Search results for: variation sets

Authors: G. S. Thakur

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In this paper, four new operators (O1, O2, O3, O4) are proposed, defined and considered to study the new properties and identities on hesitant fuzzy sets. These operators are useful for different operation on hesitant fuzzy sets. The various theorems are proved using the new operators. The study of the proposed new operators has opened a new area of research and applications.

Keywords: vague sets, hesitant fuzzy sets, intuitionistic fuzzy set, fuzzy sets, fuzzy multisets

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Authors: Asha Gupta, Ramandeep Kaur

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The purpose of this paper is to study a class of closed sets, called generalized pre-closed sets with respect to an ideal (briefly Igp-closed sets), which is an extension of generalized pre-closed sets in general topology. Then, by using these sets, the concepts of Igp- compact spaces along with some classes of maps like continuous and closed maps via ideals have been introduced and analogues of some known results for compact spaces, continuous maps and closed maps in general topology have been obtained.

Keywords: ideal, gp-closed sets, gp-closed maps, gp-continuous maps

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Authors: Inayatur Rehman

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Molodtstove developed the theory of soft sets which can be seen as an effective tool to deal with uncertainties. Since the introduction of this concept, the application of soft sets has been restricted to associative algebraic structures (groups, semi groups, associative rings, semi-rings etc.). Acceptably, though the study of soft sets, where the base set of parameters is a commutative structure, has attracted the attention of many researchers for more than one decade. But on the other hand there are many sets which are naturally endowed by two compatible binary operations forming a non-associative ring and we may dig out examples which investigate a non-associative structure in the context of soft sets. Thus it seems natural to apply the concept of soft sets to non-commutative and non-associative structures. In present paper, we make a new approach to apply Molodtsoves notion of soft sets to LA-ring (a class of non-associative ring). We extend the study of soft commutative rings from theoretical aspect.

Keywords: soft sets, LA-rings, soft LA-rings, soft ideals, soft prime ideals, idealistic soft LA-rings, LA-ring homomorphism

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Authors: Surabhi Maiti, Prajakta Tamhankar, Prachi Uttam Mehta

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Since the accomplishment of the Human Genome Project, there has been an unparalled escalation in the sequencing of genomic data. This project has been the first major vault in the field of medical research, especially in genomics. This project won accolades by using a concept called Bigdata which was earlier, extensively used to gain value for business. Bigdata makes use of data sets which are generally in the form of files of size terabytes, petabytes, or exabytes and these data sets were traditionally used and managed using excel sheets and RDBMS. The voluminous data made the process tedious and time consuming and hence a stronger framework called Hadoop was introduced in the field of genetic sciences to make data processing faster and efficient. This paper focuses on using SPARK which is gaining momentum with the advancement of BigData technologies. Cloud Storage is an effective medium for storage of large data sets which is generated from the genetic research and the resultant sets produced from SPARK analysis.

Keywords: human genome project, Bigdata, genomic data, SPARK, cloud storage, Hadoop

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Authors: Özlem Öksüzer

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In this paper, we introduce variation detracting property of Kantorovich-Stancu type operators in the space of functions of bounded variation. These problems are studied with respect to the variation seminorm.

Keywords: Kantorovich-Stancu type operators, variation seminorm, variation detracting property, absolutely continuous function

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Authors: Jianwei Ma, Diriba Gemechu

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In seismic data processing, attenuation of random noise is the basic step to improve quality of data for further application of seismic data in exploration and development in different gas and oil industries. The signal-to-noise ratio of the data also highly determines quality of seismic data. This factor affects the reliability as well as the accuracy of seismic signal during interpretation for different purposes in different companies. To use seismic data for further application and interpretation, we need to improve the signal-to-noise ration while attenuating random noise effectively. To improve the signal-to-noise ration and attenuating seismic random noise by preserving important features and information about seismic signals, we introduce the concept of anisotropic total fractional order denoising algorithm. The anisotropic total fractional order variation model defined in fractional order bounded variation is proposed as a regularization in seismic denoising. The split Bregman algorithm is employed to solve the minimization problem of the anisotropic total fractional order variation model and the corresponding denoising algorithm for the proposed method is derived. We test the effectiveness of theproposed method for synthetic and real seismic data sets and the denoised result is compared with F-X deconvolution and non-local means denoising algorithm.

