Search results for: Segmented corm explant

Authors: Nicanor Garcia Alvarez, Belarmino Adenso-Diaz, Laura Calzada Infante

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In recent years, researchers have shown an interest in modelling maritime traffic as a complex network. In this paper, we propose a bipartite weighted network to model maritime traffic and detect port maritime communities. The bipartite weighted network considers two different types of nodes. The first one represents Spanish ports, while the second one represents the countries with which there is major import/export activity. The flow among both types of nodes is modeled by weighting the volume of product transported. To illustrate the model, the data is segmented by each type of traffic. This will allow fine tuning and the creation of communities for each type of traffic and therefore finding similar ports for a specific type of traffic, which will provide decision-makers with tools to search for alliances or identify their competitors. The traffic with the greatest impact on the Spanish gross domestic product is selected, and the evolution of the communities formed by the most important ports and their differences between 2019 and 2009 will be analyzed. Finally, the set of communities formed by the ports of the Spanish port system will be inspected to determine global similarities between them, analyzing the sum of the membership of the different ports in communities formed for each type of traffic in particular.

Keywords: bipartite networks, competition, infomap, maritime traffic, port communities

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Authors: Halima Albalushi, Mohadese Boroojerdi, Murtadha Alkhabori

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Introduction: Maintenance of stem cell properties during culture necessitates the recreation of the natural cell niche. Studies reported the promising outcome of mesenchymal stem cells (MSC) properties maintenance after using extracellular matrix such as CELLstart™, which is the recommended coating material for stem cells cultured in serum-free and xeno-free conditions. Laminin-521 is known as a crucial adhesion protein, which is found in natural stem cell niche, and plays an important role in facilitating the maintenance of self-renewal, pluripotency, standard morphology, and karyotype of human pluripotent stem cells (PSCs). The aim of this study is to investigate the effects of Laminin-521 on human umbilical cord-derived mesenchymal stem cells (UC-MSC) characteristics as a step toward clinical application. Methods: Human MSC were isolated from the umbilical cord via the explant method. Umbilical cord-derived-MSC were cultured in serum-free and xeno-free conditions in the presence of Laminin-521 for six passages. Cultured cells were evaluated by morphology and expansion index for each passage. Phenotypic characterization of UC-MSCs cultured on Laminin-521 was evaluated by assessment of cell surface markers. Results: Umbilical cord derived-MSCs formed small colonies and expanded as a homogeneous monolayer when cultured on Laminin-521. Umbilical cord derived-MSCs reached confluence after 4 days in culture. No statistically significant difference was detected in all passages when comparing the expansion index of UC-MSCs cultured on LN-521 and CELLstart™. Phenotypic characterization of UC-MSCs cultured on LN-521 using flow cytometry revealed positive expression of CD73, CD90, CD105 and negative expression of CD34, CD45, CD19, CD14 and HLA-DR.Conclusion: Laminin-521 is comparable to CELLstart™ in supporting UC-MSCs expansion and maintaining their characteristics during culture in xeno-free and serum-free culture conditions.

Keywords: mesenchymal stem cells, culture, laminin-521, xeno-free serum-free

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Authors: Inayat Ur Rahman Arshad

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Stevia rebaudiana B. is a shrubby perennial herb of Asteraceae family that possesses the unique ability of accumulative non caloric sweet Steviol Glycosides (SGs). The purpose of the study is to optimize sugar concentration, pH level and inoculum size for inducing the callus with optimum growth and efficient antibacterial potential. Three different experiments were conducted in which Callus explant from three-months-old already established callus of Stevia reabudiana of four different sizes were inoculated on Murashige and Skoog (MS) basal medium supplemented with five different sucrose concentration and pH adjusted at four different levels. Maximum callus induction 100, 87.5 and 85.33% was resulted in the medium supplemented with 30g/l sucrose, pH maintained at 5.5 and inoculated with 1.25g inoculum respectively. Similarly, the highest fresh weight 65.00, 75.50 and 50.53g/l were noted in medium fortified with 40g/l sucrose, inoculated 1.25g inoculum and 6.0 pH level respectively. However, the callus developed in medium containing 50g/l sucrose found highly antibacterial potent with 27.3 and 26.5mm inhibition zone against P. vulgaris and B. subtilize respectively. Similarly, the callus grown on medium inoculated with 1.00g inoculum resulted in maximum antibacterial potential against S. aureus and P. vulgaris with 25 and 23.72mm inhibition zones respectively. However, in the case of pH levels the medium maintained at 6.5pH showed maximum antibacterial activity against P. vulgaris, B.subtilis and E.coli with 27.9, 25 and 23.72mm respectively. The ethyl acetate extract of Stevia callus and leaves did not show antibacterial potential against Xanthomonas campestris and Clavebactor michiganensis. In the entire experiment the standard antibacterial agent Streptomycin showed the highest inhibition zones from the rest of the callus extract, however the pure DMSO (Dimethyl Sulfoxide) caused no inhibitory zone against any bacteria. From these findings it is concluded that among various levels sucrose at the rate of 40g L-1, pH 6.0 and inoculums 0.75g was found best for most of the growth and quality attributes including fresh weight, dry weight and antibacterial activities and therefore can be recommended for callus proliferation and antibacterial potential of Stevia rebaudiana

