Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 160

Search results for: self organizing map

160 Kohonen Self-Organizing Maps as a New Method for Determination of Salt Composition of Multi-Component Solutions

Authors: Sergey A. Burikov, Tatiana A. Dolenko, Kirill A. Gushchin, Sergey A. Dolenko

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The paper presents the results of clusterization by Kohonen self-organizing maps (SOM) applied for analysis of array of Raman spectra of multi-component solutions of inorganic salts, for determination of types of salts present in the solution. It is demonstrated that use of SOM is a promising method for solution of clusterization and classification problems in spectroscopy of multi-component objects, as attributing a pattern to some cluster may be used for recognition of component composition of the object.

Keywords: Kohonen self-organizing maps, clusterization, multi-component solutions, Raman spectroscopy

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159 Optimization of Structures Subjected to Earthquake

Authors: Alireza Lavaei, Alireza Lohrasbi, Mohammadali M. Shahlaei

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To reduce the overall time of structural optimization for earthquake loads two strategies are adopted. In the first strategy, a neural system consisting self-organizing map and radial basis function neural networks, is utilized to predict the time history responses. In this case, the input space is classified by employing a self-organizing map neural network. Then a distinct RBF neural network is trained in each class. In the second strategy, an improved genetic algorithm is employed to find the optimum design. A 72-bar space truss is designed for optimal weight using exact and approximate analysis for the El Centro (S-E 1940) earthquake loading. The numerical results demonstrate the computational advantages and effectiveness of the proposed method.

Keywords: optimization, genetic algorithm, neural networks, self-organizing map

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158 Using Self Organizing Feature Maps for Classification in RGB Images

Authors: Hassan Masoumi, Ahad Salimi, Nazanin Barhemmat, Babak Gholami

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Artificial neural networks have gained a lot of interest as empirical models for their powerful representational capacity, multi input and output mapping characteristics. In fact, most feed-forward networks with nonlinear nodal functions have been proved to be universal approximates. In this paper, we propose a new supervised method for color image classification based on self organizing feature maps (SOFM). This algorithm is based on competitive learning. The method partitions the input space using self-organizing feature maps to introduce the concept of local neighborhoods. Our image classification system entered into RGB image. Experiments with simulated data showed that separability of classes increased when increasing training time. In additional, the result shows proposed algorithms are effective for color image classification.

Keywords: classification, SOFM algorithm, neural network, neighborhood, RGB image

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157 Evaluation of Groundwater Quality and Its Suitability for Drinking and Agricultural Purposes Using Self-Organizing Maps

Authors: L. Belkhiri, L. Mouni, A. Tiri, T.S. Narany

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In the present study, the self-organizing map (SOM) clustering technique was applied to identify homogeneous clusters of hydrochemical parameters in El Milia plain, Algeria, to assess the quality of groundwater for potable and agricultural purposes. The visualization of SOM-analysis indicated that 35 groundwater samples collected in the study area were classified into three clusters, which showed progressive increase in electrical conductivity from cluster one to cluster three. Samples belonging to cluster one are mostly located in the recharge zone showing hard fresh water type, however, water type gradually changed to hard-brackish type in the discharge zone, including clusters two and three. Ionic ratio studies indicated the role of carbonate rock dissolution in increases on groundwater hardness, especially in cluster one. However, evaporation and evapotranspiration are the main processes increasing salinity in cluster two and three.

Keywords: groundwater quality, self-organizing maps, drinking water, irrigation water

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156 Process Monitoring Based on Parameterless Self-Organizing Map

Authors: Young Jae Choung, Seoung Bum Kim

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Statistical Process Control (SPC) is a popular technique for process monitoring. A widely used tool in SPC is a control chart, which is used to detect the abnormal status of a process and maintain the controlled status of the process. Traditional control charts, such as Hotelling’s T2 control chart, are effective techniques to detect abnormal observations and monitor processes. However, many complicated manufacturing systems exhibit nonlinearity because of the different demands of the market. In this case, the unregulated use of a traditional linear modeling approach may not be effective. In reality, many industrial processes contain the nonlinear and time-varying properties because of the fluctuation of process raw materials, slowing shift of the set points, aging of the main process components, seasoning effects, and catalyst deactivation. The use of traditional SPC techniques with time-varying data will degrade the performance of the monitoring scheme. To address these issues, in the present study, we propose a parameterless self-organizing map (PLSOM)-based control chart. The PLSOM-based control chart not only can manage a situation where the distribution or parameter of the target observations changes, but also address the nonlinearity of modern manufacturing systems. The control limits of the proposed PLSOM chart are established by estimating the empirical level of significance on the percentile using a bootstrap method. Experimental results with simulated data and actual process data from a thin-film transistor-liquid crystal display process demonstrated the effectiveness and usefulness of the proposed chart.

