Search results for: market segmentation

Authors: Aishik Deb, Rituparna Sinha

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We have developed an algorithm to detect the abnormal segment/"structural variation in the genome across a number of samples. We have worked on simulated as well as real data from the BAM Files and have designed a segmentation algorithm where abnormal segments are detected. This algorithm aims to improve the accuracy and performance of the existing CNV-CH algorithm. The next-generation sequencing (NGS) approach is very fast and can generate large sequences in a reasonable time. So the huge volume of sequence information gives rise to the need for Big Data and parallel approaches of segmentation. Therefore, we have designed a map-reduce approach for the existing CNV-CH algorithm where a large amount of sequence data can be segmented and structural variations in the human genome can be detected. We have compared the efficiency of the traditional and map-reduce algorithms with respect to precision, sensitivity, and F-Score. The advantages of using our algorithm are that it is fast and has better accuracy. This algorithm can be applied to detect structural variations within a genome, which in turn can be used to detect various genetic disorders such as cancer, etc. The defects may be caused by new mutations or changes to the DNA and generally result in abnormally high or low base coverage and quantification values.

Keywords: cancer detection, convex hull segmentation, map reduce, next generation sequencing

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Authors: Yousif Mohamed Y. Abdallah, Mommen A. Alkhir, Amel S. Algaddal

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This was experimental study conducted to study segmentation of brain in MRI images using edge detection and morphology filters. For brain MRI images each film scanned using digitizer scanner then treated by using image processing program (MatLab), where the segmentation was studied. The scanned image was saved in a TIFF file format to preserve the quality of the image. Brain tissue can be easily detected in MRI image if the object has sufficient contrast from the background. We use edge detection and basic morphology tools to detect a brain. The segmentation of MRI images steps using detection and morphology filters were image reading, detection entire brain, dilation of the image, filling interior gaps inside the image, removal connected objects on borders and smoothen the object (brain). The results of this study were that it showed an alternate method for displaying the segmented object would be to place an outline around the segmented brain. Those filters approaches can help in removal of unwanted background information and increase diagnostic information of Brain MRI.

Keywords: improvement, brain, matlab, markers, boundaries

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Authors: Abder-Rahman Ali, Antoine Vacavant, Manuel Grand-Brochier, Adélaïde Albouy-Kissi, Jean-Yves Boire

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In this paper, we present a new segmentation approach for liver lesions in regions of interest within MRI (Magnetic Resonance Imaging). This approach, based on a two-cluster Fuzzy C-Means methodology, considers the parameter variable compactness to handle uncertainty. Fine boundaries are detected by a local recursive merging of ambiguous pixels with a sequential forward floating selection with Zernike moments. The method has been tested on both synthetic and real images. When applied on synthetic images, the proposed approach provides good performance, segmentations obtained are accurate, their shape is consistent with the ground truth, and the extracted information is reliable. The results obtained on MR images confirm such observations. Our approach allows, even for difficult cases of MR images, to extract a segmentation with good performance in terms of accuracy and shape, which implies that the geometry of the tumor is preserved for further clinical activities (such as automatic extraction of pharmaco-kinetics properties, lesion characterization, etc).

Keywords: defuzzification, floating search, fuzzy clustering, Zernike moments

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Authors: Atanu K Samanta, Asim Ali Khan

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Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: brain tumor, computer-aided diagnostic (CAD) system, gray-level co-occurrence matrix (GLCM), tumor segmentation, level set method

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Authors: Saurabh Farkya, Govinda Surampudi

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Optical Character Recognition is one of the current major research areas. This paper is focussed on recognition of Devanagari script and its sound generation. This Paper consists of two parts. First, Optical Character Recognition of Devnagari handwritten Script. Second, speech synthesis of the recognized text. This paper shows an implementation of support vector machines for the purpose of Devnagari Script recognition. The Support Vector Machines was trained with Multi Domain features; Transform Domain and Spatial Domain or Structural Domain feature. Transform Domain includes the wavelet feature of the character. Structural Domain consists of Distance Profile feature and Gradient feature. The Segmentation of the text document has been done in 3 levels-Line Segmentation, Word Segmentation, and Character Segmentation. The pre-processing of the characters has been done with the help of various Morphological operations-Otsu's Algorithm, Erosion, Dilation, Filtration and Thinning techniques. The Algorithm was tested on the self-prepared database, a collection of various handwriting. Further, Unicode was used to convert recognized Devnagari text into understandable computer document. The document so obtained is an array of codes which was used to generate digitized text and to synthesize Hindi speech. Phonemes from the self-prepared database were used to generate the speech of the scanned document using concatenation technique.

