Search results for: corporate image

Authors: Karthiyayini Nagarajan, P. V. RamaKrishna

Abstract:

Radar Imaging techniques provides extensive applications in the field of remote sensing, majorly Synthetic Aperture Radar(SAR) that provide high resolution target images. This paper work puts forward the effective and realizable signal generation and processing for SAR images. The major units in the system include camera, signal generation unit, signal processing unit and display screen. The real radio channel is replaced by its mathematical model based on optical image to calculate a reflected signal model in real time. Signal generation realizes the algorithm and forms the radar reflection model. Signal processing unit provides range and azimuth resolution through matched filtering and spectrum analysis procedure to form radar image on the display screen. The restored image has the same quality as that of the optical image. This SAR imaging system has been designed and implemented using MATLAB and Quartus II tools on Stratix III device as a System(lab bench) that works in real time to study/investigate on radar imaging rudiments and signal processing scheme for educational and research purposes.

Keywords: synthetic aperture radar, radio reflection model, lab bench

Procedia PDF Downloads 458

Authors: Hossein Shareh, Farhad Seifi

Abstract:

The present study was to examine the role of attachment styles, gender schemas, sexual-self schemas, and body image during sexual activity in sexual function, marital satisfaction, and sexual self-esteem. The sampling method was among married women who were living in Mashhad; a snowball selected 765 people. Questionnaires and measures of adult attachment style (AAS), Bem Sex Role Inventory (BSRI), sexual self-schema (SSS), body exposure during sexual activity questionnaire (BESAQ), sexual function female inventory (FSFI), a short form of sexual self-esteem (SSEI-W-SF) and marital satisfaction (Enrich) were completed by participants. Data analysis using Pearson correlation and hierarchical regression and case analysis was performed by SPSS-19 software. The results showed that there is a significant correlation (P <0.05) between attachment and sexual function (r=0.342), marital satisfaction (r=0.351) and sexual self-esteem (r =0.292). A correlation (P <0.05) was observed between sexual schema (r=0.342) and sexual esteem (r=0.31). A meaningful correlation (P <0.05) exists between gender stereotypes and sexual function (r=0.352). There was a significant inverse correlation (P <0.05) between body image and their performance during sexual activity (r=0.41). There is no significant relationship between gender schemas, sexual schemas, body image, and marital satisfaction, and no relation was found between gender schemas, body image, and sexual self-esteem. Also, the result of the regression showed that attachment styles, gender schemas, sexual self- schemas, and body exposures during sexual activity are predictable in sexual function, and marital satisfaction can be predicted by attachment style and gender schema. Somewhat, sexual self-esteem can be expected by attachment style and gender schemas.

Keywords: attachment styles, gender and sexual schemas, body image, sexual function, marital satisfaction, sexual self-esteem

Procedia PDF Downloads 25

Authors: Azam Abkhiz, Abolghasem Nasir

Abstract:

To achieve sustainable competitive advantage in the market, it is necessary to provide and improve customer satisfaction and Loyalty. To reach this objective, companies need to identify and analyze their customers. Thus, it is critical to measure the level of customer satisfaction and Loyalty very carefully. This study attempts to build a conceptual model to provide clear insights of customer loyalty. Using Bayesian networks (BNs), a model is proposed to evaluate customer loyalty and its consequences, such as repurchase and positive word-of-mouth. BN is a probabilistic approach that predicts the behavior of a system based on observed stochastic events. The most relevant determinants of customer loyalty are identified by the literature review. Perceived value, service quality, trust, corporate image, satisfaction, and switching costs are the most important variables that explain customer loyalty. The data are collected by use of a questionnaire-based survey from 1430 customers of a home appliances manufacturer in Iran. Four scenarios and sensitivity analyses are performed to run and analyze the impact of different determinants on customer loyalty. The proposed model allows businesses to not only set their targets but proactively manage their customer behaviors as well.

Keywords: customer satisfaction, customer loyalty, Bayesian networks, home appliances industry

Procedia PDF Downloads 130

Authors: Deniz Guven, Wil Ward, Jinming Duan, Li Bai

Abstract:

Over the past two decades or so, Optical Coherence Tomography (OCT) has been used to diagnose retina and optic nerve diseases. The retinal nerve fibre layer, for example, is a powerful diagnostic marker for detecting and staging glaucoma. With the advances in optical imaging hardware, the adoption of OCT is now commonplace in clinics. More and more OCT images are being generated, and for these OCT images to have clinical applicability, accurate automated OCT image segmentation software is needed. Oct image segmentation is still an active research area, as OCT images are inherently noisy, with the multiplicative speckling noise. Simple edge detection algorithms are unsuitable for detecting retinal layer boundaries in OCT images. Intensity fluctuation, motion artefact, and the presence of blood vessels also decrease further OCT image quality. In this paper, we introduce a new method for segmenting three-dimensional (3D) OCT images. This involves the use of a Kalman filter, which is commonly used in computer vision for object tracking. The Kalman filter is applied to the 3D OCT image volume to track the retinal layer boundaries through the slices within the volume and thus segmenting the 3D image. Specifically, after some pre-processing of the OCT images, points on the retinal layer boundaries in the first image are identified, and curve fitting is applied to them such that the layer boundaries can be represented by the coefficients of the curve equations. These coefficients then form the state space for the Kalman Filter. The filter then produces an optimal estimate of the current state of the system by updating its previous state using the measurements available in the form of a feedback control loop. The results show that the algorithm can be used to segment the retinal layers in OCT images. One of the limitations of the current algorithm is that the curve representation of the retinal layer boundary does not work well when the layer boundary is split into two, e.g., at the optic nerve, the layer boundary split into two. This maybe resolved by using a different approach to representing the boundaries, such as b-splines or level sets. The use of a Kalman filter shows promise to developing accurate and effective 3D OCT segmentation methods.