Keywords: control chart, parameter-less self-organizing map, self-organizing map, time-varying property

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155 Clustering the Wheat Seeds Using SOM Artificial Neural Networks

Authors: Salah Ghamari

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In this study, the ability of self organizing map artificial (SOM) neural networks in clustering the wheat seeds varieties according to morphological properties of them was considered. The SOM is one type of unsupervised competitive learning. Experimentally, five morphological features of 300 seeds (including three varieties: gaskozhen, Md and sardari) were obtained using image processing technique. The results show that the artificial neural network has a good performance (90.33% accuracy) in classification of the wheat varieties despite of high similarity in them. The highest classification accuracy (100%) was achieved for sardari.

Keywords: artificial neural networks, clustering, self organizing map, wheat variety

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154 Hyperspectral Data Classification Algorithm Based on the Deep Belief and Self-Organizing Neural Network

Authors: Li Qingjian, Li Ke, He Chun, Huang Yong

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In this paper, the method of combining the Pohl Seidman's deep belief network with the self-organizing neural network is proposed to classify the target. This method is mainly aimed at the high nonlinearity of the hyperspectral image, the high sample dimension and the difficulty in designing the classifier. The main feature of original data is extracted by deep belief network. In the process of extracting features, adding known labels samples to fine tune the network, enriching the main characteristics. Then, the extracted feature vectors are classified into the self-organizing neural network. This method can effectively reduce the dimensions of data in the spectrum dimension in the preservation of large amounts of raw data information, to solve the traditional clustering and the long training time when labeled samples less deep learning algorithm for training problems, improve the classification accuracy and robustness. Through the data simulation, the results show that the proposed network structure can get a higher classification precision in the case of a small number of known label samples.

Keywords: DBN, SOM, pattern classification, hyperspectral, data compression

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153 Self-Organizing Maps for Exploration of Partially Observed Data and Imputation of Missing Values in the Context of the Manufacture of Aircraft Engines

Authors: Sara Rejeb, Catherine Duveau, Tabea Rebafka

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To monitor the production process of turbofan aircraft engines, multiple measurements of various geometrical parameters are systematically recorded on manufactured parts. Engine parts are subject to extremely high standards as they can impact the performance of the engine. Therefore, it is essential to analyze these databases to better understand the influence of the different parameters on the engine's performance. Self-organizing maps are unsupervised neural networks which achieve two tasks simultaneously: they visualize high-dimensional data by projection onto a 2-dimensional map and provide clustering of the data. This technique has become very popular for data exploration since it provides easily interpretable results and a meaningful global view of the data. As such, self-organizing maps are usually applied to aircraft engine condition monitoring. As databases in this field are huge and complex, they naturally contain multiple missing entries for various reasons. The classical Kohonen algorithm to compute self-organizing maps is conceived for complete data only. A naive approach to deal with partially observed data consists in deleting items or variables with missing entries. However, this requires a sufficient number of complete individuals to be fairly representative of the population; otherwise, deletion leads to a considerable loss of information. Moreover, deletion can also induce bias in the analysis results. Alternatively, one can first apply a common imputation method to create a complete dataset and then apply the Kohonen algorithm. However, the choice of the imputation method may have a strong impact on the resulting self-organizing map. Our approach is to address simultaneously the two problems of computing a self-organizing map and imputing missing values, as these tasks are not independent. In this work, we propose an extension of self-organizing maps for partially observed data, referred to as missSOM. First, we introduce a criterion to be optimized, that aims at defining simultaneously the best self-organizing map and the best imputations for the missing entries. As such, missSOM is also an imputation method for missing values. To minimize the criterion, we propose an iterative algorithm that alternates the learning of a self-organizing map and the imputation of missing values. Moreover, we develop an accelerated version of the algorithm by entwining the iterations of the Kohonen algorithm with the updates of the imputed values. This method is efficiently implemented in R and will soon be released on CRAN. Compared to the standard Kohonen algorithm, it does not come with any additional cost in terms of computing time. Numerical experiments illustrate that missSOM performs well in terms of both clustering and imputation compared to the state of the art. In particular, it turns out that missSOM is robust to the missingness mechanism, which is in contrast to many imputation methods that are appropriate for only a single mechanism. This is an important property of missSOM as, in practice, the missingness mechanism is often unknown. An application to measurements on one type of part is also provided and shows the practical interest of missSOM.

