Search results for: statistical approaches

Authors: Zamri Abu Bakar Zamri, Normaly Kamal Ismail Normaly, Mohd Izani Mohamed Rawi Izani

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Malay noun compound are phrases that consist of two or more nouns. The key characteristic behind noun compounds lies on its frequent occurrences within the text. Therefore, extracting these noun compounds is essential for several domains of research such as Information Retrieval, Sentiment Analysis and Question Answering. Many research efforts have been proposed in terms of extracting Malay noun compounds using linguistic and statistical approaches. Most of the existing methods have concentrated on the extraction of bi-gram noun+noun compound. However, extracting noun+verb, noun+adjective and noun+prepositional is challenging due to the difficulty of selecting an appropriate method with effective results. Thus, there is still room for improvement in terms of enhancing the effectiveness of compound word extraction. Therefore, this study proposed a combination of linguistic approach and statistical measures in order to enhance the extraction of compound words. Several preprocessing steps are involved including normalization, tokenization, and stemming. The linguistic approach that has been used in this study is Part-of-Speech (POS) tagging. In addition, a new linguistic pattern for named entities has been utilized using a list of Malays named entities in order to enhance the linguistic approach in terms of noun compound recognition. The proposed statistical measures consists of NC-value, NTC-value and NLC value.

Keywords: Compound Word, Noun Compound, Linguistic Approach, Statistical Approach

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Authors: F. Berna Benli, Özgür Keskin

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Lately, many mathematicians have been studied the statistical convergence of a sequence of fuzzy numbers. We know that Lambda-statistically convergence is a kind of convergence between ordinary convergence and statistical convergence. In this paper, we will introduce the new kind of convergence such as λ-levelwise statistical convergence. Then, we will define the concept of the λ-levelwise statistical cluster and limit points of a sequence of fuzzy numbers. Also, we will discuss the relations between the sets of λ-levelwise statistical cluster points and λ-levelwise statistical limit points of sequences of fuzzy numbers. This work has been extended in this paper, where some relations have been considered such that when lambda-statistical limit inferior and lambda-statistical limit superior for lambda-statistically convergent sequences of fuzzy numbers are equal. Furthermore, lambda-statistical boundedness condition for different sequences of fuzzy numbers has been studied.

Keywords: fuzzy number, λ-levelwise statistical cluster points, λ-levelwise statistical convergence, λ-levelwise statistical limit points, λ-statistical cluster points, λ-statistical convergence, λ-statistical limit points

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Authors: Tamanna Goyal, Divya Bansal, Sanjeev Sofat

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In world-threatening terrorist attacks, where early detection, distinction, and prediction are effective diagnosis techniques and for functionally accurate and precise analysis of terrorism data, there are so many data mining & statistical approaches to assure accuracy. The computational extraction of derived patterns is a non-trivial task which comprises specific domain discovery by means of sophisticated algorithm design and analysis. This paper proposes an approach for similarity extraction by obtaining the useful attributes from the available datasets of terrorist attacks and then applying feature selection technique based on the statistical impurity measures followed by clustering techniques on the basis of similarity measures. On the basis of degree of participation of attributes in the rules, the associative dependencies between the attacks are analyzed. Consequently, to compute the similarity among the discovered rules, we applied a weighted similarity measure. Finally, the rules are grouped by applying using hierarchical clustering. We have applied it to an open source dataset to determine the usability and efficiency of our technique, and a literature search is also accomplished to support the efficiency and accuracy of our results.

Keywords: association rules, clustering, similarity measure, statistical approaches

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Authors: Bernardo C. P. Albuquerque, Darym J. F. Campos

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Increasing our ability to solve complex engineering problems is directly related to the processing capacity of computers. By means of such equipments, one is able to fast and accurately run numerical algorithms. Besides the increasing interest in numerical simulations, probabilistic approaches are also of great importance. This way, statistical tools have shown their relevance to the modelling of practical engineering problems. In general, statistical approaches to such problems consider that the random variables involved follow a normal distribution. This assumption tends to provide incorrect results when skew data is present since normal distributions are symmetric about their means. Thus, in order to visualize and quantify this aspect, 9 statistical distributions (symmetric and skew) have been considered to model a hypothetical slope stability problem. The data modeled is the friction angle of a superficial soil in Brasilia, Brazil. Despite the apparent universality, the normal distribution did not qualify as the best fit. In the present effort, data obtained in consolidated-drained triaxial tests and saturated direct shear tests have been modeled and used to analytically derive the probability density function (PDF) of the safety factor of a hypothetical slope based on Mohr-Coulomb rupture criterion. Therefore, based on this analysis, it is possible to explicitly derive the failure probability considering the friction angle as a random variable. Furthermore, it is possible to compare the stability analysis when the friction angle is modelled as a Dagum distribution (distribution that presented the best fit to the histogram) and as a Normal distribution. This comparison leads to relevant differences when analyzed in light of the risk management.