Keywords: optical coherence tomography, image segmentation, Kalman filter, object tracking

Procedia PDF Downloads 475

Authors: Tong He, Long Chen, Irag Mantegh, Wen-Fang Xie

Abstract:

This paper proposes an image-based obstacle avoidance and tracking target identification strategy in GPS-degraded or GPS-denied environment for an Unmanned Aerial Vehicle (UAV). The traditional force algorithm for obstacle avoidance could produce local minima area, in which UAV cannot get away obstacle effectively. In order to eliminate it, an artificial potential approach based on harmonic potential is proposed to guide the UAV to avoid the obstacle by using the vision system. And image-based visual servoing scheme (IBVS) has been adopted to implement the proposed obstacle avoidance approach. In IBVS, the pixel accuracy is a key factor to realize the obstacle avoidance. In this paper, the deep reinforcement learning framework has been applied by reducing pixel errors through constant interaction between the environment and the agent. In addition, the combination of OpenTLD and Tensorflow based on neural network is used to identify the type of tracking target. Numerical simulation in Matlab and ROS GAZEBO show the satisfactory result in target identification and obstacle avoidance.

Keywords: image-based visual servoing, obstacle avoidance, tracking target identification, deep reinforcement learning, artificial potential approach, neural network

Procedia PDF Downloads 134

Authors: Bola Adeleke, Kayode Ogunsusi

Abstract:

Heritage sites have evolved to preserve culture and heritage and also to educate and entertain tourists. Tourist travel decisions and behavior are influenced by destination image and value of the experience of tourists. Perceived value is one of the important tools for securing a competitive edge in tourism destinations. The model of Ritchie and Crouch distinguished 36 attributes of competitiveness which are classified into five factors which are quality of experience, touristic attractiveness, environment and infrastructure, entertainment/outdoor activities and cultural traditions. The study extended this model with a different grouping of the determinants of destination competitiveness. The theoretical framework used for this study assumes that apart from attractions already situated in the grove, satisfaction with destination common service, and entertainment and events, can all be used in creating a positive image for/and in attracting customers (destination selection) to visit Osun Sacred Osogbo Grove during and after annual celebrations. All these will impact positively on travel experience of customers as well as their spiritual fulfillment. Destination image has a direct impact on tourists’ satisfaction which consequently impacts on tourists’ likely future behavior on whether to revisit a cultural destination or not. The study investigated the variables responsible for destination image competitiveness of the Heritage Site; assessed the factors enhancing the destination image; and evaluated the perceived value realized by tourists from their cultural experience at the grove. A complete enumeration of tourists above 18 years of age who visited the Heritage Site within the month of March and April 2017 was taken. 240 respondents, therefore, were used for the study. The structured questionnaire with 5 Likert scales was administered. Five factors comprising 63 variables were used to determine the destination image competitiveness through principal component analysis, while multiple regressions were used to evaluate perceived value of tourists at the grove. Results revealed that 11 out of the 12 variables determining the destination image competitiveness were significant in attracting tourists to the grove. From the R-value, all factors predicted tourists’ value of experience strongly (R= 0.936). The percentage variance of customer value was explained by 87.70% of the variance of destination common service, entertainment and event satisfaction, travel environment satisfaction and spiritual satisfaction, with F-value being significant at 0.00. Factors with high alpha value contributed greatly to adding value to enhancing destination and tourists’ experience. 11 variables positively predicted tourist value with significance. Managers of Osun World Heritage Site should improve on variables critical to adding values to tourists’ experience.

Keywords: competitiveness, destination image, Osun Osogbo world heritage site, tourists

Procedia PDF Downloads 178

Authors: Manmeet Kaur, Madhu Vij

Abstract:

The Board of Directors in a firm performs the primary role of an internal control mechanism. This Study seeks to understand the relationship between internal governance and performance of banks in India. The research paper investigates the effect of board structure (proportion of nonexecutive directors, gender diversity, board size and meetings per year) on the firm performance. This paper evaluates the impact of corporate governance mechanisms on bank’s financial performance using panel data for 28 listed banks in National Stock Exchange of India for the period of 2008-2014. Returns on Asset, Return on Equity, Tobin’s Q and Net Interest Margin were used as the financial performance indicators. To estimate the relationship among governance and bank performance initially the Study uses Pooled Ordinary Least Square (OLS) Estimation and Generalized Least Square (GLS) Estimation. Then a well-developed panel Generalized Method of Moments (GMM) Estimator is developed to investigate the dynamic nature of performance and governance relationship. The Study empirically confirms that two-step system GMM approach controls the problem of unobserved heterogeneity and endogeneity as compared to the OLS and GLS approach. The result suggests that banks with small board, boards with female members, and boards that meet more frequently tend to be more efficient and subsequently have a positive impact on performance of banks. The study offers insights to policy makers interested in enhancing the quality of governance of banks in India. Also, the findings suggest that board structure plays a vital role in the improvement of corporate governance mechanism for financial institutions. There is a need to have efficient boards in banks to improve the overall health of the financial institutions and the economic development of the country.

Keywords: board of directors, corporate governance, GMM estimation, Indian banking

Procedia PDF Downloads 248

Authors: P. Subbuthai, S. Muruganand

Abstract:

Diabetic Retinopathy is one of the complicated diseases and it is caused by the changes in the blood vessels of the retina. Extraction of retina image through Fundus camera sometimes produced poor contrast and noises. Because of this noise, detection of blood vessels in the retina is very complicated. So preprocessing is needed, in this paper, a novel algorithm is implemented to remove the noisy pixel in the retina image. The proposed algorithm is Extended Median Filter and it is applied to the green channel of the retina because green channel vessels are brighter than the background. Proposed extended median filter is compared with the existing standard median filter by performance metrics such as PSNR, MSE and RMSE. Experimental results show that the proposed Extended Median Filter algorithm gives a better result than the existing standard median filter in terms of noise suppression and detail preservation.

Keywords: fundus retina image, diabetic retinopathy, median filter, microaneurysms, exudates

Procedia PDF Downloads 331

Authors: Tanapond S.

Abstract:

Typically, most of the controlling firms are relate to family firms which are widespread and important for economic growth particularly in Asian Pacific region. The unique characteristics of the controlling families tend to play an important role in determining the corporate policies such as dividend policy. Given the complexity of the family business phenomenon, the empirical evidence has been unclear on how the families behind business groups influence dividend policy in Asian markets with the prevalent existence of cross-shareholdings and pyramidal structure. Dividend policy as one of an important determinant of firm value could also be implemented in order to examine the effect of the controlling families behind business groups on strategic decisions-making in terms of a governance perspective and agency problems. The purpose of this paper is to investigate the impact of ownership structure and concentration which are influential internal corporate governance mechanisms in family firms on dividend decision-making. Using panel data and constructing a unique dataset of family ownership and control through hand-collecting information from the nonfinancial companies listed in Stock Exchange of Thailand (SET) between 2000 and 2015, the study finds that family firms with large stakes distribute higher dividends than family firms with small stakes. Family ownership can mitigate the agency problems and the expropriation of minority investors in family firms. To provide insight into the distinguish between ownership rights and control rights, this study examines specific firm characteristics including the degrees of concentration of controlling shareholders by classifying family ownership in different categories. The results show that controlling families with large deviation between voting rights and cash flow rights have more power and affect lower dividend payment. These situations become worse when second blockholders are families. To the best knowledge of the researcher, this study is the first to examine the association between family firms’ characteristics and dividend policy from the corporate governance perspectives in Thailand with weak investor protection environment and high ownership concentration. This research also underscores the importance of family control especially in a context in which family business groups and pyramidal structure are prevalent. As a result, academics and policy makers can develop markets and corporate policies to eliminate agency problem.

Keywords: agency theory, dividend policy, family control, Thailand

Procedia PDF Downloads 273

Authors: Ojo Adeshina Akinwumi

Abstract:

This study investigated leadership style and organizational culture as predictors of unethical work behaviour among employees in corporate organizations. This study adopted an expo facto research design. Two Hundred and Seventy-Four (274) employees (149 males, 125 females) sampled from the organization participated in the study. Their ages ranged from 19 to 65, with a mean of 36.36 years and a standard deviation of 10.43. Unethical Work Behaviour was measured using Unethical Work Behaviour Scale (UWBC), Organizational Culture was measured using Organizational Culture Scale, (and OCS and Leadership Styles were measured using Multifactor Leadership Questionnaire (LSMLQ). Two hypotheses were formulated and tested using Pearson Product Moment Correlation and Multiple Regressions Analysis. Results indicated that leadership styles had no significant relationship with unethical work behaviour (r(274)=.09;>0.05). However, organizational culture had a significant relationship with unethical work behaviour (r(274)=.15;p,0.05). Lastly, leadership style and organizational culture jointly predicted unethical work behaviour among employees. [F (2, 273) =3.65, p<0.05). Findings from this study were discussed in line with existing literature. It was also recommended that leadership styles and organizational culture should be improved upon in order to reduce unethical work behaviour by employees.

Keywords: leadership style, organizational culture, unethical work behavior, employees in corporate organisations in Nigeria

Procedia PDF Downloads 104

Authors: Mark Harmon, Abdolghani Ebrahimi, Patrick Lucey, Diego Klabjan

Abstract:

In this paper, we predict the likelihood of a player making a shot in basketball from multiagent trajectories. Previous approaches to similar problems center on hand-crafting features to capture domain-specific knowledge. Although intuitive, recent work in deep learning has shown, this approach is prone to missing important predictive features. To circumvent this issue, we present a convolutional neural network (CNN) approach where we initially represent the multiagent behavior as an image. To encode the adversarial nature of basketball, we use a multichannel image which we then feed into a CNN. Additionally, to capture the temporal aspect of the trajectories, we use “fading.” We find that this approach is superior to a traditional FFN model. By using gradient ascent, we were able to discover what the CNN filters look for during training. Last, we find that a combined FFN+CNN is the best performing network with an error rate of 39%.

Keywords: basketball, computer vision, image processing, convolutional neural network

Procedia PDF Downloads 143

Authors: Sana Masmoudi, Yosra Makni

Abstract:

Regulators highlight the importance of the Audit Committee (AC) as a key internal corporate governance mechanism. One of the most important roles of this committee is to oversee the financial reporting process. The purpose of this paper is to examine the link between the characteristics of an audit committee and the financial reporting quality by investigating whether the formation of audit committees and their characteristics are associated with improved financial reporting quality. This study provides empirical evidence of the association between audit committee independence, financial expertise, gender diversity, and meetings and Real Earnings Management (REM) as a proxy of financial reporting quality. Using data from, with a sample of 80 companies listed on the Amsterdam Stock Exchange during 2010-2017, the study finds that independence and AC Gender diversity are strongly related to financial reporting quality. In fact, these two characteristics constrain REM. The results also suggest that AC-financial expertise reduces to some extent, the likelihood of engaging in REM. These conclusions provide support then to the audit committee requirement under the Dutch Corporate Governance Code rules regarding gender diversity and AC meetings.

Keywords: audit committee, financial expertise, independence, real earnings management

Procedia PDF Downloads 158

Authors: Qasim Munye, Juned Islam, Haseeb Qureshi, Syed Jung

Abstract:

Lung nodules are commonly identified in computed tomography (CT) scans by experienced radiologists at a relatively late stage. Early diagnosis can greatly increase survival. We propose using a pix2pix conditional generative adversarial network to generate realistic images simulating early-stage lung nodule growth. We have applied deep images prior to 2341 slices from 895 computed tomography (CT) scans from the Lung Image Database Consortium (LIDC) dataset to generate pseudo-healthy medical images. From these images, 819 were chosen to train a pix2pix network. We observed that for most of the images, the pix2pix network was able to generate images where the nodule increased in size and intensity across epochs. To evaluate the images, 400 generated images were chosen at random and shown to a medical student beside their corresponding original image. Of these 400 generated images, 384 were defined as satisfactory - meaning they resembled a nodule and were visually similar to the corresponding image. We believe that this generated dataset could be used as training data for neural networks to detect lung nodules at an early stage or to improve the accuracy of such networks. This is particularly significant as datasets containing the growth of early-stage nodules are scarce. This project shows that the combination of deep image prior and generative models could potentially open the door to creating larger datasets than currently possible and has the potential to increase the accuracy of medical classification tasks.

Keywords: medical technology, artificial intelligence, radiology, lung cancer

Procedia PDF Downloads 60

Authors: M. F. Haroun, T. A. Gulliver

Abstract:

In this paper, an encryption algorithm is proposed for real-time image encryption. The scheme employs a dual chaotic generator based on a three dimensional (3D) discrete Lorenz attractor. Encryption is achieved using non-autonomous modulation where the data is injected into the dynamics of the master chaotic generator. The second generator is used to permute the dynamics of the master generator using the same approach. Since the data stream can be regarded as a random source, the resulting permutations of the generator dynamics greatly increase the security of the transmitted signal. In addition, a technique is proposed to mitigate the error propagation due to the finite precision arithmetic of digital hardware. In particular, truncation and rounding errors are eliminated by employing an integer representation of the data which can easily be implemented. The simple hardware architecture of the algorithm makes it suitable for secure real-time applications.

Keywords: chaotic systems, image encryption, non-autonomous modulation, FPGA

Procedia PDF Downloads 501

Authors: Waqqas-ur-Rehman Butt, Martin Servin, Marion Pause

Abstract:

In recent years, object detection has gained much attention and very encouraging research area in the field of computer vision. The robust object boundaries detection in an image is demanded in numerous applications of human computer interaction and automated surveillance systems. Many methods and approaches have been developed for automatic object detection in various fields, such as automotive, quality control management and environmental services. Inappropriately, to the best of our knowledge, object detection under illumination with shadow consideration has not been well solved yet. Furthermore, this problem is also one of the major hurdles to keeping an object detection method from the practical applications. This paper presents an approach to automatic object detection in images under non-standardized environmental conditions. A key challenge is how to detect the object, particularly under uneven illumination conditions. Image capturing conditions the algorithms need to consider a variety of possible environmental factors as the colour information, lightening and shadows varies from image to image. Existing methods mostly failed to produce the appropriate result due to variation in colour information, lightening effects, threshold specifications, histogram dependencies and colour ranges. To overcome these limitations we propose an object detection algorithm, with pre-processing methods, to reduce the interference caused by shadow and illumination effects without fixed parameters. We use the Y CrCb colour model without any specific colour ranges and predefined threshold values. The segmented object regions are further classified using morphological operations (Erosion and Dilation) and contours. Proposed approach applied on a large image data set acquired under various environmental conditions for wood stack detection. Experiments show the promising result of the proposed approach in comparison with existing methods.

Keywords: image processing, illumination equalization, shadow filtering, object detection

Procedia PDF Downloads 207

Authors: G. Bruno, A. Ciavarella, N. Linciano

Abstract:

The proportion of women in boardroom has traditionally been low around the world. Over the last decades, several jurisdictions opted for active intervention, which triggered a tangible progress in female representation. In Europe, many countries have implemented boardroom diversity policies in the form of legal quotas (Norway, Italy, France, Germany) or governance code amendments (United Kingdom, Finland). Policy actions rest, among other things, on the assumption that gender balanced boards result in improved corporate governance and performance. The investigation of the relationship between female boardroom representation and firm value is therefore key on policy grounds. The evidence gathered so far, however, has not produced conclusive results also because empirical studies on the impact of voluntary female board representation had to tackle with endogeneity, due to either differences in unobservable characteristics across firms that may affect their gender policies and governance choices, or potential reverse causality. In this paper, we study the relationship between the presence of female directors and corporate performance in Italy, where the Law 120/2011 envisaging mandatory quotas has introduced an exogenous shock in board composition which may enable to overcome reverse causality. Our sample comprises Italian firms listed on the Italian Stock Exchange and the members of their board of directors over the period 2008-2016. The study relies on two different databases, both drawn from CONSOB, referring respectively to directors and companies’ characteristics. On methodological grounds, information on directors is treated at the individual level, by matching each company with its directors every year. This allows identifying all time-invariant, possibly correlated, elements of latent heterogeneity that vary across firms and board members, such as the firm immaterial assets and the directors’ skills and commitment. Moreover, we estimate dynamic panel data specifications, so accommodating non-instantaneous adjustments of firm performance and gender diversity to institutional and economic changes. In all cases, robust inference is carried out taking into account the bidimensional clustering of observations over companies and over directors. The study shows the existence of a U-shaped impact of the percentage of women in the boardroom on profitability, as measured by Return On Equity (ROE) and Return On Assets. Female representation yields a positive impact when it exceeds a certain threshold, ranging between about 18% and 21% of the board members, depending on the specification. Given the average board size, i.e., around ten members over the time period considered, this would imply that a significant effect of gender diversity on corporate performance starts to emerge when at least two women hold a seat. This evidence supports the idea underpinning the critical mass theory, i.e., the hypothesis that women may influence.

Keywords: gender diversity, quotas, firms performance, corporate governance

Procedia PDF Downloads 163

Authors: Evan W. Krieger, Vijayan K. Asari, Saibabu Arigela

Abstract:

Video imagery captured for real-time security and surveillance applications is typically captured in complex lighting conditions. These less than ideal conditions can result in imagery that can have underexposed or overexposed regions. It is also typical that the video is too low in resolution for certain applications. The purpose of security and surveillance video is that we should be able to make accurate conclusions based on the images seen in the video. Therefore, if poor lighting and low resolution conditions occur in the captured video, the ability to make accurate conclusions based on the received information will be reduced. We propose a solution to this problem by using image preprocessing to improve these images before use in a particular application. The proposed algorithm will integrate an intensity enhancement algorithm with a super resolution technique. The intensity enhancement portion consists of a nonlinear inverse sign transformation and an adaptive contrast enhancement. The super resolution section is a single image super resolution technique is a Fourier phase feature based method that uses a machine learning approach with kernel regression. The proposed technique intelligently integrates these algorithms to be able to produce a high quality output while also being more efficient than the sequential use of these algorithms. This integration is accomplished by performing the proposed algorithm on the intensity image produced from the original color image. After enhancement and super resolution, a color restoration technique is employed to obtain an improved visibility color image.

Keywords: dynamic range compression, multi-level Fourier features, nonlinear enhancement, super resolution

Procedia PDF Downloads 543

Authors: Dhruv Saini, Megha Sharma, Sharad Gupta

Abstract:

This research is showing the use of celebrity endorsement and social media influencers and how they help in enhancing the brand loyalty of the consumers. The study aims at keeping brand image of the brand as the link between the two. However, choosing the right celebrity or social media influencer is not an easy task and it is very essential for a brand to select the right ambassador for advertising their products and for selling the product to the ultimate consumer. The purpose of the study is to create a relationship of Celebrity endorsement with brand image and with brand loyalty and creating a relationship of Social media influencers with brand image and with brand loyalty and then making a comparison between the two by measuring the effects of both simultaneously. And then by analyzing which among the two has a greater impact on brand loyalty of the consumers. The study mainly focuses on four major variables namely Celebrity endorsement, Social media influencers, Brand image and Brand loyalty. The study also focuses on interdependence and relationships that these variables have with each other and how they are linked with each other. The study also aims at looking which among Celebrity endorsement and Social media influencer has a greater impact on increasing or enhancing the loyalty for a brand. Earlier celebrity endorsers had a major impact on brand loyalty of the consumers but with time social media influencers are also playing a very vital role in impacting the brand loyalty of the consumers and are giving a fight to the celebrity endorsers as well. Also, Brand image also has a very vital role to play in enhancing the brand loyalty of a brand in the minds of the consumers as a well-known and a better perception of a brand leads to retention of more and more consumers. Also, both Celebrity endorsement and Social media influencers are two-way swords as both have a number of positives and a number of negatives as well, so these are to be compared keeping in mind their adverse effects. Examination of the current market situation has shown that the recommendations of celebrities when properly integrated by comparing product strengths. Advertisers agree that celebrity authorization does not guarantee sales but it can create buzz and make the consumer feel better by-product, which is also what customers should expect as a real star by delivering the promise. On the other hand, depending on the results of the studies, there should be a variety of conclusions planned. Some of the influential people on social media had a positive impact on the product portrait. One of the conclusions is that the product image had a positive impact on consumers. Moreover, the results of the following study states that the most influential influencers consumers in their intended purpose of the purchase, but instead produced a positive result indirectly with Brand image which would further lead to brand loyalty .

Keywords: brand image, brand loyalty, celebrity endorsement, social media influencer

Procedia PDF Downloads 185

Authors: L. U. Dumuje, R. Leite

Abstract:

There is an ongoing debate in terms of corporate social responsibility (CSR) initiative in Niger Delta, Nigeria, that originates from existing gap between stated objective of organizations in the Nigerian oil sector and their main activities that threaten the society. CSR in developing countries is becoming popular, and to contribute to scientific knowledge, we need to research on CSR practices and discourse in indigenous Nigeria that is scarce. Despite governments mandate in terms of unofficial blazing, methane gas is released into the air around refinery area which contributes to global warming. There is a need to understand if this practice applies to indigenous oil companies in Nigeria. To get a better understanding of CSR among indigenous oil companies in Nigeria, our study focuses on discourse and rhetoric regarding CSR. This current paper contributions is twofold: on the one hand, it aims to better understand practitioner’s rationale and fundamentals of CSR in Nigerian oil companies. On the other hand, it intends to identify the stages of CSR initiatives, advantages and difficulties of CSR implementation in indigenous Nigeria oil sector. This current paper uses the qualitative research as a methodological strategy. Instrument for data collection is semi-structured interview. Besides 28 interviews, we conduct five focus group discussions with stakeholders. Participant for this study consist of: employees, managers and executives of indigenous oil companies in Nigeria. It is relevant to mention, key informants as government institution, environmental organization and community leader/member are part of our sample. It is important that despite significant findings in some studies, there are still some gaps. To help filling this existing gaps, we have formulated some research questions, as follows: ‘What are the stages, opportunities and obstacles of having corporate social responsibility practice in indigenous oil companies in Nigeria’. This ongoing research sub-questions as follows: What are the CSR discourses and practices among indigenous companies in the Nigerian oil sector; what is the actual status regarding CSR development; what are the main perceptions of opportunities and obstacles with regard to CSR in indigenous Nigerian oil companies; who are the main stakeholders of indigenous Nigerian oil companies and their different meanings and understandings of CSR practices. Regarding the above questions, the following objectives have been determined: first, we conduct a literature review with the aim of understanding and identifying importance of CSR practises in western and developing countries. Second, this current paper identify specific characteristics of the national context in terms of CSR engagement in Nigeria, so we perform empirical research with relevant stakeholder in indigenous Nigerian, as well as key informants, in order to identify development of CSR and different perception of this praised initiative, CSR.

Keywords: corporate social responsibility, indigenous, oil organizations, Nigeria, practice

Procedia PDF Downloads 123

Authors: Thalia Viveros-Uehara

Abstract:

The virtues of Corporate Social Responsibility (CSR) are explored widely in the academic literature. However, few studies address its link to human rights, per se; specifically, the right to a safe, clean and healthy environment. Fewer still are the research works in this area that relate to developing countries, where a number of areas are biodiversity hotspots. In Mexico, despite the rise and evolution of CSR schemes, grave episodes of pollution persist, especially those caused by the mining industry. These cases set up the question of the correspondence between the current CSR practices of mining companies in the country and their responsibility to respect the right to a safe, clean and healthy environment. The present study approaches precisely such a bridge, which until now has not been fully tackled in light of Mexico's 2011 constitutional human rights amendment and the United Nation's Guiding Principles on Business and Human Rights (UN Guiding Principles), adopted by the Human Rights Council in 2011. To that aim, it initially presents a contextual framework; it then explores qualitatively the adoption of human rights’ language in the CSR strategies of the three main mining companies in Mexico, and finally, it examines their standing with respect to the UN Guiding Principles. The results reveal that human rights are included in the RSE strategies of the analysed businesses, at least at the rhetoric level; however, they do not embrace the right to a safe, clean and healthy environment as such. Moreover, we conclude that despite the finding that corporations publicly express their commitment to respect human rights, some operational weaknesses that hamper the exercise of such responsibility persist; for example, the systematic lack of human rights impact assessments per mining unit, the denial of actual and publicly-known negative episodes on the environment linked directly to their operations, and the absence of effective mechanisms to remediate adverse impacts.

Keywords: corporate social responsibility, environmental impacts, human rights, right to a safe, clean and healthy environment, mining industry

Procedia PDF Downloads 323

Authors: Faci Youcef

Abstract:

In the present work, an experimental study is carried out using the digital image correlation (DIC) technique to analyze the damage and behavior of woven composite carbon/epoxy under tensile loading. The tension mechanisms associated with failure modes of bolted joints in advanced composites are studied, as well as displacement distribution and strain distribution. The evolution value of bolt angle inclination during tensile tests was studied. In order to compare the distribution of displacements and strains along the surface, figures of image mapping are made. Several factors that are responsible for the failure of fiber-reinforced polymer composite materials are observed. It was found that strain concentrations observed in the specimens can be used to identify full-field damage onset and to monitor damage progression during loading. Moreover, there is an interaction between laminate pattern, laminate thickness, fastener size and type, surface strain concentrations, and out-of-plane displacement. Conclusions include a failure analysis associated with bolt angle inclinations and supported by microscopic visualizations of the composite specimen. The DIC results can be used to develop and accurately validate numerical models.

Keywords: Carbone, woven, damage, digital image, bolted joint, the inclination of angle

Procedia PDF Downloads 67

Authors: J. M. Hernández-Ontiveros, E. E. García-Guerrero, E. Inzunza-González, O. R. López-Bonilla

Abstract:

This paper presents the implementation of an algorithm that identifies and accounts different fish species: Catfish, Sea bream, Sawfish, Tilapia, and Totoaba. The main contribution of the method is the fusion of the characteristics of invariance to the position, rotation and scale of the Hu moments, with the proper counting of fish. The identification and counting is performed, from an image under different noise conditions. From the experimental results obtained, it is inferred the potentiality of the proposed algorithm to be applied in different scenarios of aquaculture production.

Keywords: counting fish, digital image processing, invariant moments, pattern recognition

Procedia PDF Downloads 399

Authors: M. Shaker, S. Minaei, M. H. Khoshtaghaza, A. Banakar, A. Jafari

Abstract:

In this study a system of machine vision and singulation was developed to separate paddy from rice and determine paddy husking and rice breakage percentages. The machine vision system consists of three main components including an imaging chamber, a digital camera, a computer equipped with image processing software. The singulation device consists of a kernel holding surface, a motor with vacuum fan, and a dimmer. For separation of paddy from rice (in the image), it was necessary to set a threshold. Therefore, some images of paddy and rice were sampled and the RGB values of the images were extracted using MATLAB software. Then mean and standard deviation of the data were determined. An Image processing algorithm was developed using MATLAB to determine paddy/rice separation and rice breakage and paddy husking percentages, using blue to red ratio. Tests showed that, a threshold of 0.75 is suitable for separating paddy from rice kernels. Results from the evaluation of the image processing algorithm showed that the accuracies obtained with the algorithm were 98.36% and 91.81% for paddy husking and rice breakage percentage, respectively. Analysis also showed that a suction of 45 mmHg to 50 mmHg yielding 81.3% separation efficiency is appropriate for operation of the kernel singulation system.

Keywords: breakage, computer vision, husking, rice kernel

Procedia PDF Downloads 367

Authors: S. Jagadeesh Kumar

Abstract:

Face detection and recognition is an authoritative technology for image database management, video surveillance, and human computer interface (HCI). Face recognition is a rapidly nascent method, which has been extensively discarded in forensics such as felonious identification, tenable entree, and custodial security. This paper recommends an erudite technique using curvature analysis (CA) that has less false positives incidence, operative in different light environments and confiscates the artifacts that are introduced during image acquisition by ring correction in polar coordinate (RCP) method. This technique affronts mean and median filtering technique to remove the artifacts but it works in polar coordinate during image acquisition. Investigational fallouts for face detection and recognition confirms decent recitation even in diagonal orientation and stance variation.

Keywords: curvature analysis, ring correction in polar coordinate method, face detection, face recognition, human computer interaction

Procedia PDF Downloads 276

Authors: Micheal Olaolu Arowolo, Muhammad Azam, Fei He, Mihail Popescu, Dong Xu

Abstract:

As the quantity of biological articles rises, so does the number of biological route figures. Each route figure shows gene names and relationships. Annotating pathway diagrams manually is time-consuming. Advanced image understanding models could speed up curation, but they must be more precise. There is rich information in biological pathway figures. The first step to performing image understanding of these figures is to recognize gene names automatically. Classical optical character recognition methods have been employed for gene name recognition, but they are not optimized for literature mining data. This study devised a method to recognize an image bounding box of gene name as a photo using deep Siamese neural network models to outperform the existing methods using ResNet, DenseNet and Inception architectures, the results obtained about 84% accuracy.

Keywords: biological pathway, gene identification, object detection, Siamese network

Procedia PDF Downloads 272

Authors: Abdulrahman S. Alturki, John S. Loomis

Abstract:

This paper discusses a corner detection algorithm for camera calibration. Calibration is a necessary step in many computer vision and image processing applications. Robust corner detection for an image of a checkerboard is required to determine intrinsic and extrinsic parameters. In this paper, an algorithm for fully automatic and robust X-corner detection is presented. Checkerboard corner points are automatically found in each image without user interaction or any prior information regarding the number of rows or columns. The approach represents each X-corner with a quadratic fitting function. Using the fact that the X-corners are saddle points, the coefficients in the fitting function are used to identify each corner location. The automation of this process greatly simplifies calibration. Our method is robust against noise and different camera orientations. Experimental analysis shows the accuracy of our method using actual images acquired at different camera locations and orientations.

Keywords: camera calibration, corner detector, edge detector, saddle points

Procedia PDF Downloads 399

Authors: K. V. Nabichu

Abstract:

The rationale of this research was to review how Germans perceive Uganda as a tourism destination, after German visitors arrivals to Uganda remain few compared to other destinations like Kenya. It was assumed that Uganda suffers a negative image in Germany due to negative media influence. The study findings indicate that Uganda is not a popular travel destination in Germany, there is generally lack of travel information about Uganda. Despite the respondents’ hearing about Uganda’s and her beautiful attractions, good climate and friendly people, they also think Uganda is unsafe for travel. Findings further show that Uganda is a potential travel destination for Germans due to her beautifull landscape, rich culture, wild life, primates and the Nile, however political unrest, insecurity, the fear for diseases and poor hygiene hinder Germans from travelling to Uganda. The media, internet as well as friends and relatives were the major primary sources of information on Uganda while others knew about Uganda through their school lessons and sports. Uganda is not well advertised and promoted in Germany.

Keywords: destination Uganda and Germany, image, perception, negative media influence

Procedia PDF Downloads 331

Authors: Guang-Ho Cha

Abstract:

This paper presents a context-sensitive media similarity search algorithm. One of the central problems regarding media search is the semantic gap between the low-level features computed automatically from media data and the human interpretation of them. This is because the notion of similarity is usually based on high-level abstraction but the low-level features do not sometimes reflect the human perception. Many media search algorithms have used the Minkowski metric to measure similarity between image pairs. However those functions cannot adequately capture the aspects of the characteristics of the human visual system as well as the nonlinear relationships in contextual information given by images in a collection. Our search algorithm tackles this problem by employing a similarity measure and a ranking strategy that reflect the nonlinearity of human perception and contextual information in a dataset. Similarity search in an image database based on this contextual information shows encouraging experimental results.

Keywords: context-sensitive search, image search, similarity ranking, similarity search

Procedia PDF Downloads 351

Authors: Helene Martin, Solmaz Boroomandi Barati, Jean-Charles Pinoli, Stephane Valette, Yann Gavet

Abstract:

In the present work we developed an image processing algorithm to measure water droplets characteristics during dropwise condensation on pillared surfaces. The main problem in this process is the similarity between shape and size of water droplets and the pillars. The developed method divides droplets into four main groups based on their size and applies the corresponding algorithm to segment each group. These algorithms generate binary images of droplets based on both their geometrical and intensity properties. The information related to droplets evolution during time including mean radius and drops number per unit area are then extracted from the binary images. The developed image processing algorithm is verified using manual detection and applied to two different sets of images corresponding to two kinds of pillared surfaces.

Keywords: dropwise condensation, textured surface, image processing, watershed

Procedia PDF Downloads 215

Authors: S. K. Khosrowshahi, E. Güler

Abstract:

This study investigates the reinforcement function of geosynthetics on the shear strength and strain profile of sand. Conducting a series of simple shear tests, the shearing behavior of the samples under static and cyclic loads was evaluated. Three different types of geosynthetics including geotextile and geonets were used as the reinforcement materials. An image processing analysis based on the optical flow method was performed to measure the lateral displacements and estimate the shear strains. It is shown that besides improving the shear strength, the geosynthetic reinforcement leads a remarkable reduction on the shear strains. The improved layer reduces the required thickness of the soil layer to resist against shear stresses. Consequently, the geosynthetic reinforcement can be considered as a proper approach for the sustainable designs, especially in the projects with huge amount of geotechnical applications like subgrade of the pavements, roadways, and railways.

Keywords: image processing, soil reinforcement, geosynthetics, simple shear test, shear strain profile

Procedia PDF Downloads 209