Keywords: Character Recognition (OCR), Text to Speech (TTS), Support Vector Machines (SVM), Library of Support Vector Machines (LIBSVM)

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Authors: Panupong Chanplin, Wilailuk Mepracha, Sathapath Kilaso

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The aims of this research were twofold: 1) to logo design of Huay Kon Border Market, Chaloemphrakiat District, Nan Province and 2) to study the level of tourist satisfaction towards logo design of Huay Kon Border Market, Chaloemphrakiat District, Nan Province. Tourist satisfaction was measured using four criteria: a unique product identity, ease of remembrance, product utility, and beauty/impressiveness. The researcher utilized a probability sampling method via simple random sampling. The sample consisted of 30 tourists in the Huay Kon Border Market. Statistics utilized for data analysis were percentage, mean, and standard deviation. The results suggest that tourist had high levels of satisfaction towards all four criteria of the logo design that was designed to target them. This study proposes that specifically logo designed of Huay Kon Border Market could also be implemented with other real media already available on the market.

Keywords: satisfaction, logo, design, Huay Kon border market

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Authors: Temitope Faloye

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The absence of equity and transparency in Nigeria's economic system has resulted in unemployment. Women’s unemployment rate remains higher because women's range of jobs is often narrower due to discriminatory attitudes of employers and gender segregation in the labor market. Gender inequality is one of the strong factors of unemployment, especially in developing countries like Nigeria, where the female gender is marginalized in the labor force market. However, gender equality in terms of labor market access and employment condition has not yet been attained. Feminist theory is considered as an appropriate theory for this study. The study will use a mixed-method design, collecting qualitative and quantitative data to provide answers to the research questions. Therefore, the research study aims to investigate the present situation of gender inequality in the Nigerian labor market.

Keywords: unemployment, gender inequality, gender equality, labor market, female graduate

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Authors: Marina Chavleishvili

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Introduction: Today, the study of monopolies, including natural monopolies, is topical. In real life, pure monopolies are natural monopolies. Natural monopolies are used widely and are regulated by the state. In particular, the prices and rates are regulated. The paper considers the problems associated with the operation of natural monopolies in Georgia, in particular, their microeconomic analysis, pricing mechanisms, and legal mechanisms of their operation. The analysis was carried out on the example of the power industry. The rates of natural monopolies in Georgia are controlled by the Georgian National Energy and Water Supply Regulation Commission. The paper analyzes the positive role and importance of the regulatory body and the issues of improving the legislative base that will support the efficient operation of the branch. Methodology: In order to highlight natural monopolies market tendencies, the domestic and international markets are studied. An analysis of monopolies is carried out based on the endogenous and exogenous factors that determine the condition of companies, as well as the strategies chosen by firms to increase the market share. According to the productivity-based competitiveness assessment scheme, the segmentation opportunities, business environment, resources, and geographical location of monopolist companies are revealed. Main Findings: As a result of the analysis, certain assessments and conclusions were made. Natural monopolies are quite a complex and versatile economic element, and it is important to specify and duly control their frame conditions. It is important to determine the pricing policy of natural monopolies. The rates should be transparent, should show the level of life in the country, and should correspond to the incomes. The analysis confirmed the significance of the role of the Antimonopoly Service in the efficient management of natural monopolies. The law should adapt to reality and should be applied only to regulate the market. The present-day differential electricity tariffs varying depending on the consumed electrical power need revision. The effects of the electricity price discrimination are important, segmentation in different seasons in particular. Consumers use more electricity in winter than in summer, which is associated with extra capacities and maintenance costs. If the price of electricity in winter is higher than in summer, the electricity consumption will decrease in winter. The consumers will start to consume the electricity more economically, what will allow reducing extra capacities. Conclusion: Thus, the practical realization of the views given in the paper will contribute to the efficient operation of natural monopolies. Consequently, their activity will be oriented not on the reduction but on the increase of increments of the consumers or producers. Overall, the optimal management of the given fields will allow for improving the well-being throughout the country. In the article, conclusions are made, and the recommendations are developed to deliver effective policies and regulations toward the natural monopolies in Georgia.