Keywords: imputation method of missing data, partially observed data, robustness to missingness mechanism, self-organizing maps

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152 Finding the Longest Common Subsequence in Normal DNA and Disease Affected Human DNA Using Self Organizing Map

Authors: G. Tamilpavai, C. Vishnuppriya

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Bioinformatics is an active research area which combines biological matter as well as computer science research. The longest common subsequence (LCSS) is one of the major challenges in various bioinformatics applications. The computation of the LCSS plays a vital role in biomedicine and also it is an essential task in DNA sequence analysis in genetics. It includes wide range of disease diagnosing steps. The objective of this proposed system is to find the longest common subsequence which presents in a normal and various disease affected human DNA sequence using Self Organizing Map (SOM) and LCSS. The human DNA sequence is collected from National Center for Biotechnology Information (NCBI) database. Initially, the human DNA sequence is separated as k-mer using k-mer separation rule. Mean and median values are calculated from each separated k-mer. These calculated values are fed as input to the Self Organizing Map for the purpose of clustering. Then obtained clusters are given to the Longest Common Sub Sequence (LCSS) algorithm for finding common subsequence which presents in every clusters. It returns nx(n-1)/2 subsequence for each cluster where n is number of k-mer in a specific cluster. Experimental outcomes of this proposed system produce the possible number of longest common subsequence of normal and disease affected DNA data. Thus the proposed system will be a good initiative aid for finding disease causing sequence. Finally, performance analysis is carried out for different DNA sequences. The obtained values show that the retrieval of LCSS is done in a shorter time than the existing system.

Keywords: clustering, k-mers, longest common subsequence, SOM

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151 Rule Insertion Technique for Dynamic Cell Structure Neural Network

Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

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This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.

Keywords: neural network, self-organizing map, rule extraction, rule insertion

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150 Problems in Lifelong Education Course in Information and Communication Technology

Authors: Hisham Md.Suhadi, Faaizah Shahbodin, Jamaluddin Hashim, Nurul Huda Mahsudi, Mahathir Mohd Sarjan

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The study is the way to identify the problems that occur in organizing short courses lifelong learning in the information and communication technology (ICT) education which are faced by the lecturer and staff at the Mara Skill Institute and Industrial Training Institute in Pahang, Malaysia. The important aspects of these issues are classified to five which are selecting the courses administrative. Fifty lecturers and staff were selected as a respondent. The sample is selected by using the non-random sampling method purpose sampling. The questionnaire is used as a research instrument and divided into five main parts. All the data that gain from the questionnaire are analyzed by using the SPSS in term of mean, standard deviation and percentage. The findings showed that there are the problems occur in organizing the short course for lifelong learning in ICT education.

Keywords: lifelong Education, information and communication technology, short course, ICT education, courses administrative

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149 Stochastic Programming and C-Somga: Animal Ration Formulation

Authors: Pratiksha Saxena, Dipti Singh, Neha Khanna

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A self-organizing migrating genetic algorithm(C-SOMGA) is developed for animal diet formulation. This paper presents animal diet formulation using stochastic and genetic algorithm. Tri-objective models for cost minimization and shelf life maximization are developed. These objectives are achieved by combination of stochastic programming and C-SOMGA. Stochastic programming is used to introduce nutrient variability for animal diet. Self-organizing migrating genetic algorithm provides exact and quick solution and presents an innovative approach towards successful application of soft computing technique in the area of animal diet formulation.

Keywords: animal feed ration, feed formulation, linear programming, stochastic programming, self-migrating genetic algorithm, C-SOMGA technique, shelf life maximization, cost minimization, nutrient maximization

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148 Self-Organizing Map Network for Wheeled Robot Movement Optimization

Authors: Boguslaw Schreyer

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The paper investigates the application of the Kohonen’s Self-Organizing Map (SOM) to the wheeled robot starting and braking dynamic states. In securing wheeled robot stability as well as minimum starting and braking time, it is important to ensure correct torque distribution as well as proper slope of braking and driving moments. In this paper, a correct movement distribution has been formulated, securing optimum adhesion coefficient and good transversal stability of a wheeled robot. A neural tuner has been proposed to secure the above properties, although most of the attention is attached to the SOM network application. If the delay of the torque application or torque release is not negligible, it is important to change the rising and falling slopes of the torque. The road/surface condition is also paramount in robot dynamic states control. As the road conditions may randomly change in time, application of the SOM network has been suggested in order to classify the actual road conditions.

Keywords: slip control, SOM network, torque distribution, wheeled Robot

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147 A Geospatial Consumer Marketing Campaign Optimization Strategy: Case of Fuzzy Approach in Nigeria Mobile Market

Authors: Adeolu O. Dairo

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Getting the consumer marketing strategy right is a crucial and complex task for firms with a large customer base such as mobile operators in a competitive mobile market. While empirical studies have made efforts to identify key constructs, no geospatial model has been developed to comprehensively assess the viability and interdependency of ground realities regarding the customer, competition, channel and the network quality of mobile operators. With this research, a geo-analytic framework is proposed for strategy formulation and allocation for mobile operators. Firstly, a fuzzy analytic network using a self-organizing feature map clustering technique based on inputs from managers and literature, which depicts the interrelationships amongst ground realities is developed. The model is tested with a mobile operator in the Nigeria mobile market. As a result, a customer-centric geospatial and visualization solution is developed. This provides a consolidated and integrated insight that serves as a transparent, logical and practical guide for strategic, tactical and operational decision making.

Keywords: geospatial, geo-analytics, self-organizing map, customer-centric

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146 Self-Regulation in Composition Writing: The Case of Variation of Self-Regulation Dispositions in Opinion Essay and Technical Writing

Authors: Dave Kenneth Tayao Cayado, Carlo P. Magno, Venice Cristine Dangaran

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The present study determines whether there will be differences in the self-regulation dispositions that learners utilize when writing different types of composition. There were 7 self-regulation factors that were used to develop a scale in this study such as memory strategy, goal setting, self-evaluation, seeking assistance, learning responsibility, environmental structuring, and organizing. The scale was made specific for writing a composition. The researcher-made scale was administered to 150 participants who all came from a university in the Philippines. The participants were asked to write two compositions namely opinion essay and research introduction/review of related literature. The zero-order correlation revealed that all the factors of self-regulation are correlated with one another. However, only seeking assistance and self-evaluation are correlated with opinion essay and technical writing is not correlated to any of the self-regulation factors. However, when path analysis was used, it was shown that seeking assistance can predict opinion essay scores whereas memory strategy, self-evaluation, and organizing can predict technical writing scores.

Keywords: opinion essay, self-regulation, technical writing, writing skills

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145 Application of Latent Class Analysis and Self-Organizing Maps for the Prediction of Treatment Outcomes for Chronic Fatigue Syndrome

Authors: Ben Clapperton, Daniel Stahl, Kimberley Goldsmith, Trudie Chalder

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Chronic fatigue syndrome (CFS) is a condition characterised by chronic disabling fatigue and other symptoms that currently can't be explained by any underlying medical condition. Although clinical trials support the effectiveness of cognitive behaviour therapy (CBT), the success rate for individual patients is modest. Patients vary in their response and little is known which factors predict or moderate treatment outcomes. The aim of the project is to develop a prediction model from baseline characteristics of patients, such as demographics, clinical and psychological variables, which may predict likely treatment outcome and provide guidance for clinical decision making and help clinicians to recommend the best treatment. The project is aimed at identifying subgroups of patients with similar baseline characteristics that are predictive of treatment effects using modern cluster analyses and data mining machine learning algorithms. The characteristics of these groups will then be used to inform the types of individuals who benefit from a specific treatment. In addition, results will provide a better understanding of for whom the treatment works. The suitability of different clustering methods to identify subgroups and their response to different treatments of CFS patients is compared.

Keywords: chronic fatigue syndrome, latent class analysis, prediction modelling, self-organizing maps

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144 Corporate Governance of State-Owned Enterprises: A Comparative Analysis

Authors: Adeyemi Adebayo, Barry Ackers

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This paper comparatively analyses the corporate governance of SOEs in South Africa and Singapore in the context of the World Bank’s framework for corporate governance of SOEs. This framework ensured that the analysis holistically covered key aspects of corporate governance of SOEs in these states. In order to ground our understanding of the paths taken by SOEs in the states, the paper presents the evolution and reforms of SOEs in the states before analyzing key aspects of their corporate governance. The analysis shows that even though SOEs in South Africa and Singapore are comparable in a number of ways, there are notable differences. In this context, this paper finds that the main difference between corporate governance of SOEs in South Africa and Singapore is their organizing model. Further, the analysis, among other findings, shows that SOEs Boards in Singapore are better remunerated. Further finding reveals that, even though some board members are politically connected, Singaporean SOEs boards are better constituted based on skills and experience compared to SOEs boards in South Africa. Overall, the analysis opens up new debates and as such concludes by providing avenues for further research.

Keywords: corporate governance, comparative corporate governance, corporate governance framework, government business enterprises, government linked companies, organizing models, ownership models, state-owned companies, state-owned enterprises

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143 A Comparative Study of Innovative Regions in the World Based on the Theory of Innovation Ecosystem: Cases of the Silicon Valley, Cambridge, Tsukuba and Zhongguancun

Authors: Xinlan Zhang, Dandong Ge, Bingying Liu, Haoyang Liang

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With the rapid development of technology and urbanization, innovation has become an important driving force for urban development. Since the late 20th Century, a number of cities and regions have emerged in the world with innovation as the main driving force, and many of them are still the most important innovation centers in the world. Based on the perspective of innovation ecosystem theory, this paper compares Silicon Valley in the United States, Cambridge in the United Kingdom, Tsukuba in Japan and Zhongguancun in China to explore the reasons for the success of innovative regions and their respective characteristics, hoping to provide a reference for the development of other innovative cities. The main conclusions of this study are the following; firstly, different countries have different social backgrounds. The development model of innovative regions is closely related to the regional backgrounds. Secondly, the market force and the government power have important significance for the development of the innovation regions. The influence of the government power in the early stage of development is great, and in the latter stage, development is dominated by the market force. In addition, the self-organizing ability of the region has a great impact on the innovation ability of the region. Strong self-organizing ability is conducive to the development of innovation economy.

Keywords: contrastive study, development model, innovation ecosystem, innovative regions

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142 Development of a Context Specific Planning Model for Achieving a Sustainable Urban City

Authors: Jothilakshmy Nagammal

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This research paper deals with the different case studies, where the Form-Based Codes are adopted in general and the different implementation methods in particular are discussed to develop a method for formulating a new planning model. The organizing principle of the Form-Based Codes, the transect is used to zone the city into various context specific transects. An approach is adopted to develop the new planning model, city Specific Planning Model (CSPM), as a tool to achieve sustainability for any city in general. A case study comparison method in terms of the planning tools used, the code process adopted and the various control regulations implemented in thirty two different cities are done. The analysis shows that there are a variety of ways to implement form-based zoning concepts: Specific plans, a parallel or optional form-based code, transect-based code /smart code, required form-based standards or design guidelines. The case studies describe the positive and negative results from based zoning, Where it is implemented. From the different case studies on the method of the FBC, it is understood that the scale for formulating the Form-Based Code varies from parts of the city to the whole city. The regulating plan is prepared with the organizing principle as the transect in most of the cases. The various implementation methods adopted in these case studies for the formulation of Form-Based Codes are special districts like the Transit Oriented Development (TOD), traditional Neighbourhood Development (TND), specific plan and Street based. The implementation methods vary from mandatory, integrated and floating. To attain sustainability the research takes the approach of developing a regulating plan, using the transect as the organizing principle for the entire area of the city in general in formulating the Form-Based Codes for the selected Special Districts in the study area in specific, street based. Planning is most powerful when it is embedded in the broader context of systemic change and improvement. Systemic is best thought of as holistic, contextualized and stake holder-owned, While systematic can be thought of more as linear, generalisable, and typically top-down or expert driven. The systemic approach is a process that is based on the system theory and system design principles, which are too often ill understood by the general population and policy makers. The system theory embraces the importance of a global perspective, multiple components, interdependencies and interconnections in any system. In addition, the recognition that a change in one part of a system necessarily alters the rest of the system is a cornerstone of the system theory. The proposed regulating plan taking the transect as an organizing principle and Form-Based Codes to achieve sustainability of the city has to be a hybrid code, which is to be integrated within the existing system - A Systemic Approach with a Systematic Process. This approach of introducing a few form based zones into a conventional code could be effective in the phased replacement of an existing code. It could also be an effective way of responding to the near-term pressure of physical change in “sensitive” areas of the community. With this approach and method the new Context Specific Planning Model is created towards achieving sustainability is explained in detail this research paper.

Keywords: context based planning model, form based code, transect, systemic approach

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141 Innovative Design Considerations for Adaptive Spacecraft

Authors: K. Parandhama Gowd

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Space technologies have changed the way we live in the present day society and manage many aspects of our daily affairs through Remote sensing, Navigation & Communications. Further, defense and military usage of spacecraft has increased tremendously along with civilian purposes. The number of satellites deployed in space in Low Earth Orbit (LEO), Medium Earth Orbit (MEO), and the Geostationary Orbit (GEO) has gone up. The dependency on remote sensing and operational capabilities are most invariably to be exploited more and more in future. Every country is acquiring spacecraft in one way or other for their daily needs, and spacecraft numbers are likely to increase significantly and create spacecraft traffic problems. The aim of this research paper is to propose innovative design concepts for adaptive spacecraft. The main idea here is to improve existing design methods of spacecraft design and development to further improve upon design considerations for futuristic adaptive spacecraft with inbuilt features for automatic adaptability and self-protection. In other words, the innovative design considerations proposed here are to have future spacecraft with self-organizing capabilities for orbital control and protection from anti-satellite weapons (ASAT). Here, an attempt is made to propose design and develop futuristic spacecraft for 2030 and beyond due to tremendous advancements in VVLSI, miniaturization, and nano antenna array technologies, including nano technologies are expected.

Keywords: satellites, low earth orbit (LEO), medium earth orbit (MEO), geostationary earth orbit (GEO), self-organizing control system, anti-satellite weapons (ASAT), orbital control, radar warning receiver, missile warning receiver, laser warning receiver, attitude and orbit control systems (AOCS), command and data handling (CDH)

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140 Grassroots Feminist Organizing in the Shadow of State Feminism in Ethiopia

Authors: Tina Beyene

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In this paper examines the state of grassroots feminist activism in the backdrop of state feminism in Ethiopia. Specifically, I examine the impact of the Charities and Societies Proclamation (aka CSO law), a 2009 law that banned so-called foreign NGOs—i.e., those receiving more than 10% of its operating budget from non-local sources— from working in the areas of human rights, democracy, governance, and gender equality. Viewed as government retribution for the NGO opposition to the government in the 2005 elections, the law aimed to halt the work groups such as the Ethiopian Women Lawyers Association (EWLA), who were defined as a “foreign” NGO. Based on interviews with prominent Ethiopian women’s rights leaders in Addis Ababa, Ethiopia, I assess how grassroots feminist organizing adapts to state suppression on the one hand, and the aggressive entry of the state into women’s rights work on the other hand. While the 2009 law has slowed down the work of women’s rights activism, displaced feminists view feminist advocacy as cyclical and the state as neither fully adversarial nor an ally but rather as an instable entity that at times provides political openings to push ambitious feminist agendas. Grassroots activists are regrouping and developing new political responses strategies such as coding rights issues to fit state mandate; dissembling rights work in permissible social provision language; rechanneling political work into informal spaces and unregistered social clubs; innovating new funding partnerships, and reassembling as privately held research and advocacy companies. my study reveals how grassroots feminist politics operates in the shadow of a hostile state and within the confines of local politics.

Keywords: grassroots feminism, ethiopian feminism, civil society and gender, state feminism

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139 Managment Skills and Values of School Aministrator Public Secondary School Division of Leyte Area IV: Enchancement Model

Authors: Jenney Perez Bacalla

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The study was conducted to assess the five (5) identified school administrators of the identified secondary schools in terms of professional characteristics, management skills and values patterns in the Division of Leyte Area IV for a proposed enhancement model for school administrators. The study utilized the qualitative method. There were two (2) groups of respondents: the teachers and the school administrators. The teachers perceived the management skills of the school administrators in their technical and conceptual skills and values in planning and organizing work, allocating and using of funds, submitting reports, decision-making, leading people, public relations and community involvement and other value development. It was found out in the study that most of the school administrators’ management skills were very well manifested. Their value patterns were also very well manifested. Most of them had earned master’s degree and with a unit in doctoral and five (5) years and above in service as a school administrator. Most administrators were performing and successfully execute the planning, organizing and utilizing funds and they were able to lead their subordinates. In planning, it shows that administrators studied the future and arrange the plan. Administrators also were able to manage, maintained the good environment wherein individual work together. School administrators were creating an environment conducive to learning. The school administrator is manifesting the desirable practices in school management. In terms of their educational qualifications, they were all qualified. Academic preparation, trainings and maturation were their attributes to the development of managerial skills of the school administrators. They showed competence in the areas of management skills that they were able to carry their functions with utmost responsibility and capability. School administrators in terms of seminars and trainings on administration and supervision were already equipped. It is concluded that the school administrators possessed the necessary skills and work values in administering the school.

Keywords: management skills and values, public secondary schools, qualitative, school administrators

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138 Gathering Space after Disaster: Understanding the Communicative and Collective Dimensions of Resilience through Field Research across Time in Hurricane Impacted Regions of the United States

Authors: Jack L. Harris, Marya L. Doerfel, Hyunsook Youn, Minkyung Kim, Kautuki Sunil Jariwala

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Organizational resilience refers to the ability to sustain business or general work functioning despite wide-scale interruptions. We focus on organization and businesses as a pillar of their communities and how they attempt to sustain work when a natural disaster impacts their surrounding regions and economies. While it may be more common to think of resilience as a trait possessed by an organization, an emerging area of research recognizes that for organizations and businesses, resilience is a set of processes that are constituted through communication, social networks, and organizing. Indeed, five processes, robustness, rapidity, resourcefulness, redundancy, and external availability through social media have been identified as critical to organizational resilience. These organizing mechanisms involve multi-level coordination, where individuals intersect with groups, organizations, and communities. Because the nature of such interactions are often networks of people and organizations coordinating material resources, information, and support, they necessarily require some way to coordinate despite being displaced. Little is known, however, if physical and digital spaces can substitute one for the other. We thus are guided by the question, is digital space sufficient when disaster creates a scarcity of physical space? This study presents a cross-case comparison based on field research from four different regions of the United States that were impacted by Hurricanes Katrina (2005), Sandy (2012), Maria (2017), and Harvey (2017). These four cases are used to extend the science of resilience by examining multi-level processes enacted by individuals, communities, and organizations that together, contribute to the resilience of disaster-struck organizations, businesses, and their communities. Using field research about organizations and businesses impacted by the four hurricanes, we code data from interviews, participant observations, field notes, and document analysis drawn from New Orleans (post-Katrina), coastal New Jersey (post-Sandy), Houston Texas (post-Harvey), and the lower keys of Florida (post-Maria). This paper identifies an additional organizing mechanism, networked gathering spaces, where citizens and organizations, alike, coordinate and facilitate information sharing, material resource distribution, and social support. Findings show that digital space, alone, is not a sufficient substitute to effectively sustain organizational resilience during a disaster. Because the data are qualitative, we expand on this finding with specific ways in which organizations and the people who lead them worked around the problem of scarce space. We propose that gatherings after disaster are a sixth mechanism that contributes to organizational resilience.

Keywords: communication, coordination, disaster management, information and communication technologies, interorganizational relationships, resilience, work

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137 A Case Study of An Artist Diagnosed with Schizophrenia-Using the Graphic Rorschach (Digital version) “GRD”

Authors: Maiko Kiyohara, Toshiki Ito

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In this study, we used a psychotherapy process for patient with dissociative disorder and the graphic Rorschach (Digital version) (GRD). A dissociative disorder is a type of dissociation characterized by multiple alternating personalities (also called alternate identity or another identity). "dissociation" is a state in which consciousness, memory, thinking, emotion, perception, behavior, body image, and so on are divided and experienced. Dissociation symptoms, such as lack of memory, are seen, and the repetition of blanks in daily events causes serious problems in life. Although the pathological mechanism of dissociation has not yet been fully elucidated, it is said that it is caused by childhood abuse or shocking trauma. In case of Japan, no reliable data has been reported on the number of patients and prevalence of dissociative disorders, no drug is compatible with dissociation symptoms, and no clear treatment has been established. GRD is a method that the author revised in 2017 to a Graphic Rorschach, which is a special technique for subjects to draw language responses when enforce Rorschach. GRD reduces the burden on both the subject and the examiner, reduces the complexity of organizing data, improves the simplicity of organizing data, and improves the accuracy of interpretation by introducing a tablet computer during the drawing reaction. We are conducting research for the purpose. The patient in this case is a woman in her 50s, and has multiple personalities since childhood. At present, there are about 10 personalities whose main personality is just grasped. The patients is raising her junior high school sons as single parent, but personal changes often occur at home, which makes the home environment inferior and economically oppressive, and has severely hindered daily life. In psychotherapy, while a personality different from the main personality has appeared, I have also conducted psychotherapy with her son. In this case, the psychotherapy process and the GRD were performed to understand the personality characteristics, and the possibility of therapeutic significance to personality integration is reported.

Keywords: GRD, dissociative disorder, a case study of psychotherapy process, dissociation

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136 Classification of Forest Types Using Remote Sensing and Self-Organizing Maps

Authors: Wanderson Goncalves e Goncalves, José Alberto Silva de Sá

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Human actions are a threat to the balance and conservation of the Amazon forest. Therefore the environmental monitoring services play an important role as the preservation and maintenance of this environment. This study classified forest types using data from a forest inventory provided by the 'Florestal e da Biodiversidade do Estado do Pará' (IDEFLOR-BIO), located between the municipalities of Santarém, Juruti and Aveiro, in the state of Pará, Brazil, covering an area approximately of 600,000 hectares, Bands 3, 4 and 5 of the TM-Landsat satellite image, and Self - Organizing Maps. The information from the satellite images was extracted using QGIS software 2.8.1 Wien and was used as a database for training the neural network. The midpoints of each sample of forest inventory have been linked to images. Later the Digital Numbers of the pixels have been extracted, composing the database that fed the training process and testing of the classifier. The neural network was trained to classify two forest types: Rain Forest of Lowland Emerging Canopy (Dbe) and Rain Forest of Lowland Emerging Canopy plus Open with palm trees (Dbe + Abp) in the Mamuru Arapiuns glebes of Pará State, and the number of examples in the training data set was 400, 200 examples for each class (Dbe and Dbe + Abp), and the size of the test data set was 100, with 50 examples for each class (Dbe and Dbe + Abp). Therefore, total mass of data consisted of 500 examples. The classifier was compiled in Orange Data Mining 2.7 Software and was evaluated in terms of the confusion matrix indicators. The results of the classifier were considered satisfactory, and being obtained values of the global accuracy equal to 89% and Kappa coefficient equal to 78% and F1 score equal to 0,88. It evaluated also the efficiency of the classifier by the ROC plot (receiver operating characteristics), obtaining results close to ideal ratings, showing it to be a very good classifier, and demonstrating the potential of this methodology to provide ecosystem services, particularly in anthropogenic areas in the Amazon.

Keywords: artificial neural network, computational intelligence, pattern recognition, unsupervised learning

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135 The Study on Tourist’s Satisfaction in Xinshe Flowers Festival

Authors: Yashan Liu, Yu-Chen Chien

Abstract:

In the past few years, a global trend to hold sightseeing festivals has prevailed. For the purpose of attracting more tourists, the Taiwan government has not only organized a considerable number of international activities, but also provided guidance to counties and cities in organizing festivals which reflect a collaboration of culture and humanity. These festivals have also assisted in the development of local industry and the promotion of their unique characteristics. The purpose of this research is to analyze the influences and relationships between tourist satisfaction and the revisiting willingness of visitors at the Xin-she Flower Festival.