Keywords: Steviol Glycosides, Skoog, Murashige, Clavebactor michiganensis

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Authors: Inayat Ur Rahman Arshad

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Background: Stevia rebaudiana B. is a shrubby perennial herb of Asteraceae family that possesses the unique ability of accumulative non-caloric sweet steviol glycosides (SGs). Purpose: The purpose of the study is to optimize sugar concentration, pH level, and inoculum size for inducing the callus with optimum growth and efficient antibacterial potential. Method: Three different experiments were conducted in which Callus explant from three-months-old already established callus of Stevia reabudiana of four different sizes was inoculated on Murashige and Skoog (MS) basal medium supplemented with five different sucrose concentration and pH adjusted at four different levels. Results: Maximum callus induction 100, 87.5, and 85.33% resulted in the medium supplemented with 30 g/l sucrose, pH maintained at 5.5, and inoculated with 1.25g inoculum, respectively. Similarly, the highest fresh weights 65.00, 75.50, and 50.53 g/l were noted in a medium fortified with 40 g/l sucrose, inoculated 1.25g inoculum, and 6.0 pH level, respectively. However, the callus developed in a medium containing 50 g/l sucrose was found to be highly antibacterial potent with 27.3 and 26.5 mm inhibition zone against P. vulgaris and B. subtilis, respectively. Similarly, the callus grown on a medium inoculated with 1.00 g inoculum resulted in maximum antibacterial potential against S. aureus and P. vulgaris with 25 and 23.72 mm inhibition zone, respectively. However, in the case of pH levels, the medium maintained at 6.5 pH showed maximum antibacterial activity against P. vulgaris, B.subtilis, and E.coli with 27.9, 25, and 23.72 mm, respectively. The ethyl acetate extract of Stevia callus and leaves did not show antibacterial potential against Xanthomonas campestris and Clavebactor michiganensis. In the entire experiment, the standard antibacterial agent Streptomycin showed the highest inhibition zones among the rest of the callus extract; however, the pure dimethyl sulfoxide (DMSO) caused no inhibitory zone against any bacteria. Conclusion: From these findings, it is concluded that among various levels, sucrose @ 40 g L⁻¹, pH 6.0, and inoculums at 0.75 g were found best for most of the growth and quality attributes, including fresh weight, dry weight, and antibacterial activities and therefore can be recommended for callus proliferation and antibacterial potential of Stevia rebaudiana.

Keywords: Stevia rebaudiana, Steviol Glycosides, callus, Xanthomonas campestris

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Authors: Rita Magdalena, N. K. Caecar Pratiwi, Yunendah Nur Fuadah, Sofia Saidah, Bima Sakti

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Vessel segmentation of retinal fundus is important for biomedical sciences in diagnosing ailments related to the eye. Segmentation can simplify medical experts in diagnosing retinal fundus image state. Therefore, in this study, we designed a software using MATLAB which enables the segmentation of the retinal blood vessels on retinal fundus images. There are two main steps in the process of segmentation. The first step is image preprocessing that aims to improve the quality of the image to be optimum segmented. The second step is the image segmentation in order to perform the extraction process to retrieve the retina’s blood vessel from the eye fundus image. The image segmentation methods that will be analyzed in this study are Morphology Operation, Discrete Wavelet Transform and combination of both. The amount of data that used in this project is 40 for the retinal image and 40 for manually segmentation image. After doing some testing scenarios, the average accuracy for Morphology Operation method is 88.46 % while for Discrete Wavelet Transform is 89.28 %. By combining the two methods mentioned in later, the average accuracy was increased to 89.53 %. The result of this study is an image processing system that can segment the blood vessels in retinal fundus with high accuracy and low computation time.

Keywords: discrete wavelet transform, fundus retina, morphology operation, segmentation, vessel

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Authors: Zeynep Ozkan, Cigdem Serra Uzunpinar

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Citizenship is a legal bond that binds a person to a certain state. How constitutions define ‘the citizen’ and how they regulate the elements of citizenship have great importance in terms of individuals’ duties before the state as well as the rights they own. Especially in multi-segmented societies that contain foreign elements, it becomes necessary to examinate the institution of naturalization in terms of individuals’ duty of constitutional citizenship. The meaning of citizenship in Turkey has transformed due to the changes in practices of naturalization, in parallel to receiving huge amount of immagrants with the recent Syrian Crisis, the change in the governmental system and facing economic crisis. This transformation took place in the way of a diversion from the states’ initial motive of building the bond of citizenship with the aim of founding/sustaining political unity. Hence, rising of the economic and political motives in naturalization practices are in question, instead of objective and subjective criterias, that are traditionally used on defining the notion of nation. In this study, firstly the regime of citizenship and the legal regime of aliens in Turkish legislation will be given place. Then, the transformation, that the notion of constitutional citizenship underwent, will be studied, especially on the basis of governmental practices of naturalization. The assessment will be made in the context of legal institutions brought with the new governmental system as a result of recent constitutional amendment.