Keywords: monopolies, natural monopolies, regulation, antimonopoly service

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Authors: Qura-tul-aain Khair

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Purpose- The purpose of this paper is to empirically examining the strength of association of responsive market orientation and proactive market orientation with new product performance and exploring the possible moderating role of organizational learning based on contingency theory. Design/methodology/approach- Data for this study was collected from FMCG manufacturing industry and services industry, where customers are in contact frequently and responses are recorded on continuous basis. Sample was collected through convenience sampling. The data collected from different marketing department and sales personnel were analysed using SPSS 16 version. Findings- The paper finds that responsive market orientation is more strongly associated with new product performance. The moderator, organizational learning, plays it significant role on the relationship between responsive market orientation and new product performance. Research limitations/implications- this paper has taken sample from just FMCG industry and service industry, more work can be done regarding how different-markets require different market orientation behaviours. Originality/value- This paper will be useful for foreign business looking for investing and expanding in Pakistan, they can find opportunity to get sustained competitive advantage through exploring the proactive side of market orientation and importance of organizational learning.

Keywords: organizational learning, proactive market orientation, responsive market orientation, new product performance

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Authors: B. Afsharipoor, E. Nazemi

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Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.

Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN

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Authors: J. Gochermann

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German energy market is under historical change. Turning-off the nuclear power plants and intensive subsidization of the renewable energies causes a paradigm change from big central energy production and distribution to more local structures, bringing the energy production near to the consumption. The formerly big energy market with only a few big energy plants and grid operating companies is changing into a disperse market with growing numbers of small and medium size companies (SME) generating new value-added products and services. This change in then energy market, in Germany called the “Energiewende”, inverts also the previous innovation system. Big power plants and large grids required also big operating companies. Innovations in the energy market focused mainly on big projects and complex energy technologies. Innovation in the new energy market structure is much more dispersed. Increasing number of SME is now able to develop energy production and storage technologies, smart technologies to control the grids, and numerous new energy related services. Innovation is now regional distributed, which is a remarkable problem for the old big energy companies. The paper will explain the change in the German energy market and the paradigm change as well as the consequences for the innovation structure in the German energy market. It will show examples how SME participate from this change and how innovation systems, as well for the big companies and for SME, can be adapted.

Keywords: changing energy markets, disperse innovation, new value-added products and services, SME

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Authors: Rosdyana Mangir Irawan Kusuma, Wei-Chun Kao, Ho-Thi Trang, Yu-Yen Ou, Kai-Lung Hua

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Stock market prediction is still a challenging problem because there are many factors that affect the stock market price such as company news and performance, industry performance, investor sentiment, social media sentiment, and economic factors. This work explores the predictability in the stock market using deep convolutional network and candlestick charts. The outcome is utilized to design a decision support framework that can be used by traders to provide suggested indications of future stock price direction. We perform this work using various types of neural networks like convolutional neural network, residual network and visual geometry group network. From stock market historical data, we converted it to candlestick charts. Finally, these candlestick charts will be feed as input for training a convolutional neural network model. This convolutional neural network model will help us to analyze the patterns inside the candlestick chart and predict the future movements of the stock market. The effectiveness of our method is evaluated in stock market prediction with promising results; 92.2% and 92.1 % accuracy for Taiwan and Indonesian stock market dataset respectively.

Keywords: candlestick chart, deep learning, neural network, stock market prediction

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Authors: Ahmed Elmarhomy, K. Terada

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An automated method for counting passerby has been proposed using virtual-vertical measurement lines. Space-time image is representing the human regions which are treated using the segmentation process. Different color space has been used to perform the template matching. A proper template matching has been achieved to determine direction and speed of passing people. Distinguish one or two passersby has been investigated using a correlation between passerby speed and the human-pixel area. Finally, the effectiveness of the presented method has been experimentally verified.

Keywords: counting people, measurement line, space-time image, segmentation, template matching

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

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Being able to identify biological particles such as spores, viruses, or pollens is important for health care professionals, as it allows for appropriate therapeutic management of patients. Optical microscopy is a technology widely used for the analysis of these types of microorganisms, because, compared to other types of microscopy, it is not expensive. The analysis of an optical microscope slide is a tedious and time-consuming task when done manually. However, using machine learning and computer vision, this process can be automated. The first step of an automated microscope slide image analysis process is segmentation. During this step, the biological particles are localized and extracted. Very often, the use of an automatic thresholding method is sufficient to locate and extract the particles. However, in some cases, the particles are not extracted individually because they are stuck to other biological elements. In this paper, we propose a stuck particles separation method based on the use of the Sobel operator and thresholding. We illustrate it by applying it to the separation of 813 images of adjacent pollen grains. The method correctly separated 95.4% of these images.