Keywords: statistical slope stability analysis, skew distributions, probability of failure, functions of random variables

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Authors: Balazs Somodi, Balazs Kovesdi

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In the research praxis of civil engineering the statistical evaluation of experimental and numerical investigations is an essential task in order to compare the experimental and numerical resistances of a specific structural problem with the proposed resistances of the standards. However, in the standards and in the international literature there are several different safety factor evaluation methods that can be used to check the necessary safety level (e.g.: 5% quantile level, 2.3% quantile level, 1‰ quantile level, γM partial safety factor, γM* partial safety factor, β reliability index). Moreover, in the international literature different calculation methods could be found even for the same safety factor as well. In the present study the flexural buckling resistance of high strength steel (HSS) welded closed sections are analyzed. The authors investigated the flexural buckling resistances of the analyzed columns by laboratory experiments. In the present study the safety levels of the obtained experimental resistances are calculated based on several safety approaches and compared with the EN 1990. The results of the different safety approaches are compared and evaluated. Based on the evaluation tendencies are identified and the differences between the statistical evaluation methods are explained.

Keywords: flexural buckling, high strength steel, partial safety factor, statistical evaluation

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Authors: Benyamin Ahmadnia, Javier Serrano

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In this paper we compare two different approaches for translating from Persian to Spanish, as a language pair with scarce parallel corpus. The first approach involves direct transfer using an statistical machine translation system, which is available for this language pair. The second approach involves translation through English, as a pivot language, which has more translation resources and more advanced translation systems available. The results show that, it is possible to achieve better translation quality using English as a pivot language in either approach outperforms direct translation from Persian to Spanish. Our best result is the pivot system which scores higher than direct translation by (1.12) BLEU points.

Keywords: statistical machine translation, direct translation approach, pivot language translation approach, parallel corpus

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Authors: Ali M. Al-Shaery

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The purpose of this paper is to address the functions of sustainability dimensions in city information modelling and to present the required sustainability criteria that support establishing a sustainable planning framework for enhancing existing cities and developing future smart cities. The paper is divided into two sections. The first section is based on the examination of a wide and extensive array of cross-disciplinary literature in the last decade and a half to conceptualize the terms ‘sustainable’ and ‘smart city,' and map their associated criteria to city information modelling. The second section is based on analyzing two approaches relating to city information modelling, namely statistical and dynamic approaches, and their suitability in the development of cities’ action plans. The paper argues that the use of statistical approaches to embedding sustainability dimensions in city information modelling have limited value. Despite the popularity of such approaches in addressing other dimensions like utility and service management in development and action plans of the world cities, these approaches are unable to address the dynamics across various city sectors with regards to economic, environmental and social criteria. The paper suggests an integrative dynamic and cross-disciplinary planning approach to embedding sustainability dimensions in city information modelling frameworks. Such an approach will pave the way towards optimal planning and implementation of priority actions of projects and investments. The approach can be used to achieve three main goals: (1) better development and action plans for world cities (2) serve the development of an integrative dynamic and cross-disciplinary framework that incorporates economic, environmental and social sustainability criteria and (3) address areas that require further attention in the development of future sustainable and smart cities. The paper presents an innovative approach for city information modelling and a well-argued, balanced hierarchy of sustainability criteria that can contribute to an area of research which is still in its infancy in terms of development and management.

Keywords: information modelling, smart city, sustainable city, sustainability dimensions, sustainability criteria, city development planning

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Authors: Fathi M. O. Hamed, Salma F. Elkofhaifee

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The aim of this work is to detect geometrical shape objects in an image. In this paper, the object is considered to be as a circle shape. The identification requires find three characteristics, which are number, size, and location of the object. To achieve the goal of this work, this paper presents an algorithm that combines from some of statistical approaches and image analysis techniques. This algorithm has been implemented to arrive at the major objectives in this paper. The algorithm has been evaluated by using simulated data, and yields good results, and then it has been applied to real data.

