Search results for: Ascending Sort Index Vector

Authors: Zeynep Şahin, Züleyha Yılmaz, Fikret Çankaya

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In today's business world, in which it is difficult to survive, the economic life of products, services or knowledge is considerably reduced. Competitors produce similar products or extra-featured ones instantly. In this environment, the contribution of companies to the social and economic environment is a preferred criterion by consumers alongside products or services. Therefore, consumers need to obtain more detailed information about companies. Besides, this drastic change in the market encourages companies to become sustainable. Sustainable business means the company puts consumed products back. Corporate sustainability, corresponds to sustainability at the level of the company, and gives equal importance to company growth and profitability together with environmental and social issues. The BIST Sustainability Index started to be calculated by the Istanbul Stock Exchange (BIST) in 2014 to evaluate the sustainability performance of companies in Turkey. The main objective of this study is to present the importance of sustainability reports in Turkey. To this aim, the performances of 15 companies in the BIST Sustainability Index were compared the periods before and after entering the index. On the other hand, sustainability reporting practices should be encouraged to increase studies on this issue. In this context, to remain on the agenda of the issue is a further objective of this study. To achieve these objectives, the financial data of the companies in the period before and after entering to the BIST Sustainability Index were analyzed using t-test in Statistical Package for the Social Sciences (SPSS) package. The results of the study showed that no significant difference between the performances of the companies in terms of the net profit margin, the return on assets and equity capital in these periods could be found. Therefore, it can be said that insufficient importance is given to sustainability issues in Turkey. The reasons for this situation might be considered as a lack of awareness due to the recent introduction and calculation of the index. It is expected that the awareness of firms and investors about sustainability will increase, and that they will demonstrate the necessary importance to this issue over time.

Keywords: BIST sustainability index, firm performance, sustainability, sustainability reporting.

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Authors: A. Ameur, B. Mokhtari, N. Essounbouli, L. Mokrani

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This paper presents a speed sensorless direct torque control scheme using space vector modulation (DTC-SVM) for permanent magnet synchronous motor (PMSM) drive based a Model Reference Adaptive System (MRAS) algorithm and stator resistance estimator. The MRAS is utilized to estimate speed and stator resistance and compensate the effects of parameter variation on stator resistance, which makes flux and torque estimation more accurate and insensitive to parameter variation. In other hand the use of SVM method reduces the torque ripple while achieving a good dynamic response. Simulation results are presented and show the effectiveness of the proposed method.

Keywords: MRAS, PMSM, SVM, DTC, Speed and Resistance estimation, Sensorless drive

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Authors: R. Mallika, V. Saravanan

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This paper gives a novel method for improving classification performance for cancer classification with very few microarray Gene expression data. The method employs classification with individual gene ranking and gene subset ranking. For selection and classification, the proposed method uses the same classifier. The method is applied to three publicly available cancer gene expression datasets from Lymphoma, Liver and Leukaemia datasets. Three different classifiers namely Support vector machines-one against all (SVM-OAA), K nearest neighbour (KNN) and Linear Discriminant analysis (LDA) were tested and the results indicate the improvement in performance of SVM-OAA classifier with satisfactory results on all the three datasets when compared with the other two classifiers.

Keywords: Support vector machines-one against all, cancerclassification, Linear Discriminant analysis, K nearest neighbour, microarray gene expression, gene pair ranking.

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Authors: Mimi Hafizah Abdullah, Hanani Farhah Harun, Nik Ruzni Nik Idris

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With the implied volatility as an important factor in financial decision-making, in particular in option pricing valuation, and also the given fact that the pricing biases of Leland option pricing models and the implied volatility structure for the options are related, this study considers examining the implied adjusted volatility smile patterns and term structures in the S&P/ASX 200 index options using the different Leland option pricing models. The examination of the implied adjusted volatility smiles and term structures in the Australian index options market covers the global financial crisis in the mid-2007. The implied adjusted volatility was found to escalate approximately triple the rate prior the crisis.

Keywords: Implied adjusted volatility, Financial crisis, Leland option pricing models.

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Authors: Mustafa M. Donma

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Circumference measurements may give meaningful information about the varying stages of obesity. Some formulas may be derived from a number of body circumference measurements to estimate body fat. Waist (WC), hip (HC) and neck (NC) circumferences are currently the most frequently used measurements. The aim of this study was to develop a formula derived from these three anthropometric measurements for the differential diagnosis of morbid obesity with and without metabolic syndrome (MetS), MOMetS+ and MOMetS-, respectively. 187 children were recruited from the pediatrics outpatient clinic of Tekirdag Namik Kemal University, Faculty of Medicine. Signed informed consent forms were taken from the participants. The study was carried out according to the Helsinki Declaration. The study protocol was approved by the institutional non-interventional ethics committee of Tekirdag Namik Kemal University Medical Faculty. The study population was divided into four groups as normal-body mass index (N-BMI) (n = 35), obese (OB) (n = 44), morbid obese (MO) (n = 75) and MetS (n = 33). Age- and gender-adjusted BMI percentile values were used for the classification of groups. The children in MetS group were selected based upon the nature of the MetS components described as MetS criteria. Anthropometric measurements, laboratory analysis and statistical evaluation confined to study population were performed. BMI values were calculated. A circumference index, advanced Donma circumference index (ADCI) was presented as WC*HC/NC. The statistical significance degree was chosen as p < 0.05. BMI values were 17.7 ± 2.8, 24.5 ± 3.3, 28.8 ± 5.7, 31.4 ± 8.0 kg/m2, for N-BMI, OB, MO, MetS groups (p = 0.001), respectively. An increasing trend from N-BMI to MetS was observed. However, the increase in MetS group compared to MO group was not significant. For the new index, significant differences were obtained between N-BMI and OB, MO, MetS groups (p = 0.001). A significant difference between MO and MetS groups was detected (p = 0.043). A significant correlation was found between BMI and ADCI. In conclusion, in spite of the strong correlation between BMI and ADCI values obtained when all groups were considered, ADCI, but not BMI, was the index, which was capable of differentiating cases with morbid obesity from cases with morbid obesity and MetS.

Keywords: Anthropometry, body mass index, childhood obesity, body circumference, metabolic syndrome.

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Authors: S. Chokri

Abstract:

Load modeling is one of the central functions in power systems operations. Electricity cannot be stored, which means that for electric utility, the estimate of the future demand is necessary in managing the production and purchasing in an economically reasonable way. A majority of the recently reported approaches are based on neural network. The attraction of the methods lies in the assumption that neural networks are able to learn properties of the load. However, the development of the methods is not finished, and the lack of comparative results on different model variations is a problem. This paper presents a new approach in order to predict the Tunisia daily peak load. The proposed method employs a computational intelligence scheme based on the Fuzzy neural network (FNN) and support vector regression (SVR). Experimental results obtained indicate that our proposed FNN-SVR technique gives significantly good prediction accuracy compared to some classical techniques.

Keywords: Neural network, Load Forecasting, Fuzzy inference, Machine learning, Fuzzy modeling and rule extraction, Support Vector Regression.

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Authors: Munehiro Iwami

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A property is called persistent if for any many-sorted term rewriting system , has the property if and only if term rewriting system , which results from by omitting its sort information, has the property. In this paper,we show that termination is persistent for non-overlapping term rewriting systems and we give the example as application of this result. Furthermore we obtain that completeness is persistent for non-overlapping term rewriting systems.

Keywords: Theory of computing, Model-based reasoning, termrewriting system, termination

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Authors: A. Nachour, L. Ouzizi, Y. Aoura

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Recent developments on multi-agent system have brought a new research field on image processing. Several algorithms are used simultaneously and improved in deferent applications while new methods are investigated. This paper presents a new automatic method for edge detection using several agents and many different actions. The proposed multi-agent system is based on parallel agents that locally perceive their environment, that is to say, pixels and additional environmental information. This environment is built using Vector Field Convolution that attract free agent to the edges. Problems of partial, hidden or edges linking are solved with the cooperation between agents. The presented method was implemented and evaluated using several examples on different synthetic and medical images. The obtained experimental results suggest that this approach confirm the efficiency and accuracy of detected edge.

Keywords: Edge detection, medical MR images, multi-agent systems, vector field convolution.

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Authors: Nicholas D. Assimakis

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In linear estimation, the traditional Kalman filter uses the Kalman filter gain in order to produce estimation and prediction of the n-dimensional state vector using the m-dimensional measurement vector. The computation of the Kalman filter gain requires the inversion of an m x m matrix in every iteration. In this paper, a variation of the Kalman filter eliminating the Kalman filter gain is proposed. In the time varying case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix and the inversion of an m x m matrix in every iteration. In the time invariant case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix in every iteration. The proposed Kalman filter gain elimination algorithm may be faster than the conventional Kalman filter, depending on the model dimensions.

Keywords: Discrete time, linear estimation, Kalman filter, Kalman filter gain.

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Authors: Mou-Yuan Liao, Chien-Wei Wu, Chien-Hua Lin

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Process capability index Cpk is the most widely used index in making managerial decisions since it provides bounds on the process yield for normally distributed processes. However, existent methods for assessing process performance which constructed by statistical inference may unfortunately lead to fine results, because uncertainties exist in most real-world applications. Thus, this study adopts fuzzy inference to deal with testing of Cpk . A brief score is obtained for assessing a supplier’s process instead of a severe evaluation.

Keywords: Process capability analysis, quality control.

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Authors: Jameela Ali Alkrimi, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifying the RBCs as normal or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithms tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital - Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively.

Keywords: K-Nearest Neighbors, Neural Network, Radial Basis Function, Red blood cells, Support vector machine.

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Authors: Zhibo Xiao, Tharini Nayanika de Silva, Kezhi Mao

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In this paper, we present an evolving knowledge extraction system named AKEOS (Automatic Knowledge Extraction from Online Sources). AKEOS consists of two modules, including a one-time learning module and an evolving learning module. The one-time learning module takes in user input query, and automatically harvests knowledge from online unstructured resources in an unsupervised way. The output of the one-time learning is a structured vector representing the harvested knowledge. The evolving learning module automatically schedules and performs repeated one-time learning to extract the newest information and track the development of an event. In addition, the evolving learning module summarizes the knowledge learned at different time points to produce a final knowledge vector about the event. With the evolving learning, we are able to visualize the key information of the event, discover the trends, and track the development of an event.

Keywords: Evolving learning, knowledge extraction, knowledge graph, text mining.

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Authors: Gabriella Tjondro, Julita Dortua Laurentina Nainggolan

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Introduction: There are several things affecting menstrual cycle, namely, nutritional status, diet, financial status of one’s household and exercises. The most commonly used parameter to calculate the fat in a human body is body mass index. Therefore, it is necessary to do research to prevent complications caused by menstrual disorder in the future. Design Study: This research is an observational analytical study with the cross-sectional-case control approach. Participants (n = 124; median age = 19.5 years ± SD 3.5) were classified into 2 groups: normal, NM (n = 62; BMI = 18-23 kg/m²) and obese, OB (n = 62; BMI = > 25 kg/m²). BMI was calculated from the equation; BMI = weight, kg/height, m². Results: There were 79.10% from obese group who experienced menstrual cycle disorders (n=53, 79.10%; p value 0.00; OR 5.25) and 20.90% from normal BMI group with menstrual cycle disorders. There were several factors in this research that also influence the menstrual cycle disorders such as stress (44.78%; p value 0.00; OR 1.85), sleep disorders (25.37%; p value 0.00; OR 1.01), physical activities (25.37%; p value 0.00; OR 1.24) and diet (10.45%; p value 0.00; OR 1.07). Conclusion: There is a significant relation between body mass index (obese) and menstrual cycle disorders. However, BMI is not the only factor that affects the menstrual cycle disorders. There are several factors that also can affect menstrual cycle disorders, in this study we use stress, sleep disorders, physical activities and diet, in which none of them are dominant.

Keywords: Menstrual disorders, menstrual cycle, obesity, body mass index, stress, sleep disorders, physical activities, diet.

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Authors: Joe Walsh, Mike Climstein, Ian Timothy Heazlewood, Stephen Burke, Jyrki Kettunen, Kent Adams, Mark DeBeliso

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Thousands of masters athletes participate quadrennially in the World Masters Games (WMG), yet this cohort of athletes remains proportionately under-investigated. Due to a growing global obesity pandemic in context of benefits of physical activity across the lifespan, the prevalence of obesity in this unique population was of particular interest. Data gathered on a sub-sample of 535 football code athletes, aged 31-72 yrs ( =47.4, s =±7.1), competing at the Sydney World Masters Games (2009) demonstrated a significantly (p<0.001), reduced classification of obesity using Body Mass Index (BMI) when compared to data on the Australian national population. This evidence of improved classification in one index of health (BMI<30) implies there are either improved levels of this index of health due to adherence to sport or possibly the reduced BMI is advantageous and contributes to this cohort adhering (or being attracted) to masters sport. Given the worldwide focus on the obesity epidemic and the need for a multi-faceted solution to this problem, demonstration of these middle to older aged adults having improved BMI over the general population is of particular interest.

Keywords: BMI, masters athlete, rugby union, soccer, touch football

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Authors: Mojtaba Heydarizad

Abstract:

Khorasan Razavi is the second most important province in north-east of Iran, which faces a water shortage crisis due to recent droughts and huge water consummation. Kardeh and Torogh dam reservoirs in this province provide a notable part of Mashhad metropolitan (with more than 4.5 million inhabitants) potable water needs. Hydrochemical analyses on these dam reservoirs samples demonstrate that MgHCO₃ in Kardeh and CaHCO₃ and to lower extent MgHCO₃ water types in Torogh dam reservoir are dominant. On the other hand, Gibbs binary diagram demonstrates that rock weathering is the main factor controlling water quality in dam reservoirs. Plotting dam reservoir samples on Mg²⁺/Na⁺ and HCO₃^-/Na⁺ vs. Ca²⁺/ Na⁺ diagrams demonstrate evaporative and carbonate mineral dissolution is the dominant rock weathering ion sources in these dam reservoirs. Cluster Analyses (CA) also demonstrate intense role of rock weathering mainly (carbonate and evaporative minerals dissolution) in water quality of these dam reservoirs. Studying water quality by the U.S. National Sanitation Foundation (NSF) WQI index NSF-WQI, Oregon Water Quality Index (OWQI) and Canadian Water Quality Index DWQI index show moderate and good quality.

Keywords: Hydrochemistry, water quality classification, water quality indexes, Torogh and Kardeh Dam Reservoirs.

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Authors: Olofintoye Lawrence Kayode, Olorunniyi Omojola Felix

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Schistosomiasis is a vector-borne water-based disease transmitted by Bulinus globosus, causing haematuria in the urine of man, while fascioliasis is a trematode zoonosis infectious transmitted by Lymnaea natalensis causing liver disease in man and animals. Adult Bulinus globosus and Lymnaea natalensis were used for the experiment. Aqueous leaf extract of Ageratum conyzoides and Datura stramonium were prepared into 25, 50, 75, 100, 200 and 400 ppm concentrations. Ten snails of each species were exposed to different concentrations in triplicates, and dechlorinated water was used as control at 24h, 48h, and 72h exposure. The results revealed that 100 ppm of both plants leaves extracts indicated mortality rates between 76.7% and 100% at 24h, 48h, and 72h for both snail species. (P < 0.05). In conclusion, the extract exercised molluscicidal activity to control the snail vector at lethal doses LC50 (66.611-72.021 ppm), CI = 63.083-77.90 ppm and LC90 (92.623-102.350), CI = 87.715-110.12 ppm.

Keywords: Snail, plant leaf, aqueous extract, mortality.

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Authors: Aleš Florian, Lenka Ševelová, Jaroslav Žák

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Formation of tensile cracks in concrete slabs of rigid pavement can be (among others) the initiation point of the other, more serious failures which can ultimately lead to complete degradation of the concrete slab and thus the whole pavement. Two measures can be used for reliability assessment of this phenomenon - the probability of failure and/or the reliability index. Different methods can be used for their calculation. The simple ones are called moment methods and simulation techniques. Two methods - FOSM Method and Simple Random Sampling Method - are verified and their comparison is performed. The influence of information about the probability distribution and the statistical parameters of input variables as well as of the limit state function on the calculated reliability index and failure probability are studied in three points on the lower surface of concrete slabs of the older type of rigid pavement formerly used in the Czech Republic.

Keywords: Failure, pavement, probability, reliability index, simulation, tensile crack.

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Authors: Sadia Iqbal, Faheem Iqbal, Furqan Iqbal

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Efficient utilization of existing water is a pressing need for Pakistan. Due to rising population, reduction in present storage capacity and poor delivery efficiency of 30 to 40% from canal. A study to evaluate an irrigation system in the cotton-wheat zone of Pakistan, after the watercourse lining was conducted. The study is made on the basis of cropping pattern and salinity to evaluate the system. This study employed an index-based approach of using Geographic information system with field data. The satellite images of different years were use to examine the effective area. Several combinations of the ratio of signals received in different spectral bands were used for development of this index. Near Infrared and Thermal IR spectral bands proved to be most effective as this combination helped easy detection of salt affected area and cropping pattern of the study area. Result showed that 9.97% area under salinity in 1992, 9.17% in 2000 and it left 2.29% in year 2005. Similarly in 1992, 45% area is under vegetation it improves to 56% and 65% in 2000 and 2005 respectively. On the basis of these results evaluation is done 30% performance is increase after the watercourse improvement.

Keywords: Salinity, remote sensing index, salinity index, cropping pattern.

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Authors: Surinder Deswal, D. V. S. Verma

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Aeration by a plunging water jet is an energetically attractive way to effect oxygen-transfer than conventional oxygenation systems. In the present study, a new type of conical shaped plunging aeration device is fabricated to generate hollow inclined ined plunging jets (jet plunge angle of π/3 ) to investigate its oxygen transfer capacity. The results suggest that the volumetric oxygen-transfer coefficient and oxygen-transfer efficiency of the conical plunging jet aerator are competitive with other types of aeration systems. Relationships of volumetric oxygen-transfer coefficient with jet power per unit volume and jet parameters are also proposed. The suggested relationships predict the volumetric oxygentransfer coefficient within a scatter of ± 15% . Further, the application of Support Vector Machines on the experimental data revealed its utility in the prediction of volumetric oxygen-transfer coefficient and development of conical plunging jet aerators.

Keywords: Conical plunging jet, oxygen-transfer efficiency, support vector machines, volumetric oxygen-transfer coefficient.

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Authors: U. Kalay, O. Kalıpsız

Abstract:

For a spatiotemporal database management system, I/O cost of queries and other operations is an important performance criterion. In order to optimize this cost, an intense research on designing robust index structures has been done in the past decade. With these major considerations, there are still other design issues that deserve addressing due to their direct impact on the I/O cost. Having said this, an efficient buffer management strategy plays a key role on reducing redundant disk access. In this paper, we proposed an efficient buffer strategy for a spatiotemporal database index structure, specifically indexing objects moving over a network of roads. The proposed strategy, namely MONPAR, is based on the data type (i.e. spatiotemporal data) and the structure of the index structure. For the purpose of an experimental evaluation, we set up a simulation environment that counts the number of disk accesses while executing a number of spatiotemporal range-queries over the index. We reiterated simulations with query sets with different distributions, such as uniform query distribution and skewed query distribution. Based on the comparison of our strategy with wellknown page-replacement techniques, like LRU-based and Prioritybased buffers, we conclude that MONPAR behaves better than its competitors for small and medium size buffers under all used query-distributions.

Keywords: Buffer Management, Spatiotemporal databases.

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Authors: José M. Merigó, Anna M. Gil-Lafuente

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Different types of aggregation operators such as the ordered weighted quasi-arithmetic mean (Quasi-OWA) operator and the normalized Hamming distance are studied. We introduce the use of the OWA operator in generalized distances such as the quasiarithmetic distance. We will call these new distance aggregation the ordered weighted quasi-arithmetic distance (Quasi-OWAD) operator. We develop a general overview of this type of generalization and study some of their main properties such as the distinction between descending and ascending orders. We also consider different families of Quasi-OWAD operators such as the Minkowski ordered weighted averaging distance (MOWAD) operator, the ordered weighted averaging distance (OWAD) operator, the Euclidean ordered weighted averaging distance (EOWAD) operator, the normalized quasi-arithmetic distance, etc.