Keywords: image segmentation, stuck particles separation, Sobel operator, thresholding

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Authors: Irina Bondarenko, Olga Vandina

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The theory of evolutionary economics is the basis for preparation and application of methods forming the stock market infrastructure development concept. The authors believe that the basis for the process of formation and development of the stock market model infrastructure in Russia is the theory of large systems. This theory considers the financial market infrastructure as a whole on the basis of macroeconomic approach with the further definition of its aims and objectives. Evaluation of the prospects for interaction of securities market institutions will enable identifying the problems associated with the development of this system. The interaction of elements of the stock market infrastructure allows to reduce the costs and time of transactions, thereby freeing up resources of market participants for more efficient operation. Thus, methodology of the transaction analysis allows to determine the financial infrastructure as a set of specialized institutions that form a modern quasi-stable system. The financial infrastructure, based on international standards, should include trading systems, regulatory and supervisory bodies, rating agencies, settlement, clearing and depository organizations. Distribution of financial assets, reducing the magnitude of transaction costs, increased transparency of the market are promising tasks in the solution for questions of services level and quality increase provided by institutions of the securities market financial infrastructure. In order to improve the efficiency of the regulatory system, it is necessary to provide "standards" for all market participants. The development of a clear regulation for the barrier to the stock market entry and exit, provision of conditions for the development and implementation of new laws regulating the activities of participants in the securities market, as well as formulation of proposals aimed at minimizing risks and costs, will enable the achievement of positive results. The latter will be manifested in increasing the level of market participant security and, accordingly, the attractiveness of this market for investors and issuers.

Keywords: institutional infrastructure, financial assets, regulatory system, stock market, transparency of the market

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Authors: Prabhvir Singh Marway, Kai Lok Chan, Maria-Ruxandra Jinga, Rachel Bok Ying Lee, Matthew Bok Kit Lee, Krishan Nandapalan, Sze Yi Beh, Harry Carr, Christopher Kui

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We piloted a structured series of online workshops on the 3D segmentation of anatomical structures from CT scans. 33 participants were recruited from four UK universities for two-day workshops between 2020 and 2021. Open-source software (3D-Slicer) was used. We hypothesized that active participation via real-time screen-sharing and voice-communication via Discord would enable improved engagement and learning, despite national lockdowns. Written feedback indicated positive learning experiences, with subjective measures of anatomical understanding and software confidence improving.

Keywords: medical education, workshop, segmentation, anatomy

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Authors: Sebastiana Viphindratin, Silvi Asna

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The under ground economy phenomenon is exist in Indonesia. There are some factors which affect the existence this underground economy activity. One of them is a hierarchy power structure that handles the underground economy existence. The example of the existence of underground economy is the occurring informal market in Indonesia. Malang city is one of the city which has this kind of market. Junk night market (JNM) as an underground economy activity is arising in that city. The JNM is located in Gatot Subroto Sidewalk Street. The JNM is a illegal market which sell thrift, antique, imitation and black market goods. The JNM is interesting topic to be discussed, because this market is running in long time without any policy from local government. The JNM activity has their own “power” that run the market rules. Thus, it is important to analyze how the existence and power structure of JNM actors community are in Malang city. This research using qualitative method with phenomenological approach where we try to understand the phenomenon and related actors deeply. The aim of this research is to know the existence and power structure of JNM actors community in Malang. In JNM, there is no any entry barriers and tax charge from Malang government itself. Price competition also occurs because the buyer can do a bargain with the seller. In maintaining buyer loyalty, the JNM actors also do pre-order system. Even though, this market is an illegal market but the JNM actors also give the goods guarantee (without legal contract) as a formal market. In JNM actor’s community, there is no hierarchy and formal power structure. The role in JNM is managed by informal leaders who come up from the trading activity problems that are sidewalk and parking area dividing. Therefore, can be concluded that even the JNM is illegal market but it can survive with natural market pattern. In JNM development, JNM has positive and negative impact for Malang city. The positive impact of JNM is this market can open a new employment but the negative impact is there is no tax income from that market. Therefore, suggested that the government of Malang city should manage and give appropriate policies in this case.

