponding memorability scores. The memorability score assigned to each image represents the probability of that image being remembered by participants after a single exposure. The autoencoder is finetuned for one epoch with a batch size of one, attempting to create a scenario similar to human memorability experiments where memorability is quantified by the likelihood of an image being remembered after being seen only once. The reconstruction error, which is quantified as the difference between the original and reconstructed images, serves as a measure of how well the autoencoder has learned to represent the data. The reconstruction error of each image, the error reduction, and its distinctiveness in latent space are calculated and correlated with the memorability score. Distinctiveness is measured as the Euclidean distance between each image's latent representation and its nearest neighbor within the autoencoder's latent space. Different structural and perceptual loss functions are considered to quantify the reconstruction error. The results indicate that there is a strong correlation between the reconstruction error and the distinctiveness of images and their memorability scores. This suggests that images with more unique distinct features that challenge the autoencoder's compressive capacities are inherently more memorable. There is also a negative correlation between the reduction in reconstruction error compared to the autoencoder pre-trained on ImageNet, which suggests that highly memorable images are harder to reconstruct, probably due to having features that are more difficult to learn by the autoencoder. These insights suggest a new pathway for evaluating image memorability, which could potentially impact industries reliant on visual content and mark a step forward in merging the fields of artificial intelligence and cognitive science. The current research opens avenues for utilizing neural representations as instruments for understanding and predicting visual memory.Keywords: autoencoder, computational vision, image memorability, image reconstruction, memory retention, reconstruction error, visual perception
Procedia PDF Downloads 702604 Brand Equity Tourism Destinations: An Application in Wine Regions Comparing Visitors' and Managers' Perspectives
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The concept of brand equity in the wine tourism area is an interesting topic to explore the factors that determine it. The aim of this study is to address this gap by investigating wine tourism destinations brand equity, and understanding the impact that the denomination of origin (DO) brand image and the destination image have on brand equity. Managing and monitoring the branding of wine tourism destinations is crucial to attract tourist arrivals. The multiplicity of stakeholders involved in the branding process calls for research that, unlike previous studies, adopts a broader perspective and incorporates an internal and an external perspective. Therefore, this gap by comparing managers’ and visitors’ approaches to wine tourism destination brand equity has been addressed. A survey questionnaire for data collection purposes was used. The hypotheses were tested using winery managers and winery visitors, each leading a different position relative to the wine tourism destination brand equity. All the interviews were conducted face-to-face. The survey instrument included several scales related to DO brand image, destination image, and wine tourism destination brand equity. All items were measured on seven-point Likert scales. Partial least squares was used to analyze the accuracy of scales, the structural model, and multi-group analysis to identify the differences in the path coefficients and to test the hypotheses. The results show that the positive influence of DO brand image on wine tourism destination brand equity is stronger for wineries than for visitors, but there are no significant differences between the two groups. However, there are significant differences in the positive effect of destination brand image on both wine tourism destination brand equity and DO brand image. The results of this study are important for consultants, practitioners, and policy makers. The gap between managers and visitors calls for the development of a number of campaigns to enhance the image that visitors hold and, thus, increase tourist arrivals. Events such as wine gatherings and gastronomic symposiums held at universities and culinary schools and participation in business meetings can enhance the perceptions and in turn, the added value, brand equity of the wine tourism destinations. The images of destinations and DOs can help strengthen the brand equity of the wine tourism destinations, especially for visitors. Thus, the development and reinforcement of favorable, strong, and unique destination associations and DO associations are important to increase that value. Joint campaigns are advisable to enhance the images of destinations and DOs and, as a consequence, the value of the wine tourism destination brand.Keywords: brand equity, managers, visitors, wine tourism
Procedia PDF Downloads 1282603 Computational Cell Segmentation in Immunohistochemically Image of Meningioma Tumor Using Fuzzy C-Means and Adaptive Vector Directional Filter
Authors: Vahid Anari, Leila Shahmohammadi
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Diagnosing and interpreting manually from a large cohort dataset of immunohistochemically stained tissue of tumors using an optical microscope involves subjectivity and also is tedious for pathologist specialists. Moreover, digital pathology today represents more of an evolution than a revolution in pathology. In this paper, we develop and test an unsupervised algorithm that can automatically enhance the IHC image of a meningioma tumor and classify cells into positive (proliferative) and negative (normal) cells. A dataset including 150 images is used to test the scheme. In addition, a new adaptive color image enhancement method is proposed based on a vector directional filter (VDF) and statistical properties of filtering the window. 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: digital pathology, cell segmentation, immunohistochemically, noise reduction
Procedia PDF Downloads 602602 Medical Images Enhancement Using New Dynamic Band Pass Filter
Authors: Abdellatif Baba
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In order to facilitate medical images analysis by improving their quality and readability, we present in this paper a new dynamic band pass filter as a general and suitable operator for different types of medical images. Our objective is to enrich the details of any treated medical image to make it sufficiently clear enough to give an understood and simplified meaning even for unspecialized people in the medical domain.Keywords: medical image enhancement, dynamic band pass filter, analysis improvement
Procedia PDF Downloads 2842601 Regulating Transnational Corporations and Protecting Human Rights: Analyzing the Efficiency of International Legal Framework
Authors: Stellina Jolly
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July 18th to August 19th 2013 has gone down in the history of India for undertaking the country’s first environment referendum. The Supreme Court had ruled that the Vedanta Group's bauxite mining project in the Niyamgiri Hills of Orissa will have to get clearance from the gram sabha, which will consider the cultural and religious rights of the tribals and forest dwellers living in Rayagada and Kalahandi districts. In the Niyamgiri hills, people of small tribal hamlets were asked to voice their opinion on bauxite mining in their habitat. The ministry has reiterated its stand that mining cannot be allowed on the Niyamgiri hills because it will affect the rights of the Dongria Kondhs. The tribal person who occupies the Niyamgiri Hills in Eastern India accomplished their first success in 2010 in their struggle to protect and preserve their existence, culture and land against Vedanta a London-based mining giant. In August, 2010 Government of India revoked permission for Vedanta Resources to mine bauxite from hills in Orissa State where the Dongria Kondh live as forest dwellers. This came after various protests and reports including amnesty report wherein it highlighted that an alumina refinery in eastern India operated by a subsidiary of mining company. Vedanta was accused of causing air and water pollution that threatens the health of local people and their access to water. The abuse of human rights by corporate is not a new issue it has occurred in Africa, Asia and other parts of the world. Paper focuses on the instances and extent of human right especially in terms of environment violations by corporations. Further Paper details on corporations and sustainable development. Paper finally comes up with certain recommendation including call for a declaration by United Nations on Corporate environment Human Rights Liability.Keywords: environment, corporate, human rights, sustainable development
Procedia PDF Downloads 4692600 Optoelectronic Hardware Architecture for Recurrent Learning Algorithm in Image Processing
Authors: Abdullah Bal, Sevdenur Bal
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This paper purposes a new type of hardware application for training of cellular neural networks (CNN) using optical joint transform correlation (JTC) architecture for image feature extraction. CNNs require much more computation during the training stage compare to test process. Since optoelectronic hardware applications offer possibility of parallel high speed processing capability for 2D data processing applications, CNN training algorithm can be realized using Fourier optics technique. JTC employs lens and CCD cameras with laser beam that realize 2D matrix multiplication and summation in the light speed. Therefore, in the each iteration of training, JTC carries more computation burden inherently and the rest of mathematical computation realized digitally. The bipolar data is encoded by phase and summation of correlation operations is realized using multi-object input joint images. Overlapping properties of JTC are then utilized for summation of two cross-correlations which provide less computation possibility for training stage. Phase-only JTC does not require data rearrangement, electronic pre-calculation and strict system alignment. The proposed system can be incorporated simultaneously with various optical image processing or optical pattern recognition techniques just in the same optical system.Keywords: CNN training, image processing, joint transform correlation, optoelectronic hardware
Procedia PDF Downloads 5002599 Barnard Feature Point Detector for Low-Contractperiapical Radiography Image
Authors: Chih-Yi Ho, Tzu-Fang Chang, Chih-Chia Huang, Chia-Yen Lee
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In dental clinics, the dentists use the periapical radiography image to assess the effectiveness of endodontic treatment of teeth with chronic apical periodontitis. Periapical radiography images are taken at different times to assess alveolar bone variation before and after the root canal treatment, and furthermore to judge whether the treatment was successful. Current clinical assessment of apical tissue recovery relies only on dentist personal experience. It is difficult to have the same standard and objective interpretations due to the dentist or radiologist personal background and knowledge. If periapical radiography images at the different time could be registered well, the endodontic treatment could be evaluated. In the image registration area, it is necessary to assign representative control points to the transformation model for good performances of registration results. However, detection of representative control points (feature points) on periapical radiography images is generally very difficult. Regardless of which traditional detection methods are practiced, sufficient feature points may not be detected due to the low-contrast characteristics of the x-ray image. Barnard detector is an algorithm for feature point detection based on grayscale value gradients, which can obtain sufficient feature points in the case of gray-scale contrast is not obvious. However, the Barnard detector would detect too many feature points, and they would be too clustered. This study uses the local extrema of clustering feature points and the suppression radius to overcome the problem, and compared different feature point detection methods. In the preliminary result, the feature points could be detected as representative control points by the proposed method.Keywords: feature detection, Barnard detector, registration, periapical radiography image, endodontic treatment
Procedia PDF Downloads 4382598 Development of an Image-Based Biomechanical Model for Assessment of Hip Fracture Risk
Authors: Masoud Nasiri Sarvi, Yunhua Luo
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Low-trauma hip fracture, usually caused by fall from standing height, has become a main source of morbidity and mortality for the elderly. Factors affecting hip fracture include sex, race, age, body weight, height, body mass distribution, etc., and thus, hip fracture risk in fall differs widely from subject to subject. It is therefore necessary to develop a subject-specific biomechanical model to predict hip fracture risk. The objective of this study is to develop a two-level, image-based, subject-specific biomechanical model consisting of a whole-body dynamics model and a proximal-femur finite element (FE) model for more accurately assessing the risk of hip fracture in lateral falls. Required information for constructing the model is extracted from a whole-body and a hip DXA (Dual Energy X-ray Absorptiometry) image of the subject. The proposed model considers all parameters subject-specifically, which will provide a fast, accurate, and non-expensive method for predicting hip fracture risk.Keywords: bone mineral density, hip fracture risk, impact force, sideways falls
Procedia PDF Downloads 5252597 Exploiting JPEG2000 into Reversible Information
Authors: Te-Jen Chang, I-Hui Pan, Kuang-Hsiung Tan, Shan-Jen Cheng, Chien-Wu Lan, Chih-Chan Hu
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With the event of multimedia age in order to protect data not to be tampered, damaged, and faked, information hiding technologies are proposed. Information hiding means important secret information is hidden into cover multimedia and then camouflaged media is produced. This camouflaged media has the characteristic of natural protection. Under the undoubted situation, important secret information is transmitted out.Reversible information hiding technologies for high capacity is proposed in this paper. The gray images are as cover media in this technology. We compress gray images and compare with the original image to produce the estimated differences. By using the estimated differences, expression information hiding is used, and higher information capacity can be achieved. According to experimental results, the proposed technology can be approved. For these experiments, the whole capacity of information payload and image quality can be satisfied.Keywords: cover media, camouflaged media, reversible information hiding, gray image
Procedia PDF Downloads 3172596 New Efficient Method for Coding Color Images
Authors: Walaa M.Abd-Elhafiez, Wajeb Gharibi
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In this paper a novel color image compression technique for efficient storage and delivery of data is proposed. The proposed compression technique started by RGB to YCbCr color transformation process. Secondly, the canny edge detection method is used to classify the blocks into edge and non-edge blocks. Each color component Y, Cb, and Cr compressed by discrete cosine transform (DCT) process, quantizing and coding step by step using adaptive arithmetic coding. Our technique is concerned with the compression ratio, bits per pixel and peak signal to noise ratio, and produce better results than JPEG and more recent published schemes (like, CBDCT-CABS and MHC). The provided experimental results illustrate the proposed technique which is efficient and feasible in terms of compression ratio, bits per pixel and peak signal to noise ratio.Keywords: image compression, color image, q-coder, quantization, edge-detection
Procedia PDF Downloads 3222595 The Effect of Closed Circuit Television Image Patch Layout on Performance of a Simulated Train-Platform Departure Task
Authors: Aaron J. Small, Craig A. Fletcher
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This study investigates the effect of closed circuit television (CCTV) image patch layout on performance of a simulated train-platform departure task. The within-subjects experimental design measures target detection rate and response latency during a CCTV visual search task conducted as part of the procedure for safe train dispatch. Three interface designs were developed by manipulating CCTV image patch layout. Eye movements, perceived workload and system usability were measured across experimental conditions. Task performance was compared to identify significant differences between conditions. The results of this study have not been determined.Keywords: rail human factors, workload, closed circuit television, platform departure, attention, information processing, interface design
Procedia PDF Downloads 1602594 Contradictive Representation of Women in Postfeminist Japanese Media
Authors: Emiko Suzuki
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Although some claim that we are in a post-feminist society, the word “postfeminism” still raises questions to many. In postfeminist media, as a British sociologist Rosalind Gill points out, on the one hand, it seems to promote an empowering image of women who are active, positively sexually motivated, has free will to make market choices, and have surveillance and discipline for their personality and body, yet on the other hand, such beautiful and attractive feminist image imposes stronger surveillance of their mind and body for women. Similar representation, which is that femininity is described in a contradictive way, is seen in Japanese media as well. This study tries to capture how post-feminist Japanese media is, contrary to its ostensible messages, encouraging women to join the obedience to the labor system by affirming the traditional image of attractive women using sexual objectification and promoting values of neoliberalism. The result shows an interesting insight into how Japanese media is creating a conflicting ideal representation of women through repeatedly exposing such images.Keywords: postfeminism, Japanese media, sexual objectification, embodiment
Procedia PDF Downloads 1892593 Earnings Management from Taiwan Gisa Firms
Authors: An-an Chiu, Shaio Yan Huang, Ling-Na Chen, Wei-Hua Lin
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Research has primarily focused on listed companies, less is done regarding small and medium-sized enterprises. Under the authorities' support, Taipei Exchange (TPEx) started Go Incubation Board for Startup and Acceleration Firms (GISA) in January 2014. This platform is designed to help small-sized innovative companies grow and to enter the capital market in the future. This research yield insight into earnings management activities around seasoned equity offerings (SEO) based on Taiwan’s GISA firms and the effectiveness of external corporate governance. Data for the study come from the GISA Market Observation Post System from January 2014 to December 2016. The result finds that GISA firms prone to upward accrual-based earnings management during SEO to avoid long-term negative consequences. Especially, firms with paid-in capital more than NT$ 30 million, higher fundraising amounts, or smaller-sized firms, tend to increase discretionary accruals. Finally, consistent with prior literature, CPA firms effectively serve as the role of external corporate governances on mitigating earnings management.Keywords: GISA, earnings management, CPA, seasoned equity offerings
Procedia PDF Downloads 1292592 The Mediating Role of Bank Image in Customer Satisfaction Building
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The main objective of this research was to determine the dimensions of service quality in the banking industry of Iran. For this purpose, the study empirically examined the European perspective suggesting that service quality consists of three dimensions, technical, functional and image. This research is an applied research and its strategy is casual strategy. A standard questionnaire was used for collecting the data. 287 customers of Melli Bank of Northwest were selected through cluster sampling and were studied. The results from a banking service sample revealed that the overall service quality is influenced more by a consumer’s perception of technical quality than functional quality. Accordingly, the Gronroos model is a more appropriate representation of service quality than the American perspective with its limited concentration on the dimension of functional quality in the banking industry of Iran. So, knowing the key dimensions of the quality of services in this industry and planning for their improvement can increase the satisfaction of customers and productivity of this industry.Keywords: technical quality, functional quality, banking, image, mediating role
Procedia PDF Downloads 3612591 Narrating 1968: Felipe Cazals’ Canoa (1976) and Images of Massacre
Authors: Nancy Elizabeth Naranjo Garcia
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Canoa (1976) by Felipe Cazals is a film that exposes the consequences of power that the Mexican State exercised over the 1968 student movement. The film, in this particular way, approaches the Tlatelolco Massacre from a point of view that takes into consideration the events that led up to it. Nonetheless, the reference to the political tension in Canoa remains ambiguous. Thus, the cinematographic representation refers to an event that leaves space for reflection, and as a consequence leaves evidence of an image that signals the notion of survival as Georges Didi-Huberman points out. In addition to denouncing the oppressive force by the Mexican State, the images in Canoa also emphasize what did not happen in Tlatelolco and its condensation with the student activists. To observe the images that Canoa offers in a new light, this work proposes further exploration with the following questions; How do the images in Canoa narrate? How are the images inserted in the film? In this fashion, a more profound comprehension of the objective and the essence of the images becomes feasible. As a result, it is possible to analyze the images of Canoa with the real killing at San Miguel Canoa in literature. The film visualizes a testimony of the event that once seemed unimaginable, an image that anticipates and structures the proceeding event. Therefore, this study takes a second look at how Canoa considers not only the killing at San Miguel Canoa and the Tlatlelolco Massacre, but goes further on contextualize an unimaginable image.Keywords: cinematographic representation, student movement, Tlatelolco Massacre, unimaginable image
Procedia PDF Downloads 2052590 Reliable Soup: Reliable-Driven Model Weight Fusion on Ultrasound Imaging Classification
Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong
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It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization
Procedia PDF Downloads 762589 Iris Detection on RGB Image for Controlling Side Mirror
Authors: Norzalina Othman, Nurul Na’imy Wan, Azliza Mohd Rusli, Wan Noor Syahirah Meor Idris
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Iris detection is a process where the position of the eyes is extracted from the face images. It is a current method used for many applications such as for security purpose and drowsiness detection. This paper proposes the use of eyes detection in controlling side mirror of motor vehicles. The eyes detection method aims to make driver easy to adjust the side mirrors automatically. The system will determine the midpoint coordinate of eyes detection on RGB (color) image and the input signal from y-coordinate will send it to controller in order to rotate the angle of side mirror on vehicle. The eye position was cropped and the coordinate of midpoint was successfully detected from the circle of iris detection using Viola Jones detection and circular Hough transform methods on RGB image. The coordinate of midpoint from the experiment are tested using controller to determine the angle of rotation on the side mirrors.Keywords: iris detection, midpoint coordinates, RGB images, side mirror
Procedia PDF Downloads 4152588 Fracture Crack Monitoring Using Digital Image Correlation Technique
Authors: B. G. Patel, A. K. Desai, S. G. Shah
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The main of objective of this paper is to develop new measurement technique without touching the object. DIC is advance measurement technique use to measure displacement of particle with very high accuracy. This powerful innovative technique which is used to correlate two image segments to determine the similarity between them. For this study, nine geometrically similar beam specimens of different sizes with (steel fibers and glass fibers) and without fibers were tested under three-point bending in a closed loop servo-controlled machine with crack mouth opening displacement control with a rate of opening of 0.0005 mm/sec. Digital images were captured before loading (unreformed state) and at different instances of loading and were analyzed using correlation techniques to compute the surface displacements, crack opening and sliding displacements, load-point displacement, crack length and crack tip location. It was seen that the CMOD and vertical load-point displacement computed using DIC analysis matches well with those measured experimentally.Keywords: Digital Image Correlation, fibres, self compacting concrete, size effect
Procedia PDF Downloads 3772587 Clothes Identification Using Inception ResNet V2 and MobileNet V2
Authors: Subodh Chandra Shakya, Badal Shrestha, Suni Thapa, Ashutosh Chauhan, Saugat Adhikari
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To tackle our problem of clothes identification, we used different architectures of Convolutional Neural Networks. Among different architectures, the outcome from Inception ResNet V2 and MobileNet V2 seemed promising. On comparison of the metrices, we observed that the Inception ResNet V2 slightly outperforms MobileNet V2 for this purpose. So this paper of ours proposes the cloth identifier using Inception ResNet V2 and also contains the comparison between the outcome of ResNet V2 and MobileNet V2. The document here contains the results and findings of the research that we performed on the DeepFashion Dataset. To improve the dataset, we used different image preprocessing techniques like image shearing, image rotation, and denoising. The whole experiment was conducted with the intention of testing the efficiency of convolutional neural networks on cloth identification so that we could develop a reliable system that is good enough in identifying the clothes worn by the users. The whole system can be integrated with some kind of recommendation system.Keywords: inception ResNet, convolutional neural net, deep learning, confusion matrix, data augmentation, data preprocessing
Procedia PDF Downloads 1752586 Addressing the Exorbitant Cost of Labeling Medical Images with Active Learning
Authors: Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj
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Successful application of deep learning in medical image analysis necessitates unprecedented amounts of labeled training data. Unlike conventional 2D applications, radiological images can be three-dimensional (e.g., CT, MRI), consisting of many instances within each image. The problem is exacerbated when expert annotations are required for effective pixel-wise labeling, which incurs exorbitant labeling effort and cost. Active learning is an established research domain that aims to reduce labeling workload by prioritizing a subset of informative unlabeled examples to annotate. Our contribution is a cost-effective approach for U-Net 3D models that uses Monte Carlo sampling to analyze pixel-wise uncertainty. Experiments on the AAPM 2017 lung CT segmentation challenge dataset show that our proposed framework can achieve promising segmentation results by using only 42% of the training data.Keywords: image segmentation, active learning, convolutional neural network, 3D U-Net
Procedia PDF Downloads 1402585 An Appraisal of Mining Sector Corporate Social Responsibility Processes in Mhondoro-Ngezi, Zimbabwe
Authors: A. T. Muruviwa
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To-date, the discourse on corporate social responsibility (CSR) has primarily centred on the actions and inactions of corporations; hence, the dominant focus on CSR has been on impacts and outcomes. The obscuring effect of this approach has, arguably, resulted in the emergence of what may be termed a ‘Northern’ agenda on CSR theory and practice, in contrast to an emergency ‘Southern’ discourse, which appears to highlight the crucial issues of poverty reduction, infrastructure development and the broader questions of social provisioning and community empowerment. Some scholars have explicitly called for a CSR research agenda that focuses on the 'reciprocal duties' of the stakeholders in the CSR process rather than fixate on the actions and inactions of business. It is against the backdrop of these contestations that this study assesses the reciprocal relationships amongst CSR stakeholders in a Zimbabwean platinum mining town, with a view to demonstrating how such relationships – and the expectations and obligations embedded in them – impact on the success or failure of CSR initiatives. The existence of mutual relations between the corporation and its stakeholders signifies the successes of CSR processes and hence the outcomes. The company is Zimplats Mining Company; the community is Mhondoro-Ngezi, and the stakeholders are clearly identified in the study. The study utilised a triangulated design, with data collected using a mini survey, focus groups, in-depth interview and observation. The key findings are that the CSR process in the study community is dominated by the mining company. Despite the existence of a CSR framework that recognises government, local leaders and community members as legitimate stakeholders, there is little evidence of concrete contributions made by these stakeholders towards the realisation of CSR objectives. As a result, the community development process – in so far as CSR is concerned – fails to address the developmental concerns of the various stakeholders. On the basis of these findings, the study concludes that there is a crisis of reciprocity in the CSR process in Mhondoro-Ngezi, and that a situation where the conceptualisation of local development needs and the deployment of specific development tools seems to be driven by one stakeholder almost to the exclusion of all others, can only present contradictory development outcomes. The significance of this study is that it allows for the development of a more nuanced and robust CSR discourse. Rather than focusing on the corporate and stakeholder perspectives and outcomes of CSR initiatives, this study examines the CSR- development nexus by interrogating the idea of reciprocal responsibility as a sin qua non to CSR success. This analytical strategy and focus allow the researcher to gain a clear understanding of how stakeholder relationships and duties influence CSR processes and also the overall outcome. At a more practical level, the findings of the study should help to shape the policy on corporate community relationships with a view to enhancing the role of mining in development.Keywords: community development, processes, reciprocity, stakeholders
Procedia PDF Downloads 3412584 Looking beyond Lynch's Image of a City
Authors: Sandhya Rao
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Kevin Lynch’s Theory on Imeageability, let on explore a city in terms of five elements, Nodes, Paths, Edges, landmarks and Districts. What happens when we try to record the same data in an Indian context? What happens when we apply the same theory of Imageability to a complex shifting urban pattern of the Indian cities and how can we as Urban Designers demonstrate our role in the image building ordeal of these cities? The organizational patterns formed through mental images, of an Indian city is often diverse and intangible. It is also multi layered and temporary in terms of the spirit of the place. The pattern of images formed is loaded with associative meaning and intrinsically linked with the history and socio-cultural dominance of the place. The embedded memory of a place in one’s mind often plays an even more important role while formulating these images. Thus while deriving an image of a city one is often confused or finds the result chaotic. The images formed due to its complexity are further difficult to represent using a single medium. Under such a scenario it’s difficult to derive an output of an image constructed as well as make design interventions to enhance the legibility of a place. However, there can be a combination of tools and methods that allows one to record the key elements of a place through time, space and one’s user interface with the place. There has to be a clear understanding of the participant groups of a place and their time and period of engagement with the place as well. How we can translate the result obtained into a design intervention at the end, is the main of the research. Could a multi-faceted cognitive mapping be an answer to this or could it be a very transient mapping method which can change over time, place and person. How does the context influence the process of image building in one’s mind? These are the key questions that this research will aim to answer.Keywords: imageability, organizational patterns, legibility, cognitive mapping
Procedia PDF Downloads 3042583 Corporate Social Responsibility (CSR) and Energy Efficiency: Empirical Evidence from the Manufacturing Sector of India
Authors: Baikunthanath Sahoo, Santosh Kumar Sahu, Krishna Malakar
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With the essence of global environmental sustainability and green business management, the wind of business research moved towards Corporate Social Responsibility. In addition to international and national treaties, businesses have also started realising environmental protection and energy efficiency through CSR as part of business strategy in response to climate change. Considering the ambitious emission reduction target and rapid economic development of India, this study is an attempt to explore the effect of CSR on the energy efficiency management of manufacturing firms in India. By using firm-level data, the panel fixed effect model shows that the CSR dummy variable is negatively influencing the energy intensity or technically, they are energy efficient. The result demonstrates that in the presence of CSR, all the production economic variables are significant. The result also shows that doing environmental expenditure does not improve energy efficiency might be because very few firms are motivated to do such expenditure and also not common to all sectors. The interactive effect model result conforms that without considering CSR dummy as an intervening variable only Manufacturers of Chemical and Chemical products, Manufacturers of Pharmaceutical, medical chemical, and botanical products firms energy intensity low but after considering CSR in their business practices all six sub-sector firms become energy efficient. The empirical result also validate that firms are continuously engaged in CSR activities they are highly energy efficient. It is an important motivational factor for firms to become economically and environmentally sustainable in the corporate world. This analysis would help business practitioners to know how to manage today’s profitability and tomorrow’s sustainability to achieve a comparative advantage in the emerging market economy. The paper concludes that reducing energy consumption as part of their social responsibility to care for the environment, will need collaborative efforts of business society and policy bodies.Keywords: CSR, Energy Efficiency, Indian manufacturing Sector, Business strategy
Procedia PDF Downloads 76