Keywords: Aggregation operators, Distance measures, Quasi- OWA operator.

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Authors: S. Olyaee, M. Seifouri, A. Nikoosohbat, M. Shams Esfand Abadi

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Photonic Crystal Fibers (PCFs) can be used in optical communications as transmission lines. For this reason, the PCFs with low confinement loss, low chromatic dispersion, and low nonlinear effects are highly suitable transmission media. In this paper, we introduce a new design of index-guiding nanostructured photonic crystal fiber (IG-NPCF) with ultra-low chromatic dispersion, low nonlinearity effects, and low confinement loss. Relatively low dispersion is achieved in the wavelength range of 1200 to 1600nm using the proposed design. According to the new structure of nanostructured PCF presented in this study, the chromatic dispersion slope is -30(ps/km.nm) and the confinement loss reaches below 10-7 dB/km. While in the wavelength range mentioned above at the same time an effective area of more than 50.2μm2 is obtained.

Keywords: Optical communication systems, nanostructured, index-guiding, dispersion, confinement loss, photonic crystal fiber.

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Authors: A. Perolini

Abstract:

Feature and model selection are in the center of attention of many researches because of their impact on classifiers- performance. Both selections are usually performed separately but recent developments suggest using a combined GA-SVM approach to perform them simultaneously. This approach improves the performance of the classifier identifying the best subset of variables and the optimal parameters- values. Although GA-SVM is an effective method it is computationally expensive, thus a rough method can be considered. The paper investigates a joined approach of Genetic Algorithm and kernel matrix criteria to perform simultaneously feature and model selection for SVM classification problem. The purpose of this research is to improve the classification performance of SVM through an efficient approach, the Kernel Matrix Genetic Algorithm method (KMGA).

Keywords: Feature and model selection, Genetic Algorithms, Support Vector Machines, kernel matrix.

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Authors: Naresh Yadav, I.A. Khan, Sandeep Grover

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This paper presents a methodology for operational and economic characteristics based evaluation and selection of a power plant using Graph theoretic approach. A universal evaluation index on the basis of Operational and economics characteristics of a plant is proposed which evaluates and ranks the various types of power plants. The index thus obtained from the pool of operational characteristics of the power plant attributes Digraph. The Digraph is developed considering Operational and economics attributes of the power plants and their relative importance for their smooth operation, installation and commissioning and prioritizing their selection. The sensitivity analysis of the attributes towards the objective has also been carried out in order to study the impact of attributes over the desired outcome i.e. the universal operational-economics index of the power plant.

Keywords: Power plant evaluation, Digraph methods, Matrixmethod, operational characteristics of Power plant, Gas turbines

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Authors: Ilma Robo, Saimir Heta, Greta Plaka, Vera Ostreni

Abstract:

Purpose: Drug gingival hyperplasia is an uncommon pathology encountered during routine work in dental units. The purpose of this paper is to present the clinical appearance of gingival hyperplasia caused by medications. There are already three classes of medications that cause hyperplasia and based on data from the literature, the clinical cases encountered and included in this study have been compared. Materials and Methods: The study was conducted in a total of 311 patients, out of which 182 patients were included in our study, meeting the inclusion criteria. After each patient's history was recorded and it was found that patients were in their knowledge of chronic illness, undergoing treatment of gingivitis hypertrophic drugs was performed with a clinical examination of oral cavity and assessment by vertical and horizontal evaluation according to the periodontal indexes. Results: Of the data collected during the study, it was observed that 97% of patients with gingival hyperplasia are treated with nifedipine. 84% of patients treated with selected medicines and gingival hyperplasia in the oral cavity has been exposed at time period for more than 1 year and 1 month. According to the GOI, in the first rank of this index are about 21% of patients, in the second rank are 52%, in the third rank are 24% and in the fourth grade are 3%. According to the horizontal growth index of gingival hyperplasia, grade 1 included about 61% of patients and grade 2 included about 39% of patients with gingival hyperplasia. Bacterial index divides patients by degrees: grading 0 - 8.2%, grading 1 - 32.4%, grading 2 - 14% and grading 3 - 45.1%. Conclusions: The highest percentage of gingival hyperplasia caused by drugs is due to dosing of nifedipine for a duration of dosing and application for systemic healing for more than 1 year.

Keywords: Drug gingival hyperplasia, horizontal growth index, vertical growth index.

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Authors: Lu Zhang, Chunping Li, Jun Liu, Hui Wang

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Text similarity measurement is a fundamental issue in many textual applications such as document clustering, classification, summarization and question answering. However, prevailing approaches based on Vector Space Model (VSM) more or less suffer from the limitation of Bag of Words (BOW), which ignores the semantic relationship among words. Enriching document representation with background knowledge from Wikipedia is proven to be an effective way to solve this problem, but most existing methods still cannot avoid similar flaws of BOW in a new vector space. In this paper, we propose a novel text similarity measurement which goes beyond VSM and can find semantic affinity between documents. Specifically, it is a unified graph model that exploits Wikipedia as background knowledge and synthesizes both document representation and similarity computation. The experimental results on two different datasets show that our approach significantly improves VSM-based methods in both text clustering and classification.

Keywords: Text classification, Text clustering, Text similarity, Wikipedia

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Authors: Li Xiguang

Abstract:

In this paper, by constructing a special set and utilizing fixed point index theory, we study the existence of solution for singular differential equation in Banach space, which improved and generalize the result of related paper.

Keywords: Banach space, cone, fixed point index, singular differential equation.

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Authors: Federica Cornali

Abstract:

Does education matter to the quality of our life? The results of extensive studies offer an affirmative answer to this question: high education levels are positively associated with higher income, with more highly qualified professions, with lower risk of unemployment, with better physical health and also, it is said, with more happiness. However, exploring these relationships is far from straightforward. Aside from educational credentials, what properties distinguish functionally literate individuals? How can their personal level of satisfaction be measured? What are the social mechanisms whereby education affects well-being?Using a literacy index and several measures for well-being developed by secondary analysis of the Adult Literacy and Life Skills Survey database, this investigation examined the relationship between literacy skills and subjective wellbeing in several OECD (Organisation for Economic Co-operation and Development) countries. Special attention was been addressed to Italy, and in particular to two regions representing territorial differences in this country: Piedmont and Campania.

Keywords: Cultural Divide, Literacy Index, Life Satisfaction, Subjective Well-being Index

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Authors: Hiba Basim Alwan, Ku Ruhana Ku-Mahamud

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A direction for ACO is to optimize continuous and mixed (discrete and continuous) variables in solving problems with various types of data. Support Vector Machine (SVM), which originates from the statistical approach, is a present day classification technique. The main problems of SVM are selecting feature subset and tuning the parameters. Discretizing the continuous value of the parameters is the most common approach in tuning SVM parameters. This process will result in loss of information which affects the classification accuracy. This paper presents two algorithms that can simultaneously tune SVM parameters and select the feature subset. The first algorithm, ACO_R-SVM, will tune SVM parameters, while the second IACO_MV-R-SVM algorithm will simultaneously tune SVM parameters and select the feature subset. Three benchmark UCI datasets were used in the experiments to validate the performance of the proposed algorithms. The results show that the proposed algorithms have good performances as compared to other approaches.

Keywords: Continuous ant colony optimization, incremental continuous ant colony, simultaneous optimization, support vector machine.

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Authors: Swapnoneel Roy, Ashok Kumar Thakur, Minhazur Rahman

Abstract:

The Block Sorting problem is to sort a given permutation moving blocks. A block is defined as a substring of the given permutation, which is also a substring of the identity permutation. Block Sorting has been proved to be NP-Hard. Until now two different 2-Approximation algorithms have been presented for block sorting. These are the best known algorithms for Block Sorting till date. In this work we present a different characterization of Block Sorting in terms of a transposition cycle graph. Then we suggest a heuristic, which we show to exhibit a 2-approximation performance guarantee for most permutations.

Keywords: Block Sorting, Optical Character Recognition, Genome Rearrangements, Sorting Primitives, ApproximationAlgorithms

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