Keywords: junk night market (JNM), Malang city, underground economy, illegal

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Authors: Nadia Sghaier

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In this paper, we examine the influence of the COVID-19 pandemic on the performance of the Tunisian stock market and 12 sectors over a recent period from 23 March 2020 to 18 August 2021, including several waves and the introduction of vaccination. The empirical study is conducted using cointegration techniques which allows for long and short-run relationships. The obtained results indicate that both daily growth in confirmed cases and deaths have a negative and significant effect on the stock market returns. In particular, this effect differs across sectors. It seems more pronounced in financial, consumer goods and industrials sectors. These findings have important implications for investors to predict the behavior of the stock market or sectors returns and to implement hedging strategies during the COVID-19 pandemic.

Keywords: Tunisian stock market, sectors, COVID-19 pandemic, cointegration techniques

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Authors: Saud Al Mahdi

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Traditionally,portfolio managers have been discouraged from timing the market. This means, for example, that equity managers have been forced to adhere strictly to a benchmark with static or relatively stable components, such as the SP 500 or the Russell 3000. This means that the portfolio’s exposures to all risk factors should mimic as closely as possible the corresponding exposures of the benchmark. The main risk factor, of course, is the market itself. Effectively, a long-only portfolio would be constrained to have a beta 1. More recently, however, managers have been given greater discretion to adjust their portfolio’s risk exposures (in particular, the beta of their portfolio) dynamically to match the manager’s beliefs about future performance of the risk factors themselves. This freedom translates into the manager’s ability to adjust the portfolio’s beta dynamically. These strategies have come to be known as smart beta strategies. Adjusting beta dynamically amounts to attempting to "time" the market; that is, to increase exposure when one anticipates that the market will rise, and to decrease it when one anticipates that the market will fall. Traditionally, market timing has been believed to be impossible to perform effectively and consistently. Moreover, if a majority of market participants do it, their combined actions could destabilize the market. The aim of this project is to investigate so-called smart beta strategies to determine if they really can add value, or if they are merely marketing gimmicks used to sell dubious investment strategies.

Keywords: beta, alpha, active portfolio management, trading strategies

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Authors: Mehdi Nematimoez

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Head posture is paramount to retaining gaze and balance in many activities; its control is thus important in many activities. However, little information is available about the effects of head movement restriction on other spine segment kinematics and movement patterns during lifting and lowering tasks. The aim of this study was to examine the effects of head movement restriction on relative angles and their derivatives using the stepwise segmentation approach during lifting and lowering tasks. Ten healthy men lifted and lowered a box using two styles (stoop and squat), with two loads (i.e., 10 and 20% of body weight); they performed these tasks with two instructed head postures (1. Flexing the neck to keep contact between chin and chest over the task cycle; 2. No instruction, free head posture). The spine was divided into five segments, tracked by six cluster markers (C7, T3, T6, T9, T12, and L5). Relative angles between spine segments and their derivatives (first and second) were analyzed by a stepwise segmentation approach to consider the effect of each segment on the whole spine. Accordingly, head posture significantly affected the derivatives of the relative angles and manifested latency in spine segments movement, i.e., cephalad-to-caudad or caudad-to-cephalad patterns. The relative angles for C7-T3 and T3-T6 increased over the cycle of all lifting and lowering tasks; nevertheless, in lower segments increased significantly when the spine moved into upright standing. However, these effects were clearer during lifting than lowering. Conclusively, the neck flexion can unevenly increase the flexion angles of spine segments from cervical to lumbar over lifting and lowering tasks; furthermore, stepwise segmentation reveals potential for assessing the segmental contribution in spine ROM and movement patterns.

Keywords: head movement restriction, spine kinematics, lifting, lowering, stepwise segmentation

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Authors: Sajid Hussain

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The complex domain approach for image segmentation based on active contour has been designed, which deforms step by step to partition an image into numerous expedient regions. A novel region-based trigonometric complex pressure force function is proposed, which propagates around the region of interest using image forces. The signed trigonometric force function controls the propagation of the active contour and the active contour stops on the exact edges of the object accurately. The proposed model makes the level set function binary and uses Gaussian smoothing kernel to adjust and escape the re-initialization procedure. The working principle of the proposed model is as follows: The real image data is transformed into complex data by iota (i) times of image data and the average iota (i) times of horizontal and vertical components of the gradient of image data is inserted in the proposed model to catch complex gradient of the image data. A simple finite difference mathematical technique has been used to implement the proposed model. The efficiency and robustness of the proposed model have been verified and compared with other state-of-the-art models.

Keywords: image segmentation, active contour, level set, Mumford and Shah model

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Authors: Isabel L. Guidote

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Continued advancements and innovation in the technological arena may yield both beneficial and detrimental effects to market competition in the Philippines. This paper discusses recent developments in the digital sphere which have resulted in improved access to the Philippine market for both producers and consumers. Acknowledging that these developments are likely to disrupt or alter prevailing market conditions, this paper likewise tackles competition theories of harm that may arise as a result of such technological innovations, with reference to cases decided by foreign competition authorities and the European Commission. As the Philippine moves closer to the digital frontier, it is imperative that producers, consumers, and regulators alike be well-equipped to address the risks and challenges posed by these rapid advancements in technology.

Keywords: antitrust, competition law, market competition, technology

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Authors: E. Kharaishvili, M. Chavleishvili, M. Natsvaladze

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The article presents the trends in Georgian wine market development and evaluates the competitive advantages of Georgia to enter the wine market based on its customs, traditions and historical practices combined with modern technologies. In order to analyze the supply of wine, dynamics of vineyard land area and grape varieties are discussed, trends in wine production are presented, trends in export and import are evaluated, local wine market, its micro and macro environments are studied and analyzed based on the interviews with experts and analysis of initial recording materials. For strengthening its position on the international market, the level of competitiveness of Georgian wine is defined, which is evaluated by “ex-ante” and “ex-post” methods, as well as by four basic and two additional factors of the Porter’s diamond method; potential advantages and disadvantages of Georgian wine are revealed. Conclusions are made by identifying the factors that hinder the development of Georgian wine market. Based on the conclusions, relevant recommendations are developed.

Keywords: Georgian wine market, competitive advantage, bio wine, export-import, Porter's diamond model

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Authors: Sidra Naeem, Ayesha Naeem, Sahar Rahim, Nadia Nawaz Qadri

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Citrus greening is a bacterial disease that causes considerable damage to citrus fruits worldwide. Efficient method for this disease detection must be carried out to minimize the production loss. This paper presents a pattern recognition system that comprises three stages for the detection of citrus greening from Orange leaves: segmentation, feature extraction and classification. Image segmentation is accomplished by adaptive thresholding. The feature extraction stage comprises of three visual descriptors i.e. shape, color and texture. From shape feature we have used asymmetry index, from color feature we have used histogram of Cb component from YCbCr domain and from texture feature we have used local binary pattern. Classification was done using support vector machines and k nearest neighbors. The best performances of the system is Accuracy = 88.02% and AUROC = 90.1% was achieved by automatic segmented images. Our experiments validate that: (1). Segmentation is an imperative preprocessing step for computer assisted diagnosis of citrus greening, and (2). The combination of shape, color and texture features form a complementary set towards the identification of citrus greening disease.

Keywords: citrus greening, pattern recognition, feature extraction, classification

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Authors: Hailu Getnet

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This study focus on reverse innovation on performance outcomes across developed and subsistence markets context. The subsistence market consists two third of the world population and the largest international market. To date, it has been neglected because of its issues of perceived challenges and seeming unattractiveness compared to the established markets in the west. However, subsistence markets are becoming source of reverse innovation; an innovation that is likely to be adopted first in developing world and successfully traded globally. In response, there is a growing interest on reverse innovation to power the future. Based on the theories of innovation and growing subsistence market literatures, the study propose drivers and outcomes of reverse innovation, a potential similarities and difference in benefiting and challenging firms and consumers in subsistence and developed markets.

Keywords: reverse innovation, subsistence market, developing world, developed market

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Authors: Hu Ding, Kai Liu, Guoan Tang