Keywords: anisotropic total fractional order variation, fractional order bounded variation, seismic random noise attenuation, split Bregman algorithm

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Authors: O. Poleshchuk, E. Komarov

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This paper presents a regression model for interval type-2 fuzzy sets based on the least squares estimation technique. Unknown coefficients are assumed to be triangular fuzzy numbers. The basic idea is to determine aggregation intervals for type-1 fuzzy sets, membership functions of whose are low membership function and upper membership function of interval type-2 fuzzy set. These aggregation intervals were called weighted intervals. Low and upper membership functions of input and output interval type-2 fuzzy sets for developed regression models are considered as piecewise linear functions.

Keywords: interval type-2 fuzzy sets, fuzzy regression, weighted interval

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Authors: Mary Rosa Espinosa-Ochoa

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Some constructions appear suddenly in children’s speech and are productive from the beginning. These constructions are supported by others, previously acquired, with which they share semantic and pragmatic features. Thus, for example, the acquisition of the passive voice in German is supported by other constructions with which it shares the lexical verb sein (“to be”). This also occurs in Spanish, in the acquisition of the progressive aspectual periphrasis estar (“to be”) + verb root + -ndo (present participle), supported by locative constructions acquired earlier with the same verb. The periphrasis shares with the locative constructions not only the lexical verb estar, but also pragmatic relations. Both constructions can be used to answer the question ¿Dónde está? (“Where is he/she/it?”), whose answer could be either Está aquí (“He/she/it is here”) or Se está bañando (“He/she/it is taking a bath”).This study is a corpus-based analysis of two children (1;08-2;08) and the input directed to them: it proposes that the pragmatic and semantic support from previously-acquired constructions comes from the input, during interaction with others. This hypothesis is based on analysis of constructions with estar, whose use to express temporal change (which differentiates it from its counterpart ser [“to be”]), is given in variation sets, similar to those described by Küntay and Slobin (2002), that allow the child to perceive the change of place experienced by nouns that function as its grammatical subject. For example, at different points during a bath, the mother says: El jabón está aquí “The soap is here” (beginning of bath); five minutes later, the soap has moved, and the mother says el jabón está ahí “the soap is there”; the soap moves again later on and she says: el jabón está abajo de ti “the soap is under you”. “The soap” is the grammatical subject of all of these utterances. The Spanish verb + -ndo is a progressive phase aspect encoder of a dynamic state that generates a token. The verb + -ndo is also combined with verb estar to encode. It is proposed here that the phases experienced in interaction with the adult, in events related to the verb estar, allow a child to generate this dynamicity and token reading of the verb + -ndo. In this way, children begin to produce the periphrasis suddenly and productively, even though neither the periphrasis nor the verb + -ndo itself are frequent in adult speech.

Keywords: child language acquisition, input, variation sets, Spanish language

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Authors: Suparat Niwitpong, Sa-aat Niwitpong

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Statistical inference of normal mean with known coefficient of variation has been investigated recently. This phenomenon occurs normally in environment and agriculture experiments when the scientist knows the coefficient of variation of their experiments. In this paper, we constructed new confidence intervals for the normal population mean with known coefficient of variation. We also derived analytic expressions for the coverage probability of each confidence interval. To confirm our theoretical results, Monte Carlo simulation will be used to assess the performance of these intervals based on their coverage probabilities.

Keywords: confidence interval, coverage probability, expected length, known coefficient of variation

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Authors: Abdelmagid Basyouny Sakr

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Terminological variation is a reality and it is now recognized by terminologists. This paper investigates the terminological variation in the context of specialized economic texts in Italian. It aims to find whether certain patterns or tendencies can be derived from the analysis of these texts. Term variants pose two different kinds of difficulties. The first one is being able to recognize linguistic expressions that denote the same concept in running text. Another one lies in knowing which variant should be considered and for what purpose. This would help to differentiate between variants that could be candidates for inclusion in terminological resources and the ones which are synonyms or contextual variants. New insights about terminological variation in specialized texts could contribute to improve specialized dictionaries which will better account for the different ways in which a given thought is expressed.