Keywords: image processing, median filter, projection, scale-space, segmentation, threshold

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Authors: Petros Roussos

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The present study focused on students' statistical reasoning related to Null Hypothesis Statistical Testing and p-values. Its objective was to test the hypothesis that neither the place (classroom, at a distance, online) nor the medium that actually supports the learning (ICT, internet, books) has an effect on understanding of statistical concepts. In addition, it was expected that students' attitudes towards statistics would not predict understanding of statistical concepts. The sample consisted of 385 undergraduate and postgraduate students from six state and private universities (five in Greece and one in Cyprus). Students were administered two questionnaires: a) the Greek version of the Survey of Attitudes Toward Statistics, and b) a short instrument which measures students' understanding of statistical significance and p-values. Results suggest that attitudes towards statistics do not predict students' understanding of statistical concepts, whereas the medium did not have an effect.

Keywords: attitudes towards statistics, blended learning, e-learning, statistical reasoning

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Authors: H. Nouri, S. Chavoshi Borujeni, S. Anderson, S. Beecham, P. Sutton

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The potential risk of salt leaching through wastewater irrigation is of concern for most local governments and city councils. Despite the necessity of salinity monitoring and management in urban greenery, most attention has been on agricultural fields. This study was defined to investigate the capability and feasibility of monitoring and predicting soil salinity using near sensing and remote sensing approaches using EM38 surveys, and high-resolution multispectral image of WorldView3. Veale Gardens within the Adelaide Parklands was selected as the experimental site. The results of the near sensing investigation were validated by testing soil salinity samples in the laboratory. Over 30 band combinations forming salinity indices were tested using image processing techniques. The outcomes of the remote sensing and near sensing approaches were compared to examine whether remotely sensed salinity indicators could map and predict the spatial variation of soil salinity through a potential statistical model. Statistical analysis was undertaken using the Stata 13 statistical package on over 52,000 points. Several regression models were fitted to the data, and the mixed effect modelling was selected the most appropriate one as it takes to account the systematic observation-specific unobserved heterogeneity. Results showed that SAVI (Soil Adjusted Vegetation Index) was the only salinity index that could be considered as a predictor for soil salinity but further investigation is needed. However, near sensing was found as a rapid, practical and realistically accurate approach for salinity mapping of heterogeneous urban vegetation.

Keywords: WorldView3, remote sensing, EM38, near sensing, urban green spaces, green smart cities

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Authors: Neha Bhardwaj

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In this paper, we consider positive linear operators and study the Voronovskaya type result of the operator then obtain an error estimate in terms of the higher order modulus of continuity of the function being approximated and its A-statistical convergence. Also, we compute the corresponding rate of A-statistical convergence for the linear positive operators.

Keywords: Poisson distribution, Voronovskaya, modulus of continuity, a-statistical convergence

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Authors: Lukanda Kalobo

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In South Africa, the High School Mathematics Curriculum provides teachers with specific aims and skills to be developed which involves the understanding about the measures of central tendency. The exploration begins with the definitions of statistical literacy, measurement of central tendency and a discussion on why statistical literacy is essential today. It furthermore discusses the statistical literacy basics involved in understanding the concepts of measures of central tendency. The statistical literacy test on the measures of central tendency, was used to collect data which was administered to 78 first year students direct from high schools. The results indicated that students seemed to have forgotten about the statistical literacy in understanding the concepts of measure of central tendency after completing their high school study. The authors present inferences regarding the alignment between statistical literacy and the understanding of the concepts about the measures of central tendency, leading to the conclusion that there is a need to provide in-service and pre-service training.

Keywords: conceptual understanding, mean, median, mode, statistical literacy

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Authors: Sheikh Omar Sillah

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Introduction: Monitoring is an important means of ensuring the smooth implementation and quality of clinical trials. For many years, traditional site monitoring approaches have been critical in detecting data errors but not optimal in identifying fabricated and implanted data as well as non-random data distributions that may significantly invalidate study results. The objective of this paper was to provide recommendations based on best statistical monitoring practices for detecting data-integrity issues suggestive of fabrication and implantation early in the study conduct to allow implementation of meaningful corrective and preventive actions. Methodology: Electronic bibliographic databases (Medline, Embase, PubMed, Scopus, and Web of Science) were used for the literature search, and both qualitative and quantitative studies were sought. Search results were uploaded into Eppi-Reviewer Software, and only publications written in the English language from 2012 were included in the review. Gray literature not considered to present reproducible methods was excluded. Results: A total of 18 peer-reviewed publications were included in the review. The publications demonstrated that traditional site monitoring techniques are not efficient in detecting data anomalies. By specifying project-specific parameters such as laboratory reference range values, visit schedules, etc., with appropriate interactive data monitoring, statistical monitoring can offer early signals of data anomalies to study teams. The review further revealed that statistical monitoring is useful to identify unusual data patterns that might be revealing issues that could impact data integrity or may potentially impact study participants' safety. However, subjective measures may not be good candidates for statistical monitoring. Conclusion: The statistical monitoring approach requires a combination of education, training, and experience sufficient to implement its principles in detecting data anomalies for the statistical aspects of a clinical trial.

Keywords: statistical monitoring, data anomalies, clinical trials, traditional monitoring

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Authors: Jalel Khelil

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In order to improve reliability of Gas Turbine machine especially its generator equipment, a fault diagnosis system based on fuzzy approach is proposed. Three various methods namely K-NN (K-nearest neighbors), F-KNN (Fuzzy K-nearest neighbors) and FNM (Fuzzy nearest mean) are adopted to provide the measurement of relative strength of vibration defaults. Both applications consist of two major steps: Feature extraction and default classification. 09 statistical features are extracted from vibration signals. 03 different classes are used in this study which describes vibrations condition: Normal, unbalance defect, and misalignment defect. The use of the fuzzy approaches and the classification results are discussed. Results show that these approaches yield high successful rates of vibration default classification.

Keywords: fault diagnosis, fuzzy classification k-nearest neighbor, vibration

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Authors: Mohammed Kafaji

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This paper aims to investigate the influence of quality of education and quality of research, provided by local educational institutions, on the adoption of Information and Communication Technology (ICT) in managing business operations for companies in Saudi market. A model was developed and tested using data collected from 138 CEO’s of foreign companies in diverse business sectors. The data is analysed and managed using multivariate approaches through standard statistical packages. The results showed that educational quality has little contribution to the ICT adoption while research quality seems to play a more prominent role. These results are analysed in terms of business environment and market constraints and further extended to the perceived effectiveness of applied pedagogical approaches in schools and universities.

Keywords: quality of education, quality of research, mediation, domestic competition, ICT adoption

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Authors: P. Pötters, A. Marquet, B. Leyendecker

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The objective of this paper is to investigate different implementation approaches for the implementation of Lean production in companies. Furthermore, a structured overview of those different approaches is to be made. Therefore, the present work is intended to answer the following research question: What differences and similarities exist between the various systematic approaches and phase models for the implementation of Lean Production? To present various approaches for the implementation of Lean Production discussed in the literature, a qualitative content analysis was conducted. Within the framework of a qualitative survey, a selection of texts dealing with lean production and its introduction was examined. The analysis presents different implementation approaches from the literature, covering the descriptive aspect of the study. The study also provides insights into similarities and differences among the implementation approaches, which are drawn from the analysis of latent text contents and author interpretations. In this study, the focus is on identifying differences and similarities among systemic approaches for implementing Lean Production. The research question takes into account the main object of consideration, objectives pursued, starting point, procedure, and endpoint of the implementation approach. The study defines the concept of Lean Production and presents various approaches described in literature that companies can use to implement Lean Production successfully. The study distinguishes between five systemic implementation approaches and seven phase models to help companies choose the most suitable approach for their implementation project. The findings of this study can contribute to enhancing transparency regarding the existing approaches for implementing Lean Production. This can enable companies to compare and contrast the available implementation approaches and choose the most suitable one for their specific project.

Keywords: implementation, lean production, phase models, systematic approaches

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Authors: António Fiúza, Aurora Futuro, Joana Monteiro, Joaquim Góis

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Lepidolite is an important lithium mineral that, to the author’s best knowledge, has not been used to produce lithium hydroxide, which is necessary for energy conversion to electric vehicles. Alkaline leaching of lithium concentrates allows the establishment of a production diagram avoiding most of the environmental drawbacks that are associated with the usage of acid reagents. The tested processes involve a pretreatment by digestion at high temperatures with additives, followed by leaching at hot atmospheric pressure. The solutions obtained must be compatible with solutions from the leaching of spodumene concentrates, allowing the development of a common treatment diagram, an important accomplishment for the feasible exploitation of Portuguese resources. Statistical programming and interpretation techniques minimize the laboratory effort required by conventional approaches and allow phenomenological comprehension.

Keywords: alkaline leaching, lithium, research design, statistical interpretation

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Authors: Vladimir S. Timofeev

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In this article the problem of distributional moments estimation is considered. The new approach of moments estimation based on usage of the characteristic function is proposed. By statistical simulation technique, author shows that new approach has some robust properties. For calculation of the derivatives of characteristic function there is used numerical differentiation. Obtained results confirmed that author’s idea has a certain working efficiency and it can be recommended for any statistical applications.

Keywords: characteristic function, distributional moments, robustness, outlier, statistical estimation problem, statistical simulation

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Authors: Abdullah A. H. Alzahrani, Majd Zohri Yafi, Fawaz K. Alarfaