Search results for: fuzzy rules

Authors: G. V. Siva Krishna Rao, B. Srinivasa Rao

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Electrical energy is vital in every aspect of day-to-day life. Keen interest is taken on all possible sources of energy from which it can be generated and this led to the encouragement of generating electrical power using renewable energy resources such as solar, tidal waves and wind energy. Due to the increasing interest on renewable sources in recent times, the studies on integration of distributed generation to the power grid have rapidly increased. Distributed Generation (DG) is a promising solution to many power system problems such as voltage regulation, power loss and reduction in operational cost, etc. To reduce production cost, it is important to minimize the losses by determining the location and size of local generators to be placed in the radial distribution systems. In this paper, reduction of production cost by optimal size of DG unit operated at optimal power factor is dealt. The optimal size of the DG unit is calculated analytically using approximate reasoning suitable nodes and DG placement to minimize production cost with minimum loss is determined by fuzzy technique. Total Cost of Power generation is compared with and without DG unit for 1 year duration. The suggested method is programmed under MATLAB software and is tested on IEEE 33 bus system and the results are presented.

Keywords: distributed generation, operational cost, exact loss formula, optimum size, optimum location

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Authors: Vladimir A. Todiras

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Spatio-temporal models provide new possibilities for real-time action in pest risk analysis. It should be noted that estimation of the possibility and probability of introduction of a pest and of its economic consequences involves many uncertainties. We present a new mapping technique that assesses pest invasion risk using online BioClass software. BioClass is a GIS tool designed to solve multiple-criteria classification and optimization problems based on fuzzy logic and level set methods. This research describes a method for predicting the potential establishment and spread of a plant pest into new areas using a case study: corn rootworm (Diabrotica spp.), tomato leaf miner (Tuta absoluta) and plum fruit moth (Grapholita funebrana). Our study demonstrated that in BioClass we can combine fuzzy logic and geographic information systems with knowledge of pest biology and environmental data to derive new information for decision making. Pests are sensitive to a warming climate, as temperature greatly affects their survival and reproductive rate and capacity. Changes have been observed in the distribution, frequency and severity of outbreaks of Helicoverpa armigera on tomato. BioClass has demonstrated to be a powerful tool for applying dynamic models and map the potential future distribution of a species, enable resource to make decisions about dangerous and invasive species management and control.

Keywords: classification, model, pest, risk

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Authors: Yeonjeong Lee, Kyoung-jae Kim, Youngtae Kim

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This study proposes a novel recommender system that uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user’s preference. The proposed model consists of two steps. In the first step, this study uses logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. Then, this study combines the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. In the second step, this study uses the market basket analysis to extract association rules for co-purchased products. Finally, the system selects customers who have high likelihood to purchase products in each product group and recommends proper products from same or different product groups to them through above two steps. We test the usability of the proposed system by using prototype and real-world transaction and profile data. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The results also show that the proposed system may be useful in real-world online shopping store.

Keywords: product recommender system, ensemble technique, association rules, decision tree, artificial neural networks

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Authors: Meenakshi Barsaul Chauhan, Aastha Chauhan, Shilpa Hurmade, Rajeev Sen, Jyotsna Sen, Monika Dalal

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Introduction: Ovarian masses are common forms of neoplasm in women and represent 2/3rd of gynaecological malignancies. A pre-operative suggestion of malignancy can guide the gynecologist to refer women with suspected pelvic mass to a gynecological oncologist for appropriate therapy and optimized treatment, which can improve survival. In the younger age group preoperative differentiation into benign or malignant pathology can decide for conservative or radical surgery. Imaging modalities have a definite role in establishing the diagnosis. By using International Ovarian Tumor Analysis (IOTA) classification with sonography, costly radiological methods like Magnetic Resonance Imaging (MRI) / computed tomography (CT) scan can be reduced, especially in developing countries like India. Thus, this study is being undertaken to evaluate the role of clinical methods and sonography for diagnosis of the nature of the ovarian tumor. Material And Methods: This prospective observational study was conducted on 40 patients presenting with ovarian masses, in the Department of Obstetrics and Gynaecology, at a tertiary care center in northern India. Functional cysts were excluded. Ultrasonography and color Doppler were performed on all the cases.IOTA rules were applied, which take into account locularity, size, presence of solid components, acoustic shadow, dopper flow etc . Magnetic Resonance Imaging (MRI) / computed tomography (CT) scans abdomen and pelvis were done in cases where sonography was inconclusive. In inoperable cases, Fine needle aspiration cytology (FNAC) was done. The histopathology report after surgery and cytology report after FNAC was correlated statistically with the pre-operative diagnosis made clinically and sonographically using IOTA rules. Statistical Analysis: Descriptive measures were analyzed by using mean and standard deviation and the Student t-test was applied and the proportion was analyzed by applying the chi-square test. Inferential measures were analyzed by sensitivity, specificity, negative predictive value, and positive predictive value. Results: Provisional diagnosis of the benign tumor was made in 16(42.5%) and of the malignant tumor was made in 24(57.5%) patients on the basis of clinical findings. With IOTA simple rules on sonography, 15(37.5%) were found to be benign, while 23 (57.5%) were found to be malignant and findings were inconclusive in 2 patients (5%). FNAC/Histopathology reported that benign ovarian tumors were 14 (35%) and 26(65%) were malignant, which was taken as the gold standard. The clinical finding alone was found to have a sensitivity of 66.6% and a specificity of 90.9%. USG alone had a sensitivity of 86% and a specificity of 80%. When clinical findings and IOTA simple rules of sonography were combined (excluding inconclusive masses), the sensitivity and specificity were 83.3% and 92.3%, respectively. While including inconclusive masses, sensitivity came out to be 91.6% and specificity was 89.2. Conclusion: IOTA's simple sonography rules are highly sensitive and specific in the prediction of ovarian malignancy and also easy to use and easily reproducible. Thus, combining clinical examination with USG will help in the better management of patients in terms of time, cost and better prognosis. This will also avoid the need for costlier modalities like CT, and MRI.

Keywords: benign, international ovarian tumor analysis classification, malignant, ovarian tumours, sonography

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Authors: Adewale O. Ogunde, Olusegun Folorunso, Adesina S. Sodiya

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Most existing Distributed Association Rule Mining (DARM) systems are still facing several challenges. One of such challenges that have not received the attention of many researchers is the inability of existing systems to adapt to constantly changing databases and mining environments. In this work, an Adaptive Incremental Mining Algorithm (AIMA) is therefore proposed to address these problems. AIMA employed multiple mobile agents for the entire mining process. AIMA was designed to adapt to changes in the distributed databases by mining only the incremental database updates and using this to update the existing rules in order to improve the overall response time of the DARM system. In AIMA, global association rules were integrated incrementally from one data site to another through Results Integration Coordinating Agents. The mining agents in AIMA were made adaptive by defining mining goals with reasoning and behavioral capabilities and protocols that enabled them to either maintain or change their goals. AIMA employed Java Agent Development Environment Extension for designing the internal agents’ architecture. Results from experiments conducted on real datasets showed that the adaptive system, AIMA performed better than the non-adaptive systems with lower communication costs and higher task completion rates.

Keywords: adaptivity, data mining, distributed association rule mining, incremental mining, mobile agents

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Authors: Tapas Acharya, Monalisa Mitra

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Overlay modeling is the most widely used conventional analysis for spatial decision support system. Overlay modeling requires a set of themes with different weightage computed in varied manners, which gives a resultant input for further integrated analysis. In spite of the popularity and most widely used technique; it gives inconsistent and erroneous results for similar inputs while processed in various GIS overlay techniques. This study is an attempt to compare and analyse the differences in the outputs of different overlay methods using GIS platform with same set of themes of the Precambrian metamorphic to obtain groundwater prospecting in Precambrian metamorphic rocks. The objective of the study is to emphasize the most suitable overlay method for groundwater prospecting in older Precambrian metamorphics. Seven input thematic layers like slope, Digital Elevation Model (DEM), soil thickness, lineament intersection density, average groundwater table fluctuation, stream density and lithology have been used in the spatial overlay models of fuzzy overlay, weighted overlay and weighted sum overlay methods to yield the suitable groundwater prospective zones. Spatial concurrence analysis with high yielding wells of the study area and the statistical comparative studies among the outputs of various overlay models using RStudio reveal that the Weighted Overlay model is the most efficient GIS overlay model to delineate the groundwater prospecting zones in the Precambrian metamorphic rocks.

Keywords: fuzzy overlay, GIS overlay model, groundwater prospecting, Precambrian metamorphics, weighted overlay, weighted sum overlay

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Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy

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Recently, an increasing number of researchers have been focusing on working out realistic solutions to sustainability problems. As sustainability issues gain higher importance for organisations, the management of such decisions becomes critical. Knowledge representation is a fundamental issue of complex knowledge based systems. Many types of sustainability problems would benefit from models based on experts’ knowledge. Cognitive maps have been used for analyzing and aiding decision making. A cognitive map can be made of almost any system or problem. A fuzzy cognitive map (FCM) can successfully represent knowledge and human experience, introducing concepts to represent the essential elements and the cause and effect relationships among the concepts to model the behavior of any system. Integrated waste management systems (IWMS) are complex systems that can be decomposed to non-related and related subsystems and elements, where many factors have to be taken into consideration that may be complementary, contradictory, and competitive; these factors influence each other and determine the overall decision process of the system. The goal of the present paper is to construct an efficient IWMS which considers various factors. The authors’ intention is to propose an expert based system design approach for implementing expert decision support in the area of IWMSs and introduces an appropriate methodology for the development and analysis of group FCM. A framework for such a methodology consisting of the development and application phases is presented.

Keywords: factors, fuzzy cognitive map, group decision, integrated waste management system

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Authors: Bubaker F. Shareia

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The aim of this paper is to determine a general frame of the auditor's legal responsibilities in Libya which were implied in professional codes and rules, these codes and rules were concerned with the auditor's rights and duties in conducting his professional duties. This will provide a background for the Libyan accounting profession, and the challenges in tailoring Auditors to meet third party's needs. Being informed of the kinds of legal responsibilities which the external auditors could face during conducting their duties. The study is based on a literature review and archival research, reinforced by a qualitative case study comprised of interviews, questionnaire and a study of internal documents. To reach such an understanding, the researcher designed two questionnaires for collecting the data. One questionnaire was distributed among the certified public accountant firms in Libya and the second was distributed among a group of randomly selected lawyers and judges in the same country. Most auditors agreed upon the determination of their responsibilities toward the state and they emphasized that their responsibilities toward their clients were limited to the accepted standards of auditing. Moreover, all auditors who were surveyed emphasized that there has never been any juridical claims against them, and as a consequence they have never paid any legal fines. This study focuses on one country, which does limit its generalisability. However, it also suggests fruitful research areas in considering the impact and challenge of the historic factors in the accounting profession in emerging economies.

Keywords: accounting, external auditor, legal responsibilities, libyan accounting profession

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Authors: Bidzina Matsaberidze, Anna Sikharulidze, Gia Sirbiladze, Bezhan Ghvaberidze

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In the modern world emergency management decision support systems are actively used by state organizations, which are interested in extreme and abnormal processes and provide optimal and safe management of supply needed for the civil and military facilities in geographical areas, affected by disasters, earthquakes, fires and other accidents, weapons of mass destruction, terrorist attacks, etc. Obviously, these kinds of extreme events cause significant losses and damages to the infrastructure. In such cases, usage of intelligent support technologies is very important for quick and optimal location-transportation of emergency service in order to avoid new losses caused by these events. Timely servicing from emergency service centers to the affected disaster regions (response phase) is a key task of the emergency management system. Scientific research of this field takes the important place in decision-making problems. Our goal was to create an expert knowledge-based intelligent support system, which will serve as an assistant tool to provide optimal solutions for the above-mentioned problem. The inputs to the mathematical model of the system are objective data, as well as expert evaluations. The outputs of the system are solutions for Fuzzy Multi-Objective Emergency Location-Transportation Problem (FMOELTP) for disasters’ regions. The development and testing of the Intelligent Support System were done on the example of an experimental disaster region (for some geographical zone of Georgia) which was generated using a simulation modeling. Four objectives are considered in our model. The first objective is to minimize an expectation of total transportation duration of needed products. The second objective is to minimize the total selection unreliability index of opened humanitarian aid distribution centers (HADCs). The third objective minimizes the number of agents needed to operate the opened HADCs. The fourth objective minimizes the non-covered demand for all demand points. Possibility chance constraints and objective constraints were constructed based on objective-subjective data. The FMOELTP was constructed in a static and fuzzy environment since the decisions to be made are taken immediately after the disaster (during few hours) with the information available at that moment. It is assumed that the requests for products are estimated by homeland security organizations, or their experts, based upon their experience and their evaluation of the disaster’s seriousness. Estimated transportation times are considered to take into account routing access difficulty of the region and the infrastructure conditions. We propose an epsilon-constraint method for finding the exact solutions for the problem. It is proved that this approach generates the exact Pareto front of the multi-objective location-transportation problem addressed. Sometimes for large dimensions of the problem, the exact method requires long computing times. Thus, we propose an approximate method that imposes a number of stopping criteria on the exact method. For large dimensions of the FMOELTP the Estimation of Distribution Algorithm’s (EDA) approach is developed.

Keywords: epsilon-constraint method, estimation of distribution algorithm, fuzzy multi-objective combinatorial programming problem, fuzzy multi-objective emergency location/transportation problem

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Authors: Merina Islam

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In this paper, an attempt is made to draw out the contemporary relevance of philosophy in school education of India. This paper attempt is made to inquire into the importance of philosophy for schoolchildren in the Indian cultural context. As education in philosophy for children is useful for teaching the acquisition of knowledge from the information provided, for questioning of rules in different contexts, and for the analysis of facts encountered in daily life. Ethical attitudes can neither be derived from the information provided about the moral rules, nor do they result from a practice of unquestioning obedience It includes some studies done in this field and also reports on philosophy. Many European countries emphasise on the above said theme. There are lots of work and research done by many philosophers on philosophy for children. Indian values system is different from the West and more important than others. Education has become a tool to achieve efficiency in all walks of human life whether social, political, religious or philosophical. Every nation started developing its own specific set of educational values. For India it is very necessary to increase philosophical thinking study and research. Philosophy could make significant contribution, particularly in relation to children's moral development because the Indian curriculum currently neglects this aim. A teacher can play an important role in promoting this discussion because a teacher has the capacity to influence students with their thoughts and personality and engages them in these activities. Philosophy needs to be included in the curriculum and have demonstrated cognitive and social gains in children who were explored to philosophy in their schooling.

Keywords: education, ethical attitude, moral value, philosophy

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Authors: Ahmad Afif, Teuku Yuri M. Zagloel

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Sustainable supply chain management is a new pattern that has emerged recently in industry and companies. The procurement process is one of the key factors for efficiency in supply chain management practices. Partnership is one of the procurement strategies for strategic items. The success factors of the partnership must be determined to avoid things that endanger the financial and operational status of the company. The current supplier partnership research focuses on the selection of general criteria and sustainable supplier selection. Currently, there is still limited research on the success factors of supplier partnerships that focus on strategic items in the coal mining industry. Meanwhile, the procurement of coal mining has its own characteristics, and there are regulations related to the procurement of goods. Therefore, this research was conducted to determine the categories of goods that are included in the strategic items and to design the success factors of supplier partnerships. The main factors studied are general, financial, production, reputation, synergies, and sustainable. The research was conducted using the Kraljic method to determine the categories of goods that are included in the strategic items. To design a supplier partnership success factor using the Hybrid Multi Criteria Decision Making method. Integrated Fuzzy AHP-Fuzzy TOPSIS is used to determine the weight of the success factors of supplier partnerships and to rank suppliers on the factors used.

Keywords: supplier, partnership, strategic item, success factors, and coal mining industry

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Authors: Hadi Gholizadeh, Ali Tajdin

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To have effective production planning, it is necessary to control the quality of processes. This paper aims at improving the performance of the disposable essentials process using statistical quality control and goal programming in a vague environment. That is expressed uncertainty because there is always a measurement error in the real world. Therefore, in this study, the conditions are examined in a vague environment that is a distance-based environment. The disposable essentials process in Kach Company was studied. Statistical control tools were used to characterize the existing process for four factor responses including the average of disposable glasses’ weights, heights, crater diameters, and volumes. Goal programming was then utilized to find the combination of optimal factors setting in a vague environment which is measured to apply uncertainty of the initial information when some of the parameters of the models are vague; also, the fuzzy regression model is used to predict the responses of the four described factors. Optimization results show that the process capability index values for disposable glasses’ average of weights, heights, crater diameters and volumes were improved. Such increasing the quality of the products and reducing the waste, which will reduce the cost of the finished product, and ultimately will bring customer satisfaction, and this satisfaction, will mean increased sales.

Keywords: goal programming, quality control, vague environment, disposable glasses’ optimization, fuzzy regression

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Authors: Chung-Hung Tsai, Ya-Ping Li

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Tourism industry is highly depended on the natural environment and climate. Compared to other industries, it is more susceptible to environment and climate. Taiwan belongs to a sea island country and located in the subtropical monsoon zone. The events of climate variability, frequency of typhoons and rainfalls raged are caused regularly serious disaster. In traditional disaster assessment, it usually focuses on the disaster damage and risk assessment, which is short of the features from different industries to understand the impact of the restoring force in post-disaster resilience and the main factors that constitute resilience. The object of this study is based on disaster recovery experience of tourism area and to understand the main factors affecting the tourist area of disaster resilience. The combinations of literature review and interviews with experts are prepared an early indicator system of the disaster resilience. Then, it is screened through a Fuzzy Delphi Method and Analytic Network Process for weight analysis. Finally, this study will establish the tourism disaster resilience evaluation index system considering the Taiwan's tourism industry characteristics. We hope that be able to enhance disaster resilience after tourist areas and increases the sustainability of industrial development. It is expected to provide government departments the tourism industry as the future owner of the assets in extreme climates responses.

Keywords: resilience, Fuzzy Delphi Method, Analytic Network Process, industrial development

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Authors: Agnieszka A. Malinowska, R. Hejmanowski

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A number of European cities are strongly affected by ground movements caused by anthropogenic activities or post-anthropogenic metamorphosis. Those are mainly water pumping, current mining operation, the collapse of post-mining underground voids or mining-induced earthquakes. These activities lead to large and small-scale ground displacements and a ground ruptures. The ground movements occurring in urban areas could considerably affect stability and safety of structures and infrastructures. The complexity of the ground deformation phenomenon in relation to the structures and infrastructures vulnerability leads to considerable constraints in assessing the threat of those objects. However, the increase of access to the free software and satellite data could pave the way for developing new methods and strategies for environmental risk mitigation and management. Open source geographical information systems (OS GIS), may support data integration, management, and risk analysis. Lately, developed methods based on fuzzy logic and experts methods for buildings and infrastructure damage risk assessment could be integrated into OS GIS. Those methods were verified base on back analysis proving their accuracy. Moreover, those methods could be supported by ground displacement observation. Based on freely available data from European Space Agency and free software, ground deformation could be estimated. The main innovation presented in the paper is the application of open source software (OS GIS) for integration developed models and assessment of the threat of urban areas. Those approaches will be reinforced by analysis of ground movement based on free satellite data. Those data would support the verification of ground movement prediction models. Moreover, satellite data will enable our mapping of ground deformation in urbanized areas. Developed models and methods have been implemented in one of the urban areas hazarded by underground mining activity. Vulnerability maps supported by satellite ground movement observation would mitigate the hazards of land displacements in urban areas close to mines.

Keywords: fuzzy logic, open source geographic information science (OS GIS), risk assessment on urbanized areas, satellite interferometry (InSAR)

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Authors: Emmanuel Ayobami Adesiyan

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Political theorists have identified ethnicity as an obstacle to democratic stability in deeply divided societies. Nigeria belongs to the categories of problematic states labeled divided or deeply divided societies, as such post-independence politics is characterized by ethnicity with its ruinous effect on democratic governance and development. Institutional Engineering, the purposive manipulation of the electoral rule relating to party organization and the electoral formula has been established in comparative political studies as a policy measure for managing ethnicity in order to stabilize politics in divided societies. This paper examines the use of electoral engineering tools in managing ethnic politics in Nigeria’s Fourth Republic. The study is guided by rational institutional theory. Secondary data on electoral rules and disaggregated results of presidential elections were collected from archival documents. Data were subjected to content analysis. Institutional changes in electoral rules have promoted the development of inter-ethnic bargaining and compromises within the party system. Presidential Electoral Formula aided the emergence of national rather parochial parties. Electoral engineering tools moved Nigerian Politics from ethnic parochialism to inclusion and accommodation. These innovations should be strengthened to enhance democratic stability.

Keywords: Nigeria, presidential-elections, ethnic politics, institutional engineering

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Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

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Authors: Satinder Bhatia

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Limited Liability Partnerships (LLPs) was a concept introduced in India in 2009. Ever since then, there has been a fierce growth in the number of organizations registered as LLPs outpacing the number of registrations as private companies. Among other benefits extended to LLPs, the audit being mandated only for LLPs having a turnover of at least Rs 40 lakhs or capital contribution of Rs 25 lakhs, has been a major attraction. This has resulted in only about 10 per cent of LLPs coming under mandatory audit. Even for such companies, the accounting standards to be followed in the preparation of financial statements have not been specified. The Revised Indian Accounting Standards (Revised IndAS) which are aligned with IFRS to a great extent, may apply to LLPs only under limited conditions. Thus, the veracity of even the audited financial statements of LLPs can be questioned. If in future, these LLPs would like to list on a stock exchange to raise capital, there can be serious hurdles if investors do not find the financial statements to be reliable and consistent. LLPs are generally governed by country-specific rules in the area of accounts and audit. Thus, such rules vary across UK, EU and the USA. Some countries have adopted the IFRS for SMEs and since LLPs can be referred to as SMEs; they would come under the ambit of these IFRS provisions. Besides, as the scope of audit widens to cover qualitative information in addition to quantitative data, audit of LLPs has now acquired a new meaning and a new urgency as demands for at least limited purpose audits are arising from different stakeholders including lenders, suppliers, customers and joint venture partners.

Keywords: audit disclosures, audit quality, guidance for SMEs, non-audit services

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Authors: Chukwudi Chidume

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This paper considers the symbolism of kola nut according to Igbo worldview. How kola nut helps to shape the people’s philosophical ideology, especially in relation to religion. The roles of kola nut within the Igbo socio-cultural context and the values attached to these roles will be examined. The roles of kola nut as a means of socialization, education and transmission of cultural values from the preceding to succeeding generations will come under consideration. Equally, this paper looks at the traditional rules regarding not only the uses but more essentially the mode of kola nut presentation, blessing, breaking and sharing of kola nut. How these rules and kola nut have persisted in the face of social and cultural changes which have affected the Igbo people shall be reviewed. The roles played by kola nut in Igbo religion will come under study, which is to correct some of the misconceptions by writers who are motivated by eurocentric idealism but quite oblivious of the Igbo cultural setting and the place of kola nut in it. The onslaught of Western civilization causing the change of attitude among the young generation towards kola nut as a vital aspect of our culture tends to pose a threat to the future and survival of kola nut. Again, the study of Igbo culture as many have done rarely gives an in depth knowledge on the concept, roles and symbolism of kola nut as one of the sacred objects like Ofo and Shrines in Igboland. Mostly it is forgotten that without kola nut, shrines cannot be attended to. Many people think that the spiritual significance and sacramental symbolism are not worth exploring. They, therefore, refuse to try and discover the ritual ramifications, claiming that to probe into the mystery demystifies the matter. Kola nut symbolism is not mysteriously inexplicable. It is a revered symbol of social intercourse with deep social relevance.

Keywords: communion, consecration, Igbo, kola nut, religion

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Authors: Mukhtiar Singh, Sumeet Nagar

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Vehicle routing problem (VRP) is a combinatorial optimization and nonlinear programming problem aiming to optimize decisions regarding given set of routes for a fleet of vehicles in order to provide cost-effective and efficient delivery of both services and goods to the intended customers. This paper proposes the application of integrated particle swarm optimization (PSO) and genetic optimization algorithm (GA) to address the Vehicle routing problem in sugarcane industry in India. Suger industry is very prominent agro-based industry in India due to its impacts on rural livelihood and estimated to be employing around 5 lakhs workers directly in sugar mills. Due to various inadequacies, inefficiencies and inappropriateness associated with the current vehicle routing model it costs huge money loss to the industry which needs to be addressed in proper context. The proposed algorithm utilizes the crossover operation that originally appears in genetic algorithm (GA) to improve its flexibility and manipulation more readily and avoid being trapped in local optimum, and simultaneously for improving the convergence speed of the algorithm, level set theory is also added to it. We employ the hybrid approach to an example of VRP and compare its result with those generated by PSO, GA, and parallel PSO algorithms. The experimental comparison results indicate that the performance of hybrid algorithm is superior to others, and it will become an effective approach for solving discrete combinatory problems.

Keywords: fuzzy logic, genetic algorithm, particle swarm optimization, vehicle routing problem

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Authors: Mojtaba Eshraghi Arani

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Concluding the contract for carriage of cargo with the shipper (through bill of lading or charterparty), the carrier must transport the cargo from loading port to the port of discharge and deliver it to the consignee. Unless otherwise agreed in the contract, the carrier must avoid from any deviation, transfer of cargo to another vessel or unreasonable stoppage of carriage in-transit. However, the vessel might break down in-transit for any reason and becomes unable to continue its voyage to the port of discharge. This is a frequent incident in the carriage of goods by sea which leads to important dispute between the carrier/owner and the shipper/charterer (hereinafter called “cargo interests”). It is a generally accepted rule that in such event, the carrier/owner must repair the vessel after which it will continue its voyage to the destination port. The dispute will arise in the case that temporary repair of the vessel cannot be done in the short or reasonable term. There are two options for the contract parties in such a case: First, the carrier/owner is entitled to repair the vessel while having the cargo onboard or discharged in the port of refugee, and the cargo interests must wait till the breakdown is rectified at any time, whenever. Second, the carrier/owner will be responsible to charter another vessel and transfer the entirety of cargo to the substitute vessel. In fact, the main question revolves around the duty of carrier/owner to perform transfer of cargo to another vessel. Such operation which is called “trans-shipment” or “transhipment” (in terms of the oil industry it is usually called “ship-to-ship” or “STS”) needs to be done carefully and with due diligence. In fact, the transshipment operation for various cargoes might be different as each cargo requires its own suitable equipment for transfer to another vessel, so this operation is often costly. Moreover, there is a considerable risk of collision between two vessels in particular in bulk carriers. Bulk cargo is also exposed to the shortage and partial loss in the process of transshipment especially during bad weather. Concerning tankers which carry oil and petrochemical products, transshipment, is most probably followed by sea pollution. On the grounds of the above consequences, the owners are afraid of being held responsible for such operation and are reluctant to perform in the relevant disputes. The main argument raised by them is that no regulation has recognized such duty upon their shoulders so any such operation must be done under the auspices of the cargo interests and all costs must be reimbursed by themselves. Unfortunately, not only the international conventions including Hague rules, Hague-Visby Rules, Hamburg rules and Rotterdam rules but also most domestic laws are silent in this regard. The doctrine has yet to analyse the issue and no legal researches was found out in this regard. A qualitative method with the concept of interpretation of data collection has been used in this paper. The source of the data is the analysis of regulations and cases. It is argued in this article that the paramount rule in the maritime law is “the accomplishment of the voyage” by the carrier/owner in view of which, if the voyage can only be finished by transshipment, then the carrier/owner will be responsible to carry out this operation. The duty of carrier/owner to apply “due diligence” will strengthen this reasoning. Any and all costs and expenses will also be on the account pf the owner/carrier, unless the incident is attributable to any cause arising from the cargo interests’ negligence.

Keywords: cargo, STS, transshipment, vessel, voyage

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Authors: Omar Boutkhoum, Mohamed Hanine, Abdessadek Bendarag

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Sustainable economic growth is nowadays driving firms to extend toward the adoption of many green supply chain management (GSCM) solutions. However, the evaluation and selection of these solutions is a matter of concern that needs very serious decisions, involving complexity owing to the presence of various associated factors. To resolve this problem, a comparative analysis approach based on multi-criteria decision-making methods is proposed for adequate evaluation of sustainable supply chain management solutions. In the present paper, we propose an integrated decision-making model based on FAHP (Fuzzy Analytic Hierarchy Process), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) to contribute to a better understanding and development of new sustainable strategies for industrial organizations. Due to the varied importance of the selected criteria, FAHP is used to identify the evaluation criteria and assign the importance weights for each criterion, while TOPSIS and PROMETHEE methods employ these weighted criteria as inputs to evaluate and rank the alternatives. The main objective is to provide a comparative analysis based on TOPSIS and PROMETHEE processes to help make sound and reasoned decisions related to the selection problem of GSCM solution.

Keywords: GSCM solutions, multi-criteria analysis, decision support system, TOPSIS, FAHP, PROMETHEE

Procedia PDF Downloads 159

Authors: Seema Vaidya

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Mining association rule is a key issue in data mining. In any case, the standard models ignore the distinction among the exchanges, and the weighted association rule mining does not transform on databases with just binary attributes. This paper proposes a novel continuous example and executes a tree (FP-tree) structure, which is an increased prefix-tree structure for securing compacted, discriminating data about examples, and makes a fit FP-tree-based mining system, FP enhanced capacity algorithm is used, for mining the complete game plan of examples by illustration incessant development. Here, this paper handles the motivation behind making remarkable and weighted item sets, i.e. rare weighted item set mining issue. The two novel brightness measures are proposed for figuring the infrequent weighted item set mining issue. Also, the algorithm are handled which perform IWI which is more insignificant IWI mining. Moreover we utilized the rare item set for choice based structure. The general issue of the start of reliable definite rules is troublesome for the grounds that hypothetically no inciting technique with no other person can promise the rightness of influenced theories. In this way, this framework expects the disorder with the uncommon signs. Usage study demonstrates that proposed algorithm upgrades the structure which is successful and versatile for mining both long and short diagnostics rules. Structure upgrades aftereffects of foreseeing rare diseases of patient.

Keywords: association rule, data mining, IWI mining, infrequent item set, frequent pattern growth

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Authors: S. Yakubu, E. A. Isah

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One of the objectives of the school discipline policy is to instill discipline among students. However, despite the availability of this policy in various secondary schools in Nigeria, there seem to be numerous cases of indiscipline among students, which has become a source of concern to all stakeholders in the education sector. In an attempt to proffer possible solutions to this unending challenge, the study investigated the influence of knowledge and attitude on compliance of secondary school students towards school discipline policy in Ibadan North Local Government Area of Oyo State, Nigeria. The descriptive survey research design was employed to collect the requisite data. The multi-stage sampling procedure was adopted to select 570 respondents as the sample for the study. The data collected were analyzed using statistical measures of Mean, Standard deviation and Pearson Product Moment Correlation. The findings of the study showed that knowledge and compliance of school discipline policy among secondary school students in Ibadan North Local Government Area of Oyo State were significantly related (r =0.330, p<0.05). The study also revealed a significant relationship between attitude and compliance of school discipline policy among secondary school students in Ibadan North Local Government Area of Oyo State (r = 0.593, p<0.05). Based on the findings, it was recommended that school rules and regulations should be emphasized and given more awareness for easy compliance. Also, students should be encouraged to portray a positive attitude towards their respective rules and regulations.

Keywords: knowledge, attitude, compliance, school discipline policy

Procedia PDF Downloads 183

Authors: Suraj Sharma

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Green infrastructure (GI) offers a contemporary approach for reducing the risk of flooding, improve water quality, and harvesting stormwater for sustainable use. GI promotes landscape planning to enhance sustainable development and urban resilience. However, the existing literature is lacking in ensuring the comprehensive assessment of GI performance in terms of ecosystem function and services for social, ecological, and economical system resilience. We propose a robust indicator set and fuzzy comprehensive evaluation (FCE) for quantitative and qualitative analysis for sustainable water management to assess the capacity of urban resilience. Green infrastructure in urban resilience water management system (GIUR-WMS) supports decision-making for GI planning through scenario comparisons with urban resilience capacity index. To demonstrate the GIUR-WMS, we develop five scenarios for five sectors of Chandigarh (12, 26, 14, 17, and 34) to test common type of GI (rain barrel, rain gardens, detention basins, porous pavements, and open spaces). The result shows the open spaces achieve the highest green infrastructure urban resilience index of 4.22/5. To implement the open space scenario in urban sites, suitable vacant can be converted to green spaces (example: forest, low impact recreation areas, and detention basins) GIUR-WMS is easy to replicate, customize and apply to cities of different sizes to assess environmental, social and ecological dimensions.

Keywords: green infrastructure, assessment, urban resilience, water management system, fuzzy comprehensive evaluation

Procedia PDF Downloads 139

Authors: Houda Najeh, Mahendra Pratap Singh, Stéphane Ploix, Antoine Caucheteux, Karim Chabir, Mohamed Naceur Abdelkrim

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Building system is highly vulnerable to different kinds of faults and human misbehaviors. Energy efficiency and user comfort are directly targeted due to abnormalities in building operation. The available fault diagnosis tools and methodologies particularly rely on rules or pure model-based approaches. It is assumed that model or rule-based test could be applied to any situation without taking into account actual testing contexts. Contextual tests with validity domain could reduce a lot of the design of detection tests. The main objective of this paper is to consider fault validity when validate the test model considering the non-modeled events such as occupancy, weather conditions, door and window openings and the integration of the knowledge of the expert on the state of the system. The concept of heterogeneous tests is combined with test validity to generate fault diagnoses. A combination of rules, range and model-based tests known as heterogeneous tests are proposed to reduce the modeling complexity. Calculation of logical diagnoses coming from artificial intelligence provides a global explanation consistent with the test result. An application example shows the efficiency of the proposed technique: an office setting at Grenoble Institute of Technology.

Keywords: heterogeneous tests, validity, building system, sensor grids, sensor fault, diagnosis, fault detection and isolation

Procedia PDF Downloads 287

Authors: Meiju Chen, Chaoyu Guo, Chia Wei Tang

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The present study's purpose is twofold: first, to construct indicators for learning-oriented school education and, second, to conduct a survey to examine how learning-oriented education has been implemented in junior high schools after the launch of the 12-year compulsory curriculum. For indicator system construction, we compiled relevant literature to develop a preliminary indicator list model and then conducted two rounds of a questionnaire survey to gain comprehensive feedback from experts to finalize our indicator model. In the survey's first round, 12 experts were invited to evaluate the indicators' appropriateness. Based on the experts' consensus, we determined our final indicator list and used it to develop the Fuzzy Delphi questionnaire to finalize the indicator system and each indicator's relative value. For the fact-finding survey, we collected 454 valid samples to examine how the concept of learning-oriented education is adopted and implemented in the junior high school context. We also used this data in our importance-performance analysis to explore the strengths and weaknesses of school education in Taiwan. The results suggest that the indicator system for learning-oriented school education must consist of seven dimensions and 34 indicators. Among the seven dimensions, 'student learning' and 'curriculum planning and implementation' are the most important yet underperforming dimensions that need immediate improvement. We anticipate that the indicator system will be a useful tool for other countries' evaluation of schools' performance in learning-oriented education.

Keywords: learning-oriented education, school education, fuzzy Delphi method, importance-performance analysis

Procedia PDF Downloads 140

Authors: Suchismita Dattagupta

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Social rules and guidelines specify how a body should be clothed and how it should look. The social rules have made the body a space for expression, oppression and sexual 'commodification'. Being a malleable aspect of the human body, hair has always been worn in a number of ways and this characteristic of hair has made it an essential vehicle for conveying symbolic meaning. Hair, particularly women’s hair has always been considered to be associated with richness and beauty, apart from being associated with sexual power. Society has always had a preoccupation with hair bordering on obsession and has projected its moral and political supremacy by controlling and influencing how an individual wears their hair. Irrespective of the gender of the individual, society has tried to control an individual’s hair to express its control. However, with time, there has been a marked change in the way hair has been used by the individual. Hair has always been the focus of scholarly studies; not just aesthetically, but also in the cultural and social context. The fascination with hair rises from the fact that it is the only part of the human body that is always on display. Fetishization of hair is common in literature and goes ahead to reveal the character’s social and moral status. Modern authors for children and young adults have turned this concept on its head to point out how characters are breaking away from the mould and establishing their personal, moral and social boundaries. This paper will trace the change in hair symbolism in literature for children and young adults to understand how it has changed over the course of the time and what light it throws on the changing pattern of women’s position in society.

Keywords: gender, hair, social symbols, society, women's role

Procedia PDF Downloads 229

Authors: Bárbara Magalhães Bravo, Cláudia Figueiras

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The economical globalization through the liberalization of the markets and capitals boosted the economical development of the nations and the needs for sorting out the disputes arising from the foreign investment. The arbitration, for all the inherent advantages, such as swiftness, arbitrators’ specialise skills and impartiality sets a pacifier tool for the interest in account. Safeguarded the public interest, we face the problem of the confidentiality in the arbitration. The urgent development of impelling mechanisms concerning transparency, guaranty and protection of the interest in account, reveals itself urgent. Through a bibliography review, we will dense the state of art, by going through the several solutions concerning, and pointing out the most suitable. Through the jurisprudential analysis we will point out the solution for the conflict confidentiality/public interest. The transparency, inextricable from the public interest, imposes the arbitration process can be open to all citizens. Transparency rules have been considered at the UNCITRAL in attempting to conciliate the necessity of publicity and the public interest, however still insufficient. The arbitration of foreign investment carries consequences to the citizens of the State. Articulating mechanisms between the arbitral procedures secrecy and the public interest should be adopted. The arbitration of foreign investment, being a tertius genius between the international arbitration and the administrative arbitration would claim its own regulation in each and every States where the confidentiality rules and its exceptions could be identified. One should enquiry where the limit of the citizens’ individual rights protection and the public interest should give way to the principle of transparency

Keywords: arbitration, foreign investment, transparency, confidenciality, International Centre for Settlement of Investment Disputes UNCITRAL

Procedia PDF Downloads 207

Authors: Arindam Chaudhuri

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Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

Procedia PDF Downloads 486

Authors: S. Niamkaeo, O. Robert, O. Chaowalit

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In this investigation, we focus on discovering spatial relationship of drug smuggling along the northern border of Thailand. Thailand is no longer a drug production site, but Thailand is still one of the major drug trafficking hubs due to its topographic characteristics facilitating drug smuggling from neighboring countries. Our study areas cover three districts (Mae-jan, Mae-fahluang, and Mae-sai) in Chiangrai city and four districts (Chiangdao, Mae-eye, Chaiprakarn, and Wienghang) in Chiangmai city where drug smuggling of methamphetamine crystal and amphetamine occurs mostly. The data on drug smuggling incidents from 2011 to 2017 was collected from several national and local published news. Geo-spatial drug smuggling database was prepared. Decision tree algorithm was applied in order to discover the spatial relationship of factors related to drug smuggling, which was converted into rules using rule-based system. The factors including land use type, smuggling route, season and distance within 500 meters from check points were found that they were related to drug smuggling in terms of rules-based relationship. It was illustrated that drug smuggling was occurred mostly in forest area in winter. Drug smuggling exhibited was discovered mainly along topographic road where check points were not reachable. This spatial relationship of drug smuggling could support the Thai Office of Narcotics Control Board in surveillance drug smuggling.

Keywords: decision tree, drug smuggling, Geographic Information System, GIS knowledge discovery, rule-based system

Procedia PDF Downloads 163