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The Chinese Loess Plateau suffers from serious gully erosion induced by natural and human causes. Gully features detection including gully-affected area and its two dimension parameters (length, width, area et al.), is a significant task not only for researchers but also for policy-makers. This study aims at gully-affected area detection in three catchments of Chinese Loess Plateau, which were selected in Changwu, Ansai, and Suide by using unmanned aerial vehicle (UAV). The methodology includes a sequence of UAV data generation, image segmentation, feature calculation and selection, and random forest classification. Two experiments were conducted to investigate the influences of segmentation strategy and feature selection. Results showed that vertical and horizontal root-mean-square errors were below 0.5 and 0.2 m, respectively, which were ideal for the Loess Plateau region. The segmentation strategy adopted in this paper, which considers the topographic information, and optimal parameter combination can improve the segmentation results. Besides, the overall extraction accuracy in Changwu, Ansai, and Suide achieved was 84.62%, 86.46%, and 93.06%, respectively, which indicated that the proposed method for detecting gully-affected area is more objective and effective than traditional methods. This study demonstrated that UAV can bridge the gap between field measurement and satellite-based remote sensing, obtaining a balance in resolution and efficiency for catchment-scale gully erosion research.

Keywords: unmanned aerial vehicle (UAV), object-analysis image analysis, gully erosion, gully-affected area, Loess Plateau, random forest

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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Gliomas are most challenging and aggressive type of tumors which appear in different sizes, locations, and scattered boundaries. CNN is most efficient deep learning approach with outstanding capability of solving image analysis problems. A fully automatic deep learning based 2D-CNN model for brain tumor segmentation is presented in this paper. We used small convolution filters (3 x 3) to make architecture deeper. We increased convolutional layers for efficient learning of complex features from large dataset. We achieved better results by pushing convolutional layers up to 16 layers for HGG model. We achieved reliable and accurate results through fine-tuning among dataset and hyper-parameters. Pre-processing of this model includes generation of brain pipeline, intensity normalization, bias correction and data augmentation. We used the BRATS-2015, and Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.81 for complete, 0.79 for core, 0.80 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, HGG

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Authors: Tamar Lazariashvili

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The paper examines the market of bioproducts in the world and in Georgia. The experience of European countries in the field of production of bioproducts is shown, the level of interest of the population in these products is presented, and the tendency of the demand for them to grow is evaluated. Objectives. The purpose of the research is to identify modern challenges and develop recommendations for development opportunities based on the analysis of the European and local market of organic products. Methodologies. General and specific methods are used in the research process: comparative analysis, induction, deduction. A desk study has been conducted. Findings. It has been revealed that the production of organic products in Georgia is significantly behind the European requirements, in the market of organic products of Georgia there is a formation of a layer of consumers who are in favor of healthy food and are ready to pay a different price. Conclusions. Based on the analysis of the bioproducts market, appropriate recommendations are proposed, namely, the introduction of innovative technologies; financial and legal support by the state; provision of consulting services on the tax system; Elimination of asymmetric information in the market and others.

Keywords: bioproducts market, European experience, production of bioproducts, layer of consumers.

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Authors: Alexander V. Spirov, David M. Holloway, Ekaterina M. Myasnikova

Abstract:

Segmentation of the early Drosophila embryo results from the dynamic establishment of spatial gene expression patterns. Patterning occurs on an embryo geometry which is a 'deformed' prolate ellipsoid, with anteroposterior and dorsal-ventral major and minor axes, respectively. Patterning is largely independent along each axis, but some interaction can be seen in the 'bending' of the segmental expression stripes. This interaction is not well understood. In this report, we investigate how 3D geometrical features of the early embryo affect the segmental expression patterning. Specifically, we study the effect of geometry on formation of the Bicoid primary morphogenetic gradient. Our computational results demonstrate that embryos with a much longer ventral than dorsal surface ('bellied') can produce curved Bicoid concentration contours which could activate curved stripes in the downstream pair-rule segmentation genes. In addition, we show that having an extended source for Bicoid in the anterior of the embryo may be necessary for producing the observed exponential form of the Bicoid gradient along the anteroposterior axis.

Keywords: Drosophila embryo, bicoid morphogenetic gradient, exponential expression profile, expression surface form, segmentation genes, 3D modelling

Procedia PDF Downloads 239

Authors: Tarah Bouaricha

Abstract:

The impact of worst natural disasters is analysed in terms of insured losses which happened between 2010 and 2014 on S&P insurance index. Event study analysis is used to test whether natural disasters impact insurance index stock market price. There is no negative impact on insurance stock market price around the disasters event. To analyse the reaction of insurance stock market, normal returns (NR), abnormal returns (AR), cumulative abnormal returns (CAR), cumulative average abnormal returns (CAAR) and a parametric test on AR and on CAR are used.

Keywords: study event, natural disasters, insurance, reinsurance, stock market

Procedia PDF Downloads 363