Keywords: corpus linguistics, specialized communication, terms and concepts, terminological variation

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Authors: O. Boussoufi, K. Lamrini Uahabi, M. Atounti

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The main purpose of this paper is to calculate the fractal dimension of some Julia Sets and Mandelbrot Set in the Misiurewicz Points. Using Matlab to generate the Julia Sets images that match the Misiurewicz points and using a Fractal software, we were able to find different measures that characterize those fractals in textures and other features. We are actually focusing on fractal dimension and the error calculated by the software. When executing the given equation of regression or the log-log slope of image a Box Counting method is applied to the entire image, and chosen settings are available in a FracLAc Program. Finally, a comparison is done for each image corresponding to the area (boundary) where Misiurewicz Point is located.

Keywords: box counting, FracLac, fractal dimension, Julia Sets, Mandelbrot Set, Misiurewicz Points

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Authors: Dayane de Almeida

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This work aims at presenting a study that demonstrates the usability of categories of analysis from Discourse Semiotics – also known as Greimassian Semiotics in authorship cases in forensic contexts. It is necessary to know if the categories examined in semiotic analysis (the ‘grammar’ of the content plane) can distinguish authors. Thus, a study with 4 sets of texts from a corpus of ‘not on demand’ written samples (those texts differ in formality degree, purpose, addressees, themes, etc.) was performed. Each author contributed with 20 texts, separated into 2 groups of 10 (Author1A, Author1B, and so on). The hypothesis was that texts from a single author were semiotically more similar to each other than texts from different authors. The assumptions and issues that led to this idea are as follows: -The features analyzed in authorship studies mostly relate to the expression plane: they are manifested on the ‘surface’ of texts. If language is both expression and content, content would also have to be considered for more accurate results. Style is present in both planes. -Semiotics postulates the content plane is structured in a ‘grammar’ that underlies expression, and that presents different levels of abstraction. This ‘grammar’ would be a style marker. -Sociolinguistics demonstrates intra-speaker variation: an individual employs different linguistic uses in different situations. Then, how to determine if someone is the author of several texts, distinct in nature (as it is the case in most forensic sets), when it is known intra-speaker variation is dependent on so many factors?-The idea is that the more abstract the level in the content plane, the lower the intra-speaker variation, because there will be a greater chance for the author to choose the same thing. If two authors recurrently chose the same options, differently from one another, it means each one’s option has discriminatory power. -Size is another issue for various attribution methods. Since most texts in real forensic settings are short, methods relying only on the expression plane tend to fail. The analysis of the content plane as proposed by greimassian semiotics would be less size-dependable. -The semiotic analysis was performed using the software Corpus Tool, generating tags to allow the counting of data. Then, similarities and differences were quantitatively measured, through the application of the Jaccard coefficient (a statistical measure that compares the similarities and differences between samples). The results showed the hypothesis was confirmed and, hence, the grammatical categories of the content plane may successfully be used in questioned authorship scenarios.

Keywords: authorship attribution, content plane, forensic linguistics, greimassian semiotics, intraspeaker variation, style

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Authors: Shinji Oouchi, Hajime Nomura, Kung-Da Wu, Jui-Pin Hung

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This paper presents the variation of the dynamic characteristics of a spindle with the change of bearing preload. The correlations between the variation of bearing preload and fundamental modal parameters were first examined by conducting vibration tests on physical spindle units. Experimental measurements show that the dynamic compliance and damping ratio associated with the dominating modes were affected to vary with variation of the bearing preload. When the bearing preload was slightly deviated from a standard value, the modal frequency and damping ability also vary to different extent, which further enable the spindle to perform with different compliance. For the spindle used in this study, a standard preload value set on bearings would enable the spindle to behave a higher stiffness as compared with others with a preload variation. This characteristic can be served as a reference to examine the variation of bearing preload of spindle in assemblage or operation.

Keywords: dynamic compliance, bearing preload, modal damping, standard preload

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Authors: J. K. Kavitha, D. Manjula, U. Kanimozhi

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Mining frequent and high utility item sets have gained much significance in the recent years. When the data arrives sporadically, incremental and interactive rule mining and utility mining approaches can be adopted to handle user’s dynamic environmental needs and avoid redundancies, using previous data structures, and mining results. The dependence on recommendation systems has exponentially risen since the advent of search engines. This paper proposes a model for building a recommendation system that suggests frequent and high utility item sets over dynamic datasets for a cluster based location prediction strategy to predict user’s trajectories using the Efficient Incremental Rule Mining (EIRM) algorithm and the Fast Update Utility Pattern Tree (FUUP) algorithm. Through comprehensive evaluations by experiments, this scheme has shown to deliver excellent performance.

Keywords: data sets, recommendation system, utility item sets, frequent item sets mining

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Authors: Vadim E. Levit, Eugen Mandrescu

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A graph is well-covered if all its maximal independent sets are of the same size. A well-covered graph is 1-well-covered if deletion of every vertex of the graph leaves it well-covered. It is known that a graph without isolated vertices is 1-well-covered if and only if every two disjoint independent sets are included in two disjoint maximum independent sets. Well-covered graphs are related to combinatorial commutative algebra (e.g., every Cohen-Macaulay graph is well-covered, while each Gorenstein graph without isolated vertices is 1-well-covered). Our intent is to construct several infinite families of 1-well-covered graphs using the following known graph operations: corona, join, and rooted product of graphs. Adopting some known techniques used to advantage for well-covered graphs, one can prove that: if the graph G has no isolated vertices, then the corona of G and H is 1-well-covered if and only if H is a complete graph of order two at least; the join of the graphs G and H is 1-well-covered if and only if G and H have the same independence number and both are 1-well-covered; if H satisfies the property that every three pairwise disjoint independent sets are included in three pairwise disjoint maximum independent sets, then the rooted product of G and H is 1-well-covered, for every graph G. These findings show not only how to generate some more families of 1-well-covered graphs, but also that, to this aim, sometimes, one may use graphs that are not necessarily 1-well-covered.

Keywords: maximum independent set, corona, concatenation, join, well-covered graph

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Authors: Md Al Masum Bhuiyan, Maria C. Mariani, Osei K. Tweneboah

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In the present work, we develop a technique for estimating the volatility of financial time series by using stochastic differential equation. Taking the daily closing prices from developed and emergent stock markets as the basis, we argue that the incorporation of stochastic volatility into the time-varying parameter estimation significantly improves the forecasting performance via Maximum Likelihood Estimation. While using the technique, we see the long-memory behavior of data sets and one-step-ahead-predicted log-volatility with ±2 standard errors despite the variation of the observed noise from a Normal mixture distribution, because the financial data studied is not fully Gaussian. Also, the Ornstein-Uhlenbeck process followed in this work simulates well the financial time series, which aligns our estimation algorithm with large data sets due to the fact that this algorithm has good convergence properties.

Keywords: financial time series, maximum likelihood estimation, Ornstein-Uhlenbeck type models, stochastic volatility model

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Authors: Maheen Zia

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Near the early twenty-first century, LEGO decided to diversify its product range which resulted in more specific and single-outcome sets occupying the store shelves than classic kits having fairly all-purpose bricks. Earlier, LEGOs came with more bricks and lesser instructions. Today, there are more single kits being produced and sold, which come with a strictly defined set of guidelines. If one set is used to make a car, the same bricks cannot be put together to produce any other article. Earlier, multiple bricks gave children a chance to be imaginative, think of new items and construct them (by just putting the same pieces differently). The new products are less open-ended and offer a limited possibility for players in both designing and realizing those designs. The article reviews (in the light of existing research) how classic LEGO sets could help enhance a child’s creativity in comparison with single sets, which allow a player to interact (not experiment) with the bricks.

Keywords: constructive play, creativity, LEGO, play-based learning

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Authors: Avaneesh Vaishwar, Badam Singh Kushvah, Devi Prasad Mishra

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We studied the variation in orbital elements of Mars and Jupiter for a time span of 200 thousand years by using secular theory. Here we took Sun oblateness into account and considered the first two zonal gravity constants (J2 and J4) for showing the effect of Sun oblateness on the orbital elements of Mars and Jupiter. We found that in both cases (with and without Sun oblateness) the variation in orbital elements of Mars and Jupiter is periodic moreover in case of the Sun oblateness, the period of variation in orbital elements is decreasing for both the planets.

Keywords: lagrange's planetary equation, orbital elements, planetary system, secular theory

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Authors: A. Samer Ezeldin, Jwanda M. El Sarag

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Variation orders are of great importance in any construction project. Variation orders are defined as any change in the scope of works of a project that can be an addition omission, or even modification. This paper investigates the variation orders that occur during construction projects in Egypt. The literature review represents a comparison of causes of variation orders among Egypt, Tanzania, Nigeria, Malaysia and the United Kingdom. A classification of occurrence of variation orders due to owner related factors, consultant related factors and other factors are signified in the literature review. These classified events that lead to variation orders were introduced in a survey with 19 events to observe their frequency of occurrence, and their time and cost impacts. The survey data was obtained from 87 participants that included clients, consultants, and contractors and a database of 42 scenarios was created. A model is then developed to help assist project managers in predicting the frequency of variations and account for a budget for any additional costs and minimize any delays that can take place. Two experts with more than 25 years of experience were given the model to verify that the model was working effectively. The model was then validated on a residential compound that was completed in July 2016 to prove that the model actually produces acceptable results.

Keywords: construction, cost impact, Egypt, time impact, variation orders

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Authors: Emma K. Sales, Nilda G. Butardo

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The project was undertaken to determine the effects of modified tissue culture protocols e.g. age of culture and hormone levels (2,4-D) in generating somaclonal variation. Moreover, the utility of molecular markers (SSR and MSAP) in sorting off types/somaclones were investigated. Results show that somaclonal variation is in effect due to prolonged subculture and high 2,4-D concentration. The resultant variation was observed to be due to high level of methylation events specifically cytosine methylation either at the internal or external cytosine and was identified by methylation sensitive amplification polymorphism (MSAP). Simple sequence repeats (SSR) on the other hand, was able to associate a marker to a trait of interest. These therefore, show that molecular markers can be an important tool in sorting out variation/mutants at an early stage.

Keywords: methylation, MSAP, somaclones, SSR, subculture, 2, 4-D

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Authors: Younies Saeed Hassan Mahmoud, Mai Mabrouk, Elsayed Sallam

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Analysing DNA microarray data sets is a great challenge, which faces the bioinformaticians due to the complication of using statistical and machine learning techniques. The challenge will be doubled if the microarray data sets contain missing data, which happens regularly because these techniques cannot deal with missing data. One of the most important data analysis process on the microarray data set is feature selection. This process finds the most important genes that affect certain disease. In this paper, we introduce a technique for imputing the missing data in microarray data sets while performing feature selection.

Keywords: DNA microarray, feature selection, missing data, bioinformatics

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Authors: M. Fadlallah, G. Ghibaudo, C. G. Theodorou

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The dynamic variation in memory devices such as the Static Random Access Memory can give errors in read or write operations. In this paper, the effect of low-frequency and random telegraph noise on the dynamic variation of one SRAM cell is detailed. The effect on circuit noise, speed, and length of time of processing is examined, using the Supply Read Retention Voltage and the Read Static Noise Margin. New test run methods are also developed. The obtained results simulation shows the importance of noise caused by dynamic variation, and the impact of Random Telegraph noise on SRAM variability is examined by evaluating the statistical distributions of Random Telegraph noise amplitude in the pull-up, pull-down. The threshold voltage mismatch between neighboring cell transistors due to intrinsic fluctuations typically contributes to larger reductions in static noise margin. Also the contribution of each of the SRAM transistor to total dynamic variation has been identified.

Keywords: low-frequency noise, random telegraph noise, dynamic variation, SRRV

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Authors: Nur Aziza Luxfiati

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Clustering is partitioning data sets into sub-sets or groups in such a way that elements certain properties have shared property settings with a high level of similarity within one group and a low level of similarity between groups. . The K-Means algorithm is one of thealgorithmsclustering as a grouping tool that is most widely used in scientific and industrial applications because the basic idea of the kalgorithm is-means very simple. In this research, applying the technique of clustering using the k-means algorithm as a method of solving the problem of national development imbalances between regions in Central Java Province based on macroeconomic indicators. The data sample used is secondary data obtained from the Central Java Provincial Statistics Agency regarding macroeconomic indicator data which is part of the publication of the 2019 National Socio-Economic Survey (Susenas) data. score and determine the number of clusters (k) using the elbow method. After the clustering process is carried out, the validation is tested using themethodsBetween-Class Variation (BCV) and Within-Class Variation (WCV). The results showed that detection outlier using z-score normalization showed no outliers. In addition, the results of the clustering test obtained a ratio value that was not high, namely 0.011%. There are two district/city clusters in Central Java Province which have economic similarities based on the variables used, namely the first cluster with a high economic level consisting of 13 districts/cities and theclustersecondwith a low economic level consisting of 22 districts/cities. And in the cluster second, namely, between low economies, the authors grouped districts/cities based on similarities to macroeconomic indicators such as 20 districts of Gross Regional Domestic Product, with a Poverty Depth Index of 19 districts, with 5 districts in Human Development, and as many as Open Unemployment Rate. 10 districts.

Keywords: clustering, K-Means algorithm, macroeconomic indicators, inequality, national development

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Authors: Salem Alsanusi, Loubna Bentaher

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Response Surface Methods (RSM) provide statistically validated predictive models that can then be manipulated for finding optimal process configurations. Variation transmitted to responses from poorly controlled process factors can be accounted for by the mathematical technique of propagation of error (POE), which facilitates ‘finding the flats’ on the surfaces generated by RSM. The dual response approach to RSM captures the standard deviation of the output as well as the average. It accounts for unknown sources of variation. Dual response plus propagation of error (POE) provides a more useful model of overall response variation. In our case, we implemented this technique in predicting compressive strength of concrete of 28 days in age. Since 28 days is quite time consuming, while it is important to ensure the quality control process. This paper investigates the potential of using design of experiments (DOE-RSM) to predict the compressive strength of concrete at 28th day. Data used for this study was carried out from experiment schemes at university of Benghazi, civil engineering department. A total of 114 sets of data were implemented. ACI mix design method was utilized for the mix design. No admixtures were used, only the main concrete mix constituents such as cement, coarse-aggregate, fine aggregate and water were utilized in all mixes. Different mix proportions of the ingredients and different water cement ratio were used. The proposed mathematical models are capable of predicting the required concrete compressive strength of concrete from early ages.

Keywords: mix proportioning, response surface methodology, compressive strength, optimal design

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Authors: Ivan Belik

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In terms of social networks split graphs correspond to the variety of interpersonal and intergroup relations. In this paper we analyse the interaction between the cliques (socially strong and trusty groups) and the independent sets (fragmented and non-connected groups of people) as the basic components of any split graph. Based on the Semi-Lagrangean relaxation for the k-cardinality assignment problem we show the way of how to minimize the socially risky interactions between the cliques and the independent sets within the social network.

Keywords: cliques, independent sets, k-cardinality assignment, social networks, split graphs

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Authors: Subir Gupta, Subhas Ganguly

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In this paper, we demonstrate the new area of application of image processing in metallurgical images to develop the more opportunity for structure-property correlation based approaches of alloy design. The present exercise focuses on the development of image processing tools suitable for phrase segmentation, grain boundary detection and recognition of micro-constituents in SEM micrographs of ferrite and pearlite steels. A comprehensive data of micrographs have been experimentally developed encompassing the variation of ferrite and pearlite volume fractions and taking images at different magnification (500X, 1000X, 15000X, 2000X, 3000X and 5000X) under scanning electron microscope. The variation in the volume fraction has been achieved using four different plain carbon steel containing 0.1, 0.22, 0.35 and 0.48 wt% C heat treated under annealing and normalizing treatments. The obtained data pool of micrographs arbitrarily divided into two parts to developing training and testing sets of micrographs. The statistical recognition features for ferrite and pearlite constituents have been developed by learning from training set of micrographs. The obtained features for microstructure pattern recognition are applied to test set of micrographs. The analysis of the result shows that the developed strategy can successfully detect the micro constitutes across the wide range of magnification and variation of volume fractions of the constituents in the structure with an accuracy of about +/- 5%.

Keywords: SEM micrograph, metallurgical image processing, ferrite pearlite steel, microstructure

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Authors: Maciej Zaręba, Sławomir Lasota

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Knowing the degree of dependencies between the sets of input signals and selected sets of indicators that measure a production system's effectiveness is of great importance in the industry. This paper introduces the SELM method that enables the selection of sets of input signals, which affects the most the selected subset of indicators that measures the effectiveness of a production system. For defined set of output indicators, the method quantifies the impact of input signals that are gathered in the continuous monitoring production system.

Keywords: manufacturing operation management, signal relationship, continuous monitoring, production systems

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Authors: Can Xiao, Ouanhong Jiang

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Based on the two instruction sets of complex instruction set computing (CISC) and reduced instruction set computing (RISC), processors developed in their respective “expertise” fields. This paper will summarize research on the differences in performance and energy efficiency between CISC and RISC and strive to eliminate the influence of peripheral configuration factors. We will discuss whether processor performance is centered around instruction sets or implementation. In addition, the rapidly developing RISC-V poses a challenge to existing models. We will analyze research results, analyze the impact of instruction sets themselves, and finally make suggestions for the development of RISC-V.

Keywords: ISA, RISC-V, ARM, X86, power, energy efficiency

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Authors: Apkar Salatian

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To relieve the burden of reasoning on a point to point basis, in many domains there is a need to reduce large and noisy data sets into trends for qualitative reasoning. In this paper we propose and describe a new architectural design pattern called REDUCER for reducing large and noisy data sets that can be tailored for particular situations. REDUCER consists of 2 consecutive processes: Filter which takes the original data and removes outliers, inconsistencies or noise; and Compression which takes the filtered data and derives trends in the data. In this seminal article, we also show how REDUCER has successfully been applied to 3 different case studies.

Keywords: design pattern, filtering, compression, architectural design

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Authors: N. D. Iswarya, M. A. Maluk Mohamed, N. Vijaya

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Grid is infrastructure that allows the deployment of distributed data in large size from multiple locations to reach a common goal. Scheduling data intensive applications becomes challenging as the size of data sets are very huge in size. Only two solutions exist in order to tackle this challenging issue. First, computation which requires huge data sets to be processed can be transferred to the data site. Second, the required data sets can be transferred to the computation site. In the former scenario, the computation cannot be transferred since the servers are storage/data servers with little or no computational capability. Hence, the second scenario can be considered for further exploration. During scheduling, transferring huge data sets from one site to another site requires more network bandwidth. In order to mitigate this issue, this work focuses on incorporating cognitive science in scheduling. Cognitive Science is the study of human brain and its related activities. Current researches are mainly focused on to incorporate cognitive science in various computational modeling techniques. In this work, the problem solving approach of human brain is studied and incorporated during the data intensive scheduling in grid environments. Here, a cognitive engine is designed and deployed in various grid sites. The intelligent agents present in CE will help in analyzing the request and creating the knowledge base. Depending upon the link capacity, decision will be taken whether to transfer data sets or to partition the data sets. Prediction of next request is made by the agents to serve the requesting site with data sets in advance. This will reduce the data availability time and data transfer time. Replica catalog and Meta data catalog created by the agents assist in decision making process.

Keywords: data grid, grid workflow scheduling, cognitive artificial intelligence

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