Keywords: constitutional citizenship, naturalization, naturalization practices in Turkish legal system, transformation of the notion of constitutional citizenship

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Authors: Regine R. Villanueva

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The study looks into how a cultural industry such as Tesoro’s Philippine Handicrafts underwent the brand revitalization process throughout its 70 years of existence in the Philippine market. This study uses a historical approach which analyzes the changes in product development and promotional strategies. Similarly, its brand identity was determined as well in terms of its internal processes and archival data such as history, mission – vision, customer relations, products, and promotions. The product life cycle model and the brand identity planning model were used as theoretical framework for the study. The life cycle was used in historically tracing the company’s developments and changes in terms of its branding, more specifically the products, promotions, and identity. Interviews were conducted among informants who included the CEO and the heads of each department in the business. The researcher also utilized textual analysis to have an in-depth understanding of Tesoro’s’ brand identity portrayal through its advertisements. The results showed how the company has undergone a progressive and innovative transition in its life cycle. With the changing markets and increased competition, the brand started active promotions and engaged in product development. In terms of identity, they are branded as pioneers of the handicraft industry in the Philippines. They started their brand revitalization to be able to imbibe this identity to their consumers through advertisement communication and identifying their segmented markets.

Keywords: cultural industry, handicrafts, case study, philippines

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Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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The phase of segmentation is an important step in the processing and interpretation of medical images. In this paper, we focus on the segmentation of liver and spleen from the abdomen computed tomography (CT) images. The importance of our study comes from the fact that the segmentation of ROI from CT images is usually a difficult task. This difficulty is the gray’s level of which is similar to the other organ also the ROI are connected to the ribs, heart, kidneys, etc. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to remove the surrounding and connected organs and tissues by applying morphological filters. This first step makes the extraction of interest regions easier. The second step consists of improving the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce these deficiencies by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts.

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

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Authors: Rohit Semwal, Shivam Arora, Saurav, Sangita Roy

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This work proposes a supervised framework with deep convolutional neural networks (CNNs) for vision-based sign language recognition of static gestures. Our approach addresses the acquisition and segmentation of correct inputs for the CNN-based classifier. Microsoft Kinect™ sensor, despite complex environmental conditions, can track hands efficiently. Skin Colour based segmentation is applied on cropped images of hands in different poses, used to depict different sign language gestures. The segmented hand images are used as an input for our classifier. The CNN classifier proposed in the paper is able to classify the input images with a high degree of accuracy. The system was trained and tested on 39 static sign language gestures, including 26 letters of the alphabet and 13 commonly used words. This paper includes a problem definition for building the proposed system, which acts as a sign language translator between deaf/mute and the rest of the society. It is then followed by a focus on reviewing existing knowledge in the area and work done by other researchers. It also describes the working principles behind different components of CNNs in brief. The architecture and system design specifications of the proposed system are discussed in the subsequent sections of the paper to give the reader a clear picture of the system in terms of the capability required. The design then gives the top-level details of how the proposed system meets the requirements.

Keywords: sign language, CNN, HCI, segmentation

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Authors: Jayoung Cho

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Poverty has become a social problem in South Korea, given that seven out of ten elderly experience multidimensional poverty. As quality of life is a major social welfare measure of a society, verifying the major factors affecting the quality of life among the elderly in poverty can be used as baseline data for the promotion of welfare. This study aims to investigate the longitudinal relationships between food insecurity and quality of life among the elderly in poverty. In this study, panel regression analysis using 5-year longitudinal panel data were derived from Korea Welfare Panel Study (KWPS, 2011-2015) were used to identify the research question. A total of 1,327 elderly people aged 65 or older with less than 60% of median income was analyzed. The main results of the study are as follows; first, the level of quality of life of the poor elderly was on average of 5, and repeated the increase and decrease over time. Second, food insecurity and quality of life of the elderly in poverty had a longitudinal causal relationship. Furthermore, the statistical significance of food insecurity was the highest despite controlling for major variables affecting the quality of life among the poor elderly. Therefore, political and practical approaches are strongly suggested and considered regarding the food insecurity for the quality of life among the elderly in poverty. In practical intervention, it is necessary to pay attention to food insecurity when assessing the poor elderly. Also, there is a need to build a new delivery system that incorporates segmented health and nutrition-related services. This study has an academic significance in that it brought out the issue of food insecurity of the poor elderly and confirmed the longitudinal relationship between food insecurity and quality of life.

Keywords: food insecurity, longitudinal panel analysis, poor elderly, quality of life

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Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat

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Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.

Keywords: feature extraction, feature selection, image annotation, classification

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Authors: Hatim Laalej, Salvador Sumohano-Verdeja, Thomas McLeay

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Monitoring of tool wear in milling operations is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Although there are numerous statistical models and artificial intelligence techniques available for monitoring the wear of cutting tools, these techniques cannot pin point which cutting edge of the tool, or which insert in the case of indexable tooling, is worn or broken. Currently, the task of monitoring the wear on the tool cutting edges is carried out by the operator who performs a manual inspection, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from lost productivity. The present study is concerned with the development of a flute tracking system to segment signals related to each physical flute of a cutter with three flutes used in an end milling operation. The purpose of the system is to monitor the cutting condition for individual flutes separately in order to determine their progressive wear rates and to predict imminent tool failure. The results of this study clearly show that signals associated with each flute can be effectively segmented using the proposed flute tracking system. Furthermore, the results illustrate that by segmenting the sensor signal by flutes it is possible to investigate the wear in each physical cutting edge of the cutting tool. These findings are significant in that they facilitate the online condition monitoring of a cutting tool for each specific flute without the need for operators/engineers to perform manual inspections of the tool.

Keywords: machining, milling operation, tool condition monitoring, tool wear prediction

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Authors: Felix Ehimare Enegho

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The issue of the Christian mission among various people in our world has become a subject of discussion for quite a while now considering the many challenges faced by people of different religions. The understanding of who we are and how we choose to live our life as a people is quite imperative in many societies. The Christian Church down through the ages attempted to define itself so as to become relevant in human society. In Africa, the question of identity and self-realization is quite imperative if Africans are to define themselves and place themselves in the proper perspective as Christians. With the high level of insecurity bedevilling the world and especially Nigerian society, there is the need for Christians in Nigeria to see themselves as one body belonging to the same family. It is however disheartening that for several years now, there is a high level of disunity, lack of trust, disharmony, and vices of all kinds even among Christians who are often too quick to segment themselves into denominations thereby making themselves weak, segmented ad powerless in the midst of great oppositions, as if the Christian church in Nigeria is a divided house. The significance of this paper is to explore the areas of conflict among Christians in Nigeria with a view to finding possible solutions that would lead to the integral formation and in the long run a common identity and invariably self-realization. This paper utilized the socio-historical method of research. Among the major findings in the work is the fact that it is only people that can truly be responsible and held accountable for how they define their identity and self-realization. This entails that Christianity’s identity and self-realization in Nigeria will not only lead to a better and more defined form of Christianity but would ultimately assist in the integral development of Christian mission in Nigeria, a kind of development that would lead to a better Nigerian society.

Keywords: contemporary, Christian, mission, Nigeria, identity, self-realization

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Authors: Christos Theoharatos, Dimitris Tsourounis, Spiros Oikonomou, Andreas Makedonas

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This paper focuses on the problem of visually inspecting and recognizing the road conditions in front of moving vehicles, targeting automotive scenarios. The goal of road inspection is to identify whether the road is slippery or not, as well as to detect possible anomalies on the road surface like potholes or body bumps/humps. Our work is based on an artificial intelligence methodology for real-time monitoring of road conditions in autonomous driving scenarios, using state-of-the-art deep convolutional neural network (CNN) techniques. Initially, the road and ego lane are segmented within the field of view of the camera that is integrated into the front part of the vehicle. A novel classification CNN is utilized to identify among plain and slippery road textures (e.g., wet, snow, etc.). Simultaneously, a robust detection CNN identifies severe surface anomalies within the ego lane, such as potholes and speed bumps/humps, within a distance of 5 to 25 meters. The overall methodology is illustrated under the scope of an integrated application (or system), which can be integrated into complete Advanced Driver-Assistance Systems (ADAS) systems that provide a full range of functionalities. The outcome of the proposed techniques present state-of-the-art detection and classification results and real-time performance running on AI accelerator devices like Intel’s Myriad 2/X Vision Processing Unit (VPU).

Keywords: deep learning, convolutional neural networks, road condition classification, embedded systems

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Authors: Inemesit Akpan Umoren, Aniekan James Akpan

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Media practitioners and information managers have often erroneously operated on the premise that media messages are received as disseminated to the extent that audiences of whatever background assimilate the content uniformly. This does not subsist since media audiences are often segmented in terms of educational level, social category, place of residence, gender, among others. While those who are highly educated, live in urban areas and are of highest standing are more likely to have direct access to the media, those in the rural areas and of low education and standing, may not have direct or easy access. These, therefore, informed the study to establish the consumption patterns of mass media products by residents of rural communities in south-south, Nigeria. The study, which was anchored on the multi-step flow and social categories theories, adopted a survey research design and a sample of 383 using Mayer’s 1979 guide drawn from nine rural communities in the south-south, Nigeria states of Akwa Ibom, Rivers and Edo. Findings among others showed that while a negligible percentage is highly exposed to media messages of all types, a greater member depend on opinion leaders, social groups, drinking joints, among other such for filtered content. It was concluded that since rural or community media organizations are very vital in ensuring media content get to all audience without necessarily being passing through intermediaries. Among the recommendations was that information managers and media organizations should always have in mind the ruralites while packaging their contents even in the mainstream media.

Keywords: consumption, media, media product, pattern

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Authors: Abdulkader Helwan

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Iris cancer, so called intraocular melanoma is a cancer that starts in the iris; the colored part of the eye that surrounds the pupil. There is a need for an accurate and cost-effective iris cancer detection system since the available techniques used currently are still not efficient. The combination of the image processing and artificial neural networks has a great efficiency for the diagnosis and detection of the iris cancer. Image processing techniques improve the diagnosis of the cancer by enhancing the quality of the images, so the physicians diagnose properly. However, neural networks can help in making decision; whether the eye is cancerous or not. This paper aims to develop an intelligent system that stimulates a human visual detection of the intraocular melanoma, so called iris cancer. The suggested system combines both image processing techniques and neural networks. The images are first converted to grayscale, filtered, and then segmented using prewitt edge detection algorithm to detect the iris, sclera circles and the cancer. The principal component analysis is used to reduce the image size and for extracting features. Those features are considered then as inputs for a neural network which is capable of deciding if the eye is cancerous or not, throughout its experience adopted by many training iterations of different normal and abnormal eye images during the training phase. Normal images are obtained from a public database available on the internet, “Mile Research”, while the abnormal ones are obtained from another database which is the “eyecancer”. The experimental results for the proposed system show high accuracy 100% for detecting cancer and making the right decision.

Keywords: iris cancer, intraocular melanoma, cancerous, prewitt edge detection algorithm, sclera

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Authors: Rajesh Chakraborty, Dibyendu Das, Rabindra Nath Barman, Uttam Kumar Mandal

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In the present study, the objective is to find out the most effective zone causing soil erosion in the Gumati river basin located in the state of Tripura, a north eastern state of India using analytical hierarchy process (AHP) and multi-objective optimization on the basis of ratio analysis (MOORA).The watershed is segmented into 20 zones based on Area. The watershed is considered by pointing the maximum elevation from sea lever from Google earth. The soil erosion is determined using the universal soil loss equation. The different independent variables of soil loss equation bear different weightage for different soil zones. And therefore, to find the weightage factor for all the variables of soil loss equation like rainfall runoff erosivity index, soil erodibility factor etc, analytical hierarchy process (AHP) is used. And thereafter, multi-objective optimization on the basis of ratio analysis (MOORA) approach is used to select the most effective zone causing soil erosion. The MCDM technique concludes that the maximum soil erosion is occurring in the zone 14.

Keywords: soil erosion, analytic hierarchy process (AHP), multi criteria decision making (MCDM), universal soil loss equation (USLE), multi-objective optimization on the basis of ratio analysis (MOORA)

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Authors: Christobel Gondwe, Yongtao Lu, Claudia Mazzà, Xinshan Li

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Skeletal muscle plays an important role in the human body system and function by generating voluntary forces and facilitating body motion. However, The mechanical properties and behaviour of skeletal muscle are still not comprehensively known yet. As such, various robust engineering techniques have been applied to better elucidate the mechanical behaviour of skeletal muscle. It is considered that muscle mechanics are highly governed by the architecture of the fibre orientations. Therefore, the aim of this study was to investigate the effect of different fibre orientations on the mechanical behaviour of skeletal muscle.In this study, a continuum mechanics approach–finite element (FE) analysis was applied to the left bicep femoris long head to determine the contractile mechanism of the muscle using Hill’s three-element model. The geometry of the muscle was segmented from the magnetic resonance images. The muscle was modelled as a quasi-incompressible hyperelastic (Mooney-Rivlin) material. Two types of fibre orientations were implemented: one with the idealised fibre arrangement, i.e. parallel single-direction fibres going from the muscle origin to insertion sites, and the other with curved fibre arrangement which is aligned with the muscle shape.The second fibre arrangement was implemented through the finite element method; non-uniform rational B-spline (FEM-NURBs) technique by means of user material (UMAT) subroutines. The stress-strain behaviour of the muscle was investigated under idealised exercise conditions, and will be further analysed under physiological conditions. The results of the two different FE models have been outputted and qualitatively compared.

Keywords: FEM-NURBS, finite element analysis, Mooney-Rivlin hyperelastic, muscle architecture

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Authors: Kornelius Ronald Demu, Dewi Retno Sari Saputro, Purnami Widyaningsih

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Human Development Index (HDI) is a standard measurement for a country's human development. Several factors may have influenced it, such as life expectancy, gross domestic product (GDP) based on the province's annual expenditure, the number of poor people, and the percentage of an illiterate people. The scatter plot between HDI and the influenced factors show that the plot does not follow a specific pattern or form. Therefore, the HDI's data in Indonesia can be applied with a nonparametric regression model. The estimation of the regression curve in the nonparametric regression model is flexible because it follows the shape of the data pattern. One of the nonparametric regression's method is a truncated spline. Truncated spline regression is one of the nonparametric approach, which is a modification of the segmented polynomial functions. The estimator of a truncated spline regression model was affected by the selection of the optimal knots point. Knot points is a focus point of spline truncated functions. The optimal knots point was determined by the minimum value of generalized cross validation (GCV). In this article were applied the data of Human Development Index with a truncated spline nonparametric regression model. The results of this research were obtained the best-truncated spline regression model to the HDI's data in Indonesia with the combination of optimal knots point 5-5-5-4. Life expectancy and the percentage of an illiterate people were the significant factors depend to the HDI in Indonesia. The coefficient of determination is 94.54%. This means the regression model is good enough to applied on the data of HDI in Indonesia.

Keywords: generalized cross validation (GCV), Human Development Index (HDI), knots point, nonparametric regression, truncated spline

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Authors: Ira V. Stancheva, Ely G. Zayova, Maria P. Geneva, Marieta G. Hristozkova, Lyudmila I. Dimitrova, Maria I. Petrova

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The study describes a highly efficient and low-cost protocol for rapid and mass in vitro propagation of medicinal and aromatic plant species (Hyssopus officinalis L., Lamiaceae). Hyssop is an important aromatic herb used for its medicinal values because of its antioxidant, anti-inflammatory and antimicrobial properties. The protocol for large-scale multiplication of this aromatic plant was developed using young stem tips explants. The explants were sterilized with 0.04% mercuric chloride (HgCl₂) solution for 20 minutes and washing three times with sterile distilled water in 15 minutes. The cultural media was full and half strength Murashige and Skoog medium containing indole-3-butyric acid. Full and ½ Murashige and Skoog media without auxin were used as controls. For each variant 20 glass tubes with two plants were used. In each tube two tip and nodal explants were inoculated. Maximum shoot and root number were obtained on ½ Murashige and Skoog medium supplemented with 0.1 mg L-1 indole-3-butyric acid at the same time after four weeks of culture. The number of shoots per explant and shoot height were considered. The data on rooting percentage, the number of roots per plant and root length were collected after the same cultural period. The highest percentage of survival 85% for this medicinal plant was recorded in mixture of soil, sand and perlite (2:1:1 v/v/v). This mixture was most suitable for acclimatization of all propagated plants. Ex vitro acclimatization was carried out at 24±1 °C and 70% relative humidity under 16 h illuminations (50 μmol m⁻²s⁻¹). After adaptation period, the all plants were transferred to the field. The plants flowered within three months after transplantation. Phenotypic variations in the acclimatized plants were not observed. An average of 90% of the acclimatized plants survived after transferring into the field. All the in vitro propagated plants displayed normal development under the field conditions. Developed in vitro techniques could provide a promising alternative tool for large-scale propagation that increases the number of homologous plants for field cultivation. Acknowledgments: This study was conducted with financial support from National Science Fund at the Bulgarian Ministry of Education and Science, Project DN06/7 17.12.16.

Keywords: Hyssopus officinalis L., in vitro culture, micro propagation, acclimatization

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Authors: Mehrnoosh Omati, Mahmod Reza Sahebi

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The information on land use/land cover changing plays an essential role for environmental assessment, planning and management in regional development. Remotely sensed imagery is widely used for providing information in many change detection applications. Polarimetric Synthetic aperture radar (PolSAR) image, with the discrimination capability between different scattering mechanisms, is a powerful tool for environmental monitoring applications. This paper proposes a new boundary-based segmentation algorithm as a fundamental step for land cover change detection. In this method, first, two PolSAR images are segmented using integration of marker-controlled watershed algorithm and coupled Markov random field (MRF). Then, object-based classification is performed to determine changed/no changed image objects. Compared with pixel-based support vector machine (SVM) classifier, this novel segmentation algorithm significantly reduces the speckle effect in PolSAR images and improves the accuracy of binary classification in object-based level. The experimental results on Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) polarimetric images show a 3% and 6% improvement in overall accuracy and kappa coefficient, respectively. Also, the proposed method can correctly distinguish homogeneous image parcels.

Keywords: coupled Markov random field (MRF), environment, object-based analysis, polarimetric SAR (PolSAR) images

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Authors: Hadri Hussain, M.Nasir Ibrahim, Chee-Ming Ting, Mariani Idroas, Fuad Numan, Alias Mohd Noor

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A biometric security system has become an important application in client identification and verification system. A conventional biometric system is normally based on unimodal biometric that depends on either behavioural or physiological information for authentication purposes. The behavioural biometric depends on human body biometric signal (such as speech) and biosignal biometric (such as electrocardiogram (ECG) and phonocardiogram or heart sound (HS)). The speech signal is commonly used in a recognition system in biometric, while the ECG and the HS have been used to identify a person’s diseases uniquely related to its cluster. However, the conventional biometric system is liable to spoof attack that will affect the performance of the system. Therefore, a multimodal biometric security system is developed, which is based on biometric signal of ECG, HS, and speech. The biosignal data involved in the biometric system is initially segmented, with each segment Mel Frequency Cepstral Coefficients (MFCC) method is exploited for extracting the feature. The Hidden Markov Model (HMM) is used to model the client and to classify the unknown input with respect to the modal. The recognition system involved training and testing session that is known as client identification (CID). In this project, twenty clients are tested with the developed system. The best overall performance at 44 kHz was 93.92% for ECG and the worst overall performance was ECG at 88.47%. The results were compared to the best overall performance at 44 kHz for (20clients) to increment of clients, which was 90.00% for HS and the worst overall performance falls at ECG at 79.91%. It can be concluded that the difference multimodal biometric has a substantial effect on performance of the biometric system and with the increment of data, even with higher frequency sampling, the performance still decreased slightly as predicted.

Keywords: electrocardiogram, phonocardiogram, hidden markov model, mel frequency cepstral coeffiecients, client identification

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Authors: Naeim Akbari Shahkhosravi, Reza Kakavand, Helen M. S. Davies, Amin Komeili

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Equine locomotion and performance are significantly affected by hoof health. One of the most critical diseases of the hoof is laminitis, which can lead to horse lameness in a severe condition. This disease exhibits the mechanical properties degradation of the laminar junction tissue within the hoof. Therefore, it is essential to investigate the biomechanics of the hoof, focusing specifically on excessive and cumulatively accumulated stresses within the laminar junction tissue. For this aim, the current study generated a novel equine hoof Finite Element (FE) model under dynamic physiological loading conditions and employing a hyperelastic material model. Associated tissues of the equine hoof were segmented from computed tomography scans of an equine forelimb, including the navicular bone, third phalanx, sole, frog, laminar junction, digital cushion, and medial- dorsal- lateral wall areas. The inner tissues were connected based on the hoof anatomy, and the hoof was under a dynamic loading over cyclic strides at the trot. The strain distribution on the hoof wall of the model was compared with the published in vivo strain measurements to validate the model. Then the validated model was used to study the development of laminitis. The ultimate stress tolerated by the laminar junction before rupture was considered as a stress threshold. The tissue damage was simulated through iterative reduction of the tissue’s mechanical properties in the presence of excessive maximum principal stresses. The findings of this investigation revealed how damage initiates from the medial and lateral sides of the tissue and propagates through the hoof dorsal area.

Keywords: horse hoof, laminitis, finite element model, continuous damage

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Authors: Belgherbi Aicha, Bessaid Abdelhafid

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

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

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Authors: Chamilani Nikapitiya, Mahanama De Zoysa, Jehee Lee

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Most of the bacterial diseases are associated with high mortalities in aquaculture species and causing huge economic losses. Different approaches have been taken to prevent or control of bacterial diseases including use of vaccines, probiotics, chemotherapy, water quality management, etc. Antibiotics are widely applying as chemotherapy to control bacterial diseases, however, it has been shown that frequent use of antibiotics is favored to develop multi-drug resistance bacteria. Therefore, phages and phage encoded lytic proteins are known to be one of the most promising alternatives for antibiotics to avoid the emergence of antibiotic-resistant bacteria. We isolated and characterized the two lytic phages, namely pAh-1 and pAs-1 against pathogenic Aeromonas hydrophila and Aeromonas salmonicida, respectively. Morphological characteristics were analyzed by Transmission electron microscopy (TEM) and host strain specificities were tested with Aeromonas and other closely related bacterial strains. TEM analysis revealed that both pAh-1 and pAsm-1 are composed of an icosahedral head and a segmented tail, and we suggest that, they are new members of Myoviridae family. Genome sizes of isolated phages were estimated by restriction enzyme digestion of genomic DNA using selected endonucleases followed by agarose gel electrophoresis. Estimated genome size of pAh-1 and pAs-1 were approximately 64 Kbp and 120 Kbp, respectively. Both pAh-1 and pAs-1 have shown narrow host specificity. Moreover, protective effects of phage therapy against fish pathogenic A. hydrophila were investigated in zebrafish model. The survival rate was 40% higher when zebrafish received intra-peritoneal injection (i.p.) of pAh-1 were simultaneously challenge A. hydrophila (2 x 106 CFU/fish) compared to that without phage treatment. Overall results suggest that both pAh-1 and pAs-1 can be used as a potential phage therapy to control Aeromonas infections in aquaculture.

Keywords: Aeromonas infections, antibiotic resistance, bacteriophage, bio-control, lytic phage

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Authors: Zouhair Haddi, Stephane Delliaux, Jean-Francois Pons, Ismail Kechaf, Jean-Claude De Haro, Mustapha Ouladsine

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Atrial fibrillation (AF) has been considered as the most common cardiac arrhythmia, and a major public health burden associated with significant morbidity and mortality. Nowadays, telemedical approaches targeting cardiac outpatients situate AF among the most challenged medical issues. The automatic, early, and fast AF detection is still a major concern for the healthcare professional. Several algorithms based on univariate analysis have been developed to detect atrial fibrillation. However, the published results do not show satisfactory classification accuracy. This work was aimed at resolving this shortcoming by proposing multivariate data analysis methods for automatic AF detection. Four publicly-accessible sets of clinical data (AF Termination Challenge Database, MIT-BIH AF, Normal Sinus Rhythm RR Interval Database, and MIT-BIH Normal Sinus Rhythm Databases) were used for assessment. All time series were segmented in 1 min RR intervals window and then four specific features were calculated. Two pattern recognition methods, i.e., Principal Component Analysis (PCA) and Learning Vector Quantization (LVQ) neural network were used to develop classification models. PCA, as a feature reduction method, was employed to find important features to discriminate between AF and Normal Sinus Rhythm. Despite its very simple structure, the results show that the LVQ model performs better on the analyzed databases than do existing algorithms, with high sensitivity and specificity (99.19% and 99.39%, respectively). The proposed AF detection holds several interesting properties, and can be implemented with just a few arithmetical operations which make it a suitable choice for telecare applications.

Keywords: atrial fibrillation, multivariate data analysis, automatic detection, telemedicine

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Authors: Abdul Hamid Mir

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Tourism which is considered as the economic bonanza of Jammu and Kashmir plays an important role in the socio-economic development of Jammu and Kashmir. It is considered as a multi-segmented industry which provides different type of jobs like hotel managers, receptionists, guides, tour operators, travel agents, photographers, etc. Kashmir Valley which is one of the three meso regions (Jammu, Kashmir and Ladakh) of Jammu and Kashmir State is famous all over the world due to its natural beauty. It attracts tourists from the every corner of the globe that is why it has earned name as ‘Paradise on Earth’ and ‘Switzerland of Asia’. It is full of natural treasure and gratifies the several types of tourists. The tourists are experiences fun, thrilling events and safe experience in Kashmir valley, but on the other hand, the adventure tourists are experiencing the physical risks, dangers and losses (injuries, death etc) too. Kashmir valley has greater potential to become one of the best adventure tourism destinations in the world. It offers immense opportunities to the adventurists to explore the wonderful exotic Himalayan ranges and landscapes, in addition, to facing the challenges of fast flowing rivers. Adventure tourism is at the initial stage of development in Kashmir valley and virgin areas needs to be explored and develop which in result will increase not only tourist arrivals but also enhance the business opportunities and economy of local people in Kashmir. Thus the exploitation of virginity of adventure tourism potentials in Kashmir valley is need of the hour. Therefore the present study highlights the potentials of adventure tourism in Kashmir valley and also focuses on the problems in the development of adventure tourism. Furthermore, the study extends to give various recommendations and suggestions in order to develop adventure tourism and broaden the base of tourist arrivals on one hand and sustained the growth on the other hand.

Keywords: adventure, Kashmir, tourism, tourists, potential, rafting, skiing

Procedia PDF Downloads 226

Authors: Ronald Collins, Jonathon Coleman, Joel Dasari, George Holt, Carl Metelko, Matthew Murdoch, Alexander Morgan, Yan-Jie Schnellbach, Robert Mills, Gareth Edwards, Alexander Roberts

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At the Wylfa Magnox Power Plant between 2014–2016, the VIDARR prototype anti-neutrino detector was deployed. It is comprised of extruded plastic scintillating bars measuring 4 cm × 1 cm × 152 cm and utilised wavelength shifting fibres (WLS) and multi-pixel photon counters (MPPCs) to detect and quantify radiation. During deployment, it took cosmic muon data in accidental coincidence with the anti-neutrino measurements with the power plant site buildings obscuring the muon sky. Cosmic muons have a significantly higher probability of being attenuated and/or absorbed by denser objects, and so one-sided cosmic muon tomography was utilised to image the reactor site buildings. In order to achieve clear building outlines, a control data set was taken at the University of Liverpool from 2016 – 2018, which had minimal occlusion of the cosmic muon flux by dense objects. By taking the ratio of these two data sets and using GEANT4 simulations, it is possible to perform a one-sided cosmic muon tomography analysis. This analysis can be used to discern specific buildings, building heights, and features at the Wylfa reactor site, including the reactor core/reactor core shielding using ∼ 3 hours worth of cosmic-ray detector live time. This result demonstrates the feasibility of using cosmic muon analysis to determine a segmented detector’s location with respect to surrounding buildings, assisted by aerial photography or satellite imagery.

Keywords: anti-neutrino, GEANT4, muon, tomography, occlusion

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Authors: Halimatu S. Abdullahi, Ray E. Sheriff, Fatima Mahieddine

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Agriculture is essential to the continuous existence of human life as they directly depend on it for the production of food. The exponential rise in population calls for a rapid increase in food with the application of technology to reduce the laborious work and maximize production. Technology can aid/improve agriculture in several ways through pre-planning and post-harvest by the use of computer vision technology through image processing to determine the soil nutrient composition, right amount, right time, right place application of farm input resources like fertilizers, herbicides, water, weed detection, early detection of pest and diseases etc. This is precision agriculture which is thought to be solution required to achieve our goals. There has been significant improvement in the area of image processing and data processing which has being a major challenge. A database of images is collected through remote sensing, analyzed and a model is developed to determine the right treatment plans for different crop types and different regions. Features of images from vegetations need to be extracted, classified, segmented and finally fed into the model. Different techniques have been applied to the processes from the use of neural network, support vector machine, fuzzy logic approach and recently, the most effective approach generating excellent results using the deep learning approach of convolution neural network for image classifications. Deep Convolution neural network is used to determine soil nutrients required in a plantation for maximum production. The experimental results on the developed model yielded results with an average accuracy of 99.58%.

Keywords: convolution, feature extraction, image analysis, validation, precision agriculture

Procedia PDF Downloads 296

Authors: Maria C. Proença, Maria T. Rebelo, Marília Antunes, Maria J. Alves, Hugo Osório, Sofia Cunha, João Casaca

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Using a geographic information system (GIS), the relations between a georeferenced data set of Culex pipiens sl. mosquitoes collected in Portugal mainland during seven years (2006-2012) and meteorological and physiographic parameters such as: air relative humidity, air temperature (minima, maxima and mean daily temperatures), daily total rainfall, altitude, land use/land cover and proximity to water bodies are evaluated. Focus is on the mosquito females; the characterization of its habitat is the key for the planning of chirurgical non-aggressive prophylactic countermeasures to avoid ambient degradation. The GIS allow for the spatial determination of the zones were the mosquito mean captures has been above average; using the meteorological values at these coordinates, the limits of each parameter are identified/computed. The meteorological parameters measured at the net of weather stations all over the country are averaged by month and interpolated to produce raster maps that can be segmented according to the thresholds obtained for each parameter. The intersection of the maps obtained for each month show the evolution of the area favorable to the species through the mosquito season, which is from May to October at these latitudes. In parallel, mean and above average captures were related to the physiographic parameters. Three levels of risk could be identified for each parameter, using above average captures as an index. The results were applied to the suitability meteorological maps of each month. The Culex pipiens critical niche is delimited, reflecting the critical areas and the level of risk for transmission of the pathogens to which they are competent vectors (West Nile virus, iridoviruses, rheoviruses and parvoviruses).

Keywords: Culex pipiens, ecological niche, risk assessment, risk management

Procedia PDF Downloads 521