Search results for: country's image components

Authors: Ye Tian

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Soft power has replaced hard power and become one of the most attractive ways nations pursue to expand their international influence. One of the ways to improve a nation’s soft power is to commercialise the country and brand or rebrand it to the international audience, and thus attract interests or foreign investments. In this process, translation has often been regarded as merely a tool, and researches in it are either in translating literature as culture export or in how (in)accuracy of translation influences the branding campaign. This paper proposes to analyse nation branding campaign with framing theory, and thus gives an entry for translation studies to come to a central stage in today’s soft power research. To frame information or elements of a text, an event, or, as in this paper, a nation is to put them in a mental structure. This structure can be built by outsiders or by those who create the text, the event, or by citizens of the nation. To frame information like this can be regarded as a process of translation, as what translation does in its traditional meaning of ‘translating a text’ is to put a framework on the text to, deliberately or not, highlight some of the elements while hiding the others. In the discourse of nations, then, people unavoidably simplify a national image and put the nation into their imaginary framework. In this way, problems like stereotype and prejudice come into being. Meanwhile, if nations seek ways to frame or reframe themselves, they make efforts to have in control what and who they are in the eyes of international audiences, and thus make profits, economically or politically, from it. The paper takes African nations, which are usually perceived as a whole, and the United Kingdom as examples to justify passive and active framing process, and assesses both positive and negative influence framing has on nations. In conclusion, translation as framing causes problems like prejudice, and the image of a nation is not always in the hands of nation branders, but reframing the nation in a positive way has the potential to turn the tide.

Keywords: framing, nation branding, stereotype, translation

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Authors: R. A. Deshpande, P. Chandhra Sekhar, V. Sankar

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In this paper, we discussed the basic reliability evaluation techniques needed to evaluate the reliability of distribution systems which are applied in distribution system planning and operation. Basically, the reliability study can also help to predict the reliability performance of the system after quantifying the impact of adding new components to the system. The number and locations of new components needed to improve the reliability indices to certain limits are identified and studied.

Keywords: distribution system, reliability indices, urban feeder, rural feeder

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Authors: John Paul Q. Tomas, Mark Wilson L. de los Reyes, Kirsten Joyce P. Vasquez

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The most frequent type of fracture is a wrist fracture, which often makes it difficult for medical professionals to find and locate. In this study, fractures in wrist x-ray pictures were located and identified using deep learning and computer vision. The researchers used image filtering, masking, morphological operations, and data augmentation for the image preprocessing and trained the RetinaNet and Faster R-CNN models with ResNet50 backbones and Adam optimizers separately for each image filtering technique and projection. The RetinaNet model with Anisotropic Diffusion Smoothing filter trained with 50 epochs has obtained the greatest accuracy of 99.14%, precision of 100%, sensitivity/recall of 98.41%, specificity of 100%, and an IoU score of 56.44% for the Posteroanterior projection utilizing augmented data. For the Lateral projection using augmented data, the RetinaNet model with an Anisotropic Diffusion filter trained with 50 epochs has produced the highest accuracy of 98.40%, precision of 98.36%, sensitivity/recall of 98.36%, specificity of 98.43%, and an IoU score of 58.69%. When comparing the test results of the different individual projections, models, and image filtering techniques, the Anisotropic Diffusion filter trained with 50 epochs has produced the best classification and regression scores for both projections.

Keywords: Artificial Intelligence, Computer Vision, Wrist Fracture, Deep Learning

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Authors: Teja Sai Puligadda

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Satellite images in detail can serve an important role in the geographic study. Quantitative and qualitative information provided by the satellite and remote sensing images minimizes the complexity of work and time. Data/images are captured at regular intervals by satellite remote sensing systems, and the amount of data collected is often enormous, and it expands rapidly as technology develops. Interpreting remote sensing images, geographic data mining, and researching distinct vegetation types such as agricultural and forests are all part of satellite image categorization. One of the biggest challenge data scientists faces while classifying satellite images is finding the best suitable classification algorithms based on the available that could able to classify images with utmost accuracy. In order to categorize satellite images, which is difficult due to the sheer volume of data, many academics are turning to deep learning machine algorithms. As, the CNN algorithm gives high accuracy in image recognition problems and automatically detects the important features without any human supervision and the ANN algorithm stores information on the entire network (Abhishek Gupta., 2020), these two deep learning algorithms have been used for satellite image classification. This project focuses on remote sensing through Deep Neural Networks i.e., ANN and CNN with Deep Sat (SAT-4) Airborne dataset for classifying images. Thus, in this project of classifying satellite images, the algorithms ANN and CNN are implemented, evaluated & compared and the performance is analyzed through evaluation metrics such as Accuracy and Loss. Additionally, the Neural Network algorithm which gives the lowest bias and lowest variance in solving multi-class satellite image classification is analyzed.

Keywords: artificial neural network, convolutional neural network, remote sensing, accuracy, loss

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Authors: Misha Alexander, S. B. Waykar

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Visual Cryptography is a special unbreakable encryption technique that transforms the secret image into random noisy pixels. These shares are transmitted over the network and because of its noisy texture it attracts the hackers. To address this issue a Natural Visual Secret Sharing Scheme (NVSS) was introduced that uses natural shares either in digital or printed form to generate the noisy secret share. This scheme greatly reduces the transmission risk but causes distortion in the retrieved secret image through variation in settings and properties of digital devices used to capture the natural image during encryption / decryption phase. This paper proposes a new NVSS scheme that extracts the secret key from randomly selected unaltered multiple natural images. To further improve the security of the shares data hiding techniques such as Steganography and Alpha channel watermarking are proposed.

Keywords: decryption, encryption, natural visual secret sharing, natural images, noisy share, pixel swapping

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Authors: D. D. Nguyen, H. S. Park, S. W. Yang, B. Thusa, Y. M. Kim, T. H. Lee

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Currently, the design response spectrum (i.e., Nuclear Regulatory Commission - NRC 1.60 spectrum) with the peak ground acceleration (PGA) 0.3g (for Safe Shutdown Earthquake level) is specified for designing the new nuclear power plant (NPP) structures in Korea. However, the recent earthquakes in the region such as the 2016 Gyeongju and the 2017 Pohang earthquake showed that the possible PGA of ground motions can be larger than 0.3g. Therefore, there is a need to analyze the seismic performance of the existing NPP structures under these earthquakes. An NPP model, APR-1400, which is designed and built in Korea was selected for a case study. The NPP structure is numerically modeled in terms of lumped-mass stick elements using OpenSees framework. The floor acceleration and displacement of components are measured to quantify the responses of components. The numerical results show that the floor spectral accelerations are significantly amplified in the components subjected to Korean earthquakes. A comparison between floor response spectra of Korean earthquakes and the NRC design motion highlights that the seismic design level of NPP components under an earthquake should be thoroughly reconsidered. Additionally, a seismic safety assessment of the equipment and relays attached to main structures is also required.

Keywords: nuclear power plant, floor response spectra, Korean earthquake, NRC spectrum

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Authors: Abraham Terán Salcedo, Didier Samayoa Ochoa

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This work presents a numerical implementation of a method for estimating the box-counting dimension of self-avoiding curves on a planar space, fractal objects captured on digital images; this method is named fractioning estimator. Classical methods of digital image processing, such as noise filtering, contrast manipulation, and thresholding, among others, are used in order to obtain binary images that are suitable for performing the necessary computations of the fractioning estimator. A user interface is developed for performing the image processing operations and testing the fractioning estimator on different captured images of real-life fractal objects. To analyze the results, the estimations obtained through the fractioning estimator are compared to the results obtained through other methods that are already implemented on different available software for computing and estimating the box-counting dimension.

Keywords: box-counting, digital image processing, fractal dimension, numerical method

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Authors: Siqi Qiu, Yijian Zheng, Xin Guo Ming

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In many reliability and risk analysis, failures of components are supposed to be independent. However, in reality, the ignorance of failure dependencies among components may render the results of reliability and risk analysis incorrect. There are two principal ways to incorporate failure dependencies in system reliability and risk analysis: implicit and explicit methods. In the implicit method, failure dependencies can be modeled by joint probabilities, correlation values or conditional probabilities. In the explicit method, certain types of dependencies can be modeled in a fault tree as mutually independent basic events for specific component failures. In this paper, explicit and implicit methods based on BDD will be proposed to evaluate the reliability of systems considering failure dependencies. The obtained results prove the equivalence of the proposed implicit and explicit methods. It is found that the consideration of failure dependencies decreases the reliability of systems. This observation is intuitive, because more components fail due to failure dependencies. The consideration of failure dependencies helps designers to reduce the dependencies between components during the design phase to make the system more reliable.

Keywords: reliability assessment, risk assessment, failure dependencies, binary decision diagram

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Authors: Jamila Garba Audu, Peter Adamu

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This study investigates the role of forensic accounting in the fight against corruption in Nigeria for better utilization of public funds and economic growth and development of the Country. We adopted a trend analysis to show the performance of the Nigerian economy as well as the quality of institutions which government economic and political activities in the country. It is an established fact that Nigeria has performed badly since the 1960s to date in terms of institutional quality and economic development despite large amount of money obtained from the export of crude oil. It was revealed also that the fight against corruption has not been very successful in recent times because experts in the field of forensic accounting have not been utilized. With the successes recorded in dealing with fraud and embezzlement using forensic accounting, it has become imperative for the EFCC to use forensic accountants in the fight against corruption in the country. Also, there is the need to introduce very seriously, the teaching of forensic accounting in Nigerian Universities to train experts.

Keywords: corruption, economic performance, forensic accounting, Nigeria

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Authors: Ramin Rostamkhani, Thurasamy Ramayah

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One of the most important topics of today’s industrial organizations is the challenging issue of supply chain management. In this field, scientists and researchers have published numerous practical articles and models, especially in the last decade. In this research, to our best knowledge, the discussion of data modeling of supply chain management components using well-known statistical distribution functions has been considered. The world of science owns mathematics, and showing the behavior of supply chain data based on the characteristics of statistical distribution functions is innovative research that has not been published anywhere until the moment of doing this research. In an analytical process, describing different aspects of functions including probability density, cumulative distribution, reliability, and failure function can reach the suitable statistical distribution function for each of the components of the supply chain management. It can be applied to predict the behavior data of the relevant component in the future. Providing a model to adapt the best statistical distribution function in the supply chain management components will be a big revolution in the field of the behavior of the supply chain management elements in today's industrial organizations. Demonstrating the final results of the proposed model by introducing the process capability indices before and after implementing it alongside verifying the approach through the relevant assessment as an acceptable verification is a final step. The introduced approach can save the required time and cost to achieve the organizational goals. Moreover, it can increase added value in the organization.

Keywords: analyzing, process capability indices, statistical distribution functions, supply chain management components

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Authors: Ching-Yi Huang, Pi-Fen Cheng, Hui-Zhu Chen, Shi Ting Huang, Heng-Hua Wang

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This is a case of oral cancer after extensive resection and modified right lateral neck lymph node dissection followed by reconstruction with a skin flap. The nursing period lasted From September 25 to October 3, 2017, through observation, interview, physical assessment, and medical record review, the author identified the following nursing problems: acute pain, impaired oral mucous membrane, and body image change. During the nursing period, the author provided individual and overall nursing care and established mutual trust through the use of empathy. Author listened and eased the patient's physical indisposition, such as wound pain, we use medications and acupuncture massage to relieve pain. However, for oral mucosa change caused by surgery, provide continuous and complete oral care and oral exercise training to improve oral mucosal healing and restore swallowing function. In the body-image changes, guided him to express his feeling after the body-image change, and enhanced support and from the family, and encouraged him to attend head and neck cancer survivor alliance which allowed the patient to accept the altered body image and reaffirm self-worth. Hopefully, through sharing this nursing experience will help to the nursing care quality of nursing care for oral cancer patients after extensive resection and modified right lateral neck lymph node dissection followed by reconstruction with a skin flap.

Keywords: oral cancer, acute pain, impaired oral mucous membrane, body image change

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Authors: Hamza A. Al-Sewadi, Akram N. A. Aldakari

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Copyright protection and ownership proof of digital multimedia are achieved nowadays by digital watermarking techniques. A text watermarking algorithm for protecting the property rights and ownership judgment of color images is proposed in this paper. Embedding is achieved by inserting texts elements randomly into the color image as noise. The YIQ image processing model is found to be faster than other image processing methods, and hence, it is adopted for the embedding process. An optional choice of encrypting the text watermark before embedding is also suggested (in case required by some applications), where, the text can is encrypted using any enciphering technique adding more difficulty to hackers. Experiments resulted in embedding speed improvement of more than double the speed of other considered systems (such as least significant bit method, and separate color code methods), and a fairly acceptable level of peak signal to noise ratio (PSNR) with low mean square error values for watermarking purposes.

Keywords: steganography, watermarking, time complexity measurements, private keys

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Authors: David Jurado, Carlos Ávila

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Detection of early signs of breast cancer development is crucial to quickly diagnose the disease and to define adequate treatment to increase the survival probability of the patient. Computer Aided Detection systems (CADs), along with modern data techniques such as Machine Learning (ML) and Neural Networks (NN), have shown an overall improvement in digital mammography cancer diagnosis, reducing the false positive and false negative rates becoming important tools for the diagnostic evaluations performed by specialized radiologists. However, ML and NN-based algorithms rely on datasets that might bring issues to the segmentation tasks. In the present work, an automatic segmentation and detection algorithm is described. This algorithm uses image processing techniques along with the Hough transform to automatically identify microcalcifications that are highly correlated with breast cancer development in the early stages. Along with image processing, automatic segmentation of high-contrast objects is done using edge extraction and circle Hough transform. This provides the geometrical features needed for an automatic mask design which extracts statistical features of the regions of interest. The results shown in this study prove the potential of this tool for further diagnostics and classification of mammographic images due to the low sensitivity to noisy images and low contrast mammographies.

Keywords: breast cancer, segmentation, X-ray imaging, hough transform, image analysis

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Authors: Syeda Shawana Mahasan, Muhammad Farooq Akhtar

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The objective of this study is to analyze the influence of the green marketing mix strategy and corporate social responsibility (CSR) on the performance of an organization, taking into account the mediating effect of corporate image. The impact of frugal innovation and corporate activism is being examined. The data was gathered from executives at various levels of management, including top, middle, and lower-level managers, from a total of 550 manufacturing enterprises of different sizes, ranging from small to medium to large. The collected replies are processed and analyzed using SMART PLS version 4.0.0.0. The application of PLS-SEM demonstrates that the green marketing mix strategy and corporate social responsibility have a significant impact on organizational performance. Therefore, it is imperative for organizations to effectively adopt environmentally sustainable and socially conscious methods within their operations. The results indicate that the corporate image has a key role in mediating the relationship between the green marketing mix strategy, corporate social responsibility, and organizational performance. This demonstrates the imperative for organizations to actively enhance their favorable reputation among stakeholders. The combination of frugal innovation and corporate activism enhances the connection between corporate image and organizational performance. The current study assists managers in recognizing the significance of these particular constructs in maintaining the long-term performance of the organization.

Keywords: green marketing mix strategy, CSR, corporate image, organizational performance, frugal innovation, corporate activism

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Authors: Kumar Kanudkuri, A. Sandhya

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Typically, in a MRI clinical setting, there are several protocols run, each indicated for a specific anatomy and disease condition. However, these protocols or parameters within them can change over time due to changes to the recommendations by the physician groups or updates in the software or by the availability of new technologies. Most of the time, the changes are performed by the MRI technologist to account for either time, coverage, physiological, or Specific Absorbtion Rate (SAR ) reasons. However, giving properly guidelines to MRI technologist is important so that they do not change the parameters that negatively impact the image quality. Typically a standard American College of Radiology (ACR) MRI phantom is used for Quality Control (QC) in order to guarantee that the primary objectives of MRI are met. The visual evaluation of quality depends on the operator/reviewer and might change amongst operators as well as for the same operator at various times. Therefore, overcoming these constraints is essential for a more impartial evaluation of quality. This makes quantitative estimation of image quality (IQ) metrics for MRI quality control is very important. So in order to solve this problem, we proposed that there is a need for a robust, open-source, and automated MRI image control tool. The Designed and developed an automatic analysis tool for measuring MRI image quality (IQ) metrics like Signal to Noise Ratio (SNR), Signal to Noise Ratio Uniformity (SNRU), Visual Information Fidelity (VIF), Feature Similarity (FSIM), Gray level co-occurrence matrix (GLCM), slice thickness accuracy, slice position accuracy, High contrast spatial resolution) provided good accuracy assessment. A standardized quality report has generated that incorporates metrics that impact diagnostic quality.

Keywords: ACR MRI phantom, MRI image quality metrics, SNRU, VIF, FSIM, GLCM, slice thickness accuracy, slice position accuracy

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Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen

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Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.

Keywords: convolutional neural network, feature representation, image processing, machine modelling

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Authors: Sarah Abdourraziq, R. El Bachtiri

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Renewable energies have a major importance of Morocco's new energy strategy. The geographical location of the Kingdom promotes the development of the use of solar energy. The use of this energy reduces the dependence on imports of primary energy, meets the growing demand for water and electricity in remote areas encourages the deployment of a local industry in the renewable energy sector and Minimize carbon emissions. Indeed, given the importance of the radiation intensity received and the duration of the sunshine, the country can cover some of its solar energy needs. The use of solar energy to pump water is one of the most promising application, this technique represents a solution wherever the grid does not exist. In this paper, we will present a presentation of photovoltaic pumping system components, and the important solar pumping projects installed in Morocco to supply water from remote area.

Keywords: PV pumping system, Morocco, PV panel, renewable energy

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Authors: Thanatip Lerttanaporn, Tuanjai Somboonwiwat, Charoenchai Khompatraporn

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The automotive parts industry is one of the vital sectors in Thai economy and now is facing a greater competition from ASEAN Economic Community (AEC). This article identifies important factors that impact the competitiveness of Thai automotive parts industry. There are eight groups of factors with a total of 58 factors. Due to a variety of factors, the Exploratory Factor Analysis and Principle Component Analysis have been applied to classify factors into groups or principle components. The results show that there are 15 groups and four of them are critical, covering 80% of important value. These four critical groups are then used to formulate strategies to improve the competitiveness of the Thai automotive parts industry.

Keywords: factor analysis, Thai automotive parts, principle components, exploratory factor, ASEAN economic community

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Authors: Ajitesh Pal, Arpan Datta Roy, H. K. Pratihari

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The different illegal firearms crudely made by skilled gunsmith from scrap materials are popularly known as country made firearms. Such firearms along with improvised ammunition are clandestinely marketed at the cheaper price without any license to the extremist group, criminal, poachers and firearm lovers. As per National Crime Records Bureau (NCRB), MHA, Govt of India about 80% firearm cases are committed by country made/improvised firearms. The ballistic division of the laboratory has examined a good number of cases. The analysis of firearm cases received for forensic examination revealed that 7.65mm calibre pistols mostly improvised firearm are commonly used in firearm related crime cases. In the present communication, physical parameters and other characteristics features of some 7.65mm calibre pistols have been discussed in detail. The detailed study on country made (CM) firearm will help to prepare a database related to type of material used, origin of the raw material and tools used for inscription. The study also includes to establish the chemistry of propellants & head stamp pattern. The database will be helpful to the firearm examiners, researchers, students pursuing study on forensic science as reference material.

Keywords: improvised pistol, stringent gun law, working mechanism, parameters, database

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Authors: Parisa Mansour

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The coronavirus disease 2019 (COVID-19) was discovered and rapidly spread to various countries around the world since the end of 2019. Computed tomography (CT) images have been used as an important alternative to the time-consuming RT. PCR test. However, manual segmentation of CT images alone is a major challenge as the number of suspected cases increases. Thus, accurate and automatic segmentation of COVID-19 infections is urgently needed. Because the imaging features of the COVID-19 infection are different and similar to the background, existing medical image segmentation methods cannot achieve satisfactory performance. In this work, we try to build a deep convolutional neural network adapted for the segmentation of chest CT images with COVID-19 infections. First, we maintain a large and novel chest CT image database containing 165,667 annotated chest CT images from 861 patients with confirmed COVID-19. Inspired by the observation that the boundary of an infected lung can be improved by global intensity adjustment, we introduce a feature variable block into the proposed deep CNN, which adjusts the global features of features to segment the COVID-19 infection. The proposed PV array can effectively and adaptively improve the performance of functions in different cases. We combine features of different scales by proposing a progressive atrocious space pyramid fusion scheme to deal with advanced infection regions with various aspects and shapes. We conducted experiments on data collected in China and Germany and showed that the proposed deep CNN can effectively produce impressive performance.

Keywords: chest, COVID-19, chest Image, coronavirus, CT image, chest CT

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Authors: Mihai Liviu Despa

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The paper tackles the topic of determining the cost of innovation in software development projects. Innovation can be achieved either in a planned or unplanned manner. The paper approaches the scenarios were innovation is planned for. As a starting point an innovative software development project is analyzed. The project is depicted step by step as it was implemented, from inception to delivery. Costs that are proprietary to innovation in software development are isolated based on the author’s personal experience in managing the above mentioned project. Innovation costs components identified by the author are then validated using open discussions with software development professionals and projects managers on LinkedIn groups. In order to receive relevant feedback only groups that focus on software development and innovation management are targeted. Additional innovation cost components suggested by software development professionals and projects managers are also considered. Based on the identified cost components an indicator is built. The indicator is meant to formalize the process of determining the cost of innovation in a software development project. The indicator aggregates all the innovation cost components that are identified in the research process. The process of calculating each cost component is also described. Conclusions are formulated and new related research topics are submitted for debate.

Keywords: innovation cost, IT project management, software development, innovation management

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Authors: Perihan Hazel Kaya, Mustafa Göktuğ Kaya

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Turkey has been a busy destination for immigration and it will always be as it is the geographical and cultural exit door of the East and the entrance door of the West. Among these immigrations, we can see the victims of human trafficking, human smuggling, refugees and those who came here to work and live. Human smuggling, which is one of the movements of illegal immigration, is the specific subject of this work. The fact that our country lies on the transportation destinations between the continents of Asia, Europe and Africa, the crime of human smuggling is highly committed in our country. The aim of the victims of human smuggling is to go to a more developed country to have higher standards of living, to get a better job and to escape from the economic and social instability of their countries. The human smuggling, which has gathered pace due to the improvements in communication and transportation, is not a regional issue and has become one of the most important problems for almost all countries. Accordingly, the reasons, methods and extent of human smuggling will be dealt firstly. Later, it will be studied why Turkey is preffered in human smuggling. Finally, statistical data will be given to show how much human smuggling has gone far in Turkey and the study will be finished with that what is being done and what can be done to prevent it.

Keywords: human smuggling, immigration, immigrator, human trafficking, Turkey

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Authors: David Downey

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With the introduction of additive manufacturing (3D printing) to produce titanium (Ti6Al4V) components in the medical/aerospace and automotive industries, intricate geometries can be produced with virtually complete design freedom. However, the consideration of microstructural anisotropy resulting from the additive manufacturing process becomes necessary due to this design flexibility and the need to print a geometric shape that can consist of numerous angles, radii, and swept surfaces. A femoral knee implant serves as an example of a 3D-printed near-net-shaped product. The mechanical properties of the printed components, and consequently, their machinability, are affected by microstructural anisotropy. Currently, finish-machining operations performed on titanium printed parts using selective laser melting (SLM) utilize the same cutting tools employed for processing wrought titanium components. Cutting forces for components manufactured through SLM can be up to 70% higher than those for their wrought counterparts made of Ti6Al4V. Moreover, temperatures at the cutting interface of 3D printed material can surpass those of wrought titanium, leading to significant tool wear. Although the criteria for tool wear may be similar for both 3D printed and wrought materials, the rate of wear during the machining process may differ. The impact of these issues on the choice of cutting tool material and tool lifetimes will be discussed.

Keywords: additive manufacturing, build orientation, microstructural anisotropy, printed titanium Ti6Al4V, tool wear

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Authors: A. J. S. P. Nileema, S. Kulatunga , S. H. Palihawadana

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Computer aided detection (CAD) system was developed for the diagnosis of pulmonary tuberculosis using digital chest X-rays with MATLAB image processing techniques using a statistical approach. The study comprised of 200 digital chest radiographs collected from the National Hospital for Respiratory Diseases - Welisara, Sri Lanka. Pre-processing was done to remove identification details. Lung fields were segmented and then divided into four quadrants; right upper quadrant, left upper quadrant, right lower quadrant, and left lower quadrant using the image processing techniques in MATLAB. Contrast, correlation, homogeneity, energy, entropy, and maximum probability texture features were extracted using the gray level co-occurrence matrix method. Descriptive statistics and normal distribution analysis were performed using SPSS. Depending on the radiologists’ interpretation, chest radiographs were classified manually into PTB - positive (PTBP) and PTB - negative (PTBN) classes. Features with standard normal distribution were analyzed using an independent sample T-test for PTBP and PTBN chest radiographs. Among the six features tested, contrast, correlation, energy, entropy, and maximum probability features showed a statistically significant difference between the two classes at 95% confidence interval; therefore, could be used in the classification of chest radiograph for PTB diagnosis. With the resulting value ranges of the five texture features with normal distribution, a classification algorithm was then defined to recognize and classify the quadrant images; if the texture feature values of the quadrant image being tested falls within the defined region, it will be identified as a PTBP – abnormal quadrant and will be labeled as ‘Abnormal’ in red color with its border being highlighted in red color whereas if the texture feature values of the quadrant image being tested falls outside of the defined value range, it will be identified as PTBN–normal and labeled as ‘Normal’ in blue color but there will be no changes to the image outline. The developed classification algorithm has shown a high sensitivity of 92% which makes it an efficient CAD system and with a modest specificity of 70%.

Keywords: chest radiographs, computer aided detection, image processing, pulmonary tuberculosis

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Authors: Odoh Ben Uruchi

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Access to Justice implies access to social and distributive Justice. Access to social justice in Nigeria remains an illusion where cases last in courts for unduly long period of time, as is currently the situation in the country. As the popular saying goes– justice delayed is justice denied. It is, however, important to underscore the point that these perspectives are not necessarily disconnected since the extent to which one can have distributive justice in any system is largely determined by the level and effectiveness of social justice in the country. Generally, Alternative Dispute Resolution (ADR) Processes are increasingly being accepted in Nigeria as appropriate mechanisms for resolving disputes. While some jurisdictions have institutionalized ADR through the concept of a Multidoor Courthouse, many other are at different stages of doing same. With these developments, it is obvious that stakeholders in the administration of justice in Nigeria, can no longer be indifferent about understanding and fully mainstreaming ADR into their various activities and professional practice. Any framework for promoting social justice in Nigeria should therefore of necessity include provision of avenues for use of ADR in the protection and enforcement of citizen’s rights. The constitutional and other legal provisions that guarantee various rights of citizens cannot of itself ensure the enjoyment of the rights in the absence of an effective framework for dispute resolution. Excessive reliance on litigation and other adversarial approaches will also fail to ensure a sound regime of social justice. There should be structured mainstreaming of alternative dispute resolution mechanisms in justice delivery if the society must provide and guarantee social justice to the citizens. This paper seeks to address some of the fundamental issues affecting the perception, knowledge and skills of ADR in the provision of social justice. In doing this, the paper proposes to unlock the full enormous potentials of Alternative Dispute Resolution (ADR) in promoting access to justice in Nigeria.

Keywords: aspects, dimensions, alternative dispute resolution, social justice

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Authors: N. Massoum, A. Guen. Bouazza, B. Bouazza, A. El Ouchdi

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The progress of industry integrated circuits in recent years has been pushed by continuous miniaturization of transistors. With the reduction of dimensions of components at 0.1 micron and below, new physical effects come into play as the standard simulators of two dimensions (2D) do not consider. In fact the third dimension comes into play because the transverse and longitudinal dimensions of the components are of the same order of magnitude. To describe the operation of such components with greater fidelity, we must refine simulation tools and adapted to take into account these phenomena. After an analytical study of the static characteristics of the component, according to the different operating modes, a numerical simulation is performed of field-effect transistor with submicron gate MESFET GaInP. The influence of the dimensions of the gate length is studied. The results are used to determine the optimal geometric and physical parameters of the component for their specific applications and uses.

Keywords: Monte Carlo simulation, transient electron transport, MESFET device, GaInP

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Authors: Yijie Wang, Hanwei Cheng

Abstract:

Under the Chinese educational context, the materials for patriotic education typically take the form of grand narratives. However, in post-modern times the younger members of society tend to welcome elements of more micro and personal nature. It is therefore important to explore how patriotism can be integrated into an ‘everyday’, private narrative that holds more attraction for the young. Based on semi-structured interviews of eight Chinese graduate students, this research examines how Chinese young people draw materials to establish national identity and develop love for the country from everyday-life details, as well as how they perceive, interpret and articulate their patriotism through private narratives. And implications for patriotic education are proposed accordingly. Several conclusions are drawn from the pre-interviews. Firstly, sensory experiences that remind people of their country—such as the taste of Chinese delicacies and the sound of a traditional instrument—are a major source of patriotic feelings. Secondly, the love for the country often stems from and is continued to be mediated by the emotional attachment with other people, typically significant others, and patriotism is articulated (or acknowledged) by the young as a kind of ‘sentiment’ rather than ‘faith’ or ‘belief’. Thirdly, for young people who are currently studying abroad, their birth country represents a kind of familiar, well-accustomed life or lifestyle, and any nostalgic realization of it leads to increased national belonging and sense of identity. Fourthly, the awareness of the country’s transformations—positive ones and neutral ones alike—triggers young people affections towards the country, and even negative transformations may result in promoted sense of self-involvement and therefore consolidate national identity. Implications for patriotic education can be drawn accordingly, and although the research is conducted under the Chinese context, it will hopefully contribute to the understanding of relevant fields.

Keywords: national identity, patriotic education, private narrative, young people

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Authors: Mohammad Esmaeilpour

Abstract:

One of the important open problems in the field of medical image processing is detection and quantification of small changes. In this poster, we try to investigate that, how the algebraic decomposition techniques can be used for semiautomatically detecting and quantifying subtle changes in Magnetic Resonance (MR) neuroimaging volumes. We mostly focus on the low-rank values of the matrices achieved from decomposing MR image pairs during a period of time. Besides, a skillful neuroradiologist will help the algorithm to distinguish between noises and small changes.

Keywords: magnetic resonance neuroimaging, subtle change detection and quantification, algebraic decomposition, basis functions

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Authors: Mohammad A. U. Khan, Tariq M. Khan, Yinan Kong

Abstract:

Fingerprint image enhancement is one of the most important step in an automatic fingerprint identification recognition (AFIS) system which directly affects the overall efficiency of AFIS. The conventional fingerprint enhancement like Gabor and Anisotropic filters do fill the gaps in ridge lines but they fail to tackle scar lines. To deal with this problem we are proposing a method for enhancing the ridges and valleys with scar so that true minutia points can be extracted with accuracy. Our results have shown an improved performance in terms of enhancement.

Keywords: fingerprint image enhancement, removing noise, coherence, enhanced diffusion

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Authors: Gak-Gyu Kim, Won Il Jung

Abstract:

According to a remarkable development of science and technology, function and role of the system of engineering fields has recently been diversified. The system has become increasingly more complex and precise, and thus, system designers intended to maximize reliability concentrate more effort at the design stage. This study deals with the reliability redundancy optimization problem (RROP) for k-out-of-n: G system configuration with cold standby and warm standby components. This paper further intends to present the optimal mathematical model through which the following three elements of (i) multiple components choices, (ii) redundant components quantity and (iii) the choice of redundancy strategies may be combined in order to maximize the reliability of the system. Therefore, we focus on the following three issues. First, we consider RROP that there exists warm standby state as well as cold standby state of the component. Second, as eliminating an approximation approach of the previous RROP studies, we construct a precise model for system reliability. Third, given transition time when the state of components changes, we present not simply a workable solution but the advanced method. For the wide applicability of RROPs, moreover, we use absorbing continuous time Markov chain and matrix analytic methods in the suggested mathematical model.

Keywords: RROP, matrix analytic methods, k-out-of-n: G system, MTTF, absorbing continuous time Markov Chain

Procedia PDF Downloads 254