Keywords: Flowers Festival in Xin-she, Tourist Satisfaction, Festival, Revisiting Willingness

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134 Using Blackboard to Enhance Academic Writing Classes

Authors: Laurence Craven

Abstract:

Academic writing is one of the most important class a freshman will take, as it provides the skill needed to formulate an academic essay in any discipline. Written assignments are the most common form of assessment in higher education and thus it is of paramount importance for students to master the skill of academic writing. This presentation aims to give practitioners multiple ways to enhance their academic writing classes using the Blackboard environment, with a view to improving student performance. The presentation will include ways to improve assessment and give corrective feedback. It will also provide ideas on how to increase variety in teaching lessons, assigning homework and on organizing materials.

Keywords: academic writing, assessment, e-learning, technology

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133 Detonating Culture, Statistic and Developmenet in Imo State of Nigeria

Authors: Ejikeme Ugiri

Abstract:

In an executive summary, UNESCO describes Framework for Cultural Statistics as a tool for organizing cultural statistics both nationally and internationally. This is based on conceptual foundation and a common understanding of culture that will enable the measurement of a wide range of cultural expressions. This means therefore that cultural expression in whatever guise has the potentiality of contributing reasonably to the development of a given society. The paper looked into the various tangible and intangible cultures in Imo State of Nigeria. Due to government’s insensitivity, there is need to remind ourselves of the need to pay adequate attention to the cultural heritage bequeathed to us by our forefathers for the sake of posterity. Documenting this information in written form therefore becomes imperative. The study concludes that culture if developed, could reasonably contribute to economic and social growth of the society.

Keywords: culture, detonation, development, statistics

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132 GynApp: A Mobile Application for the Organization and Control of Gynecological Studies

Authors: Betzabet García-Mendoza, Rocío Abascal-Mena

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Breast and cervical cancer are among the leading causes of death of women in Mexico. The mortality rate for these diseases is alarming, even though there have been many campaigns for making people self-aware of the importance of conducting gynecological studies for a timely prevention and detection, these have not been enough. This paper presents a mobile application for organizing and controlling gynecological studies in order to help and boost women to take care of their bodies and health. The process of analyzing and designing the mobile application is presented, along with all the steps carried out by following a user-centered design methodology.

Keywords: breast cancer, cervical cancer, gynecological mobile application, paper prototyping, storyboard, women health

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131 Sustainable Model of Outreach Eye Camps: A Case Study from Reputed Eye Hospital of Central India

Authors: Subramanyam Devarakonda Hanumantharao, Udayendu Prakash Sharma, Mahesh Garg

Abstract:

Introduction: Gomabai Netralaya a reputed eye hospital is located in Neemuch a small city of Madhya Pradesh, India. The hospital is established in 1992 by Late. G.D Agrawal a renowned educationist, freedom fighter and philanthropist. The eye hospital was established to serve all sections of the society in affordable manner. To provide comprehensive eye care services to the rural poor the hospital started organizing outreach camps since 1994. Purpose: To study the cost effectiveness of outreach eye camps for addressing the sustainability issues of the outreach program. Methods: One year statistics of outreach eye camps were collected from Hospital Management Information System software to analyze the productivity of camps. Income and expenses report was collected from outreach department records to analyze per camp expenses and per patient expenses against the income generated. All current year records were analyzed to have accuracy of information and results. Information was collected in two ways: 1)Actual camp performance records and expenses from book of accounts. 2)Cross verification was done through one to one discussion with outreach staff. Results: Total 17534 outpatients were examined through 52 outreach eye camps. Total 6042 (34% of total outpatients) patients were advised with cataracts and 4651 (77% of advice) operations were performed. The average OPD per camp was 337 and per camp 116 patients was advised for cataract surgery and 89 surgeries were performed per camp. Total 18200 US$ incurred on organizing 52 outreach camps in the radius of 100 k.ms. Considering the total outpatients screened through camps the screening cost per patient was 1.00 US$ and considering the surgical output the per surgery expenses was 4.00 US$. The cost recovery of the total expenses was through Government grant of US$ 16.00 per surgery (that includes surgical grant). All logistics cost of camps and patients transportation cost was taken care by local donors. Conclusion: The present study demonstrates that with people’s participation, successful high volume outreach eye camps can be organized. The cost effectiveness of the outreach camps is totally depended on volume of outpatient’s turn-up at camp site and per camp surgical output. The only solution to sustainability of outreach eye camps is sharing of cost with local donors and increasing productivity.

Keywords: camps, outreach, productivity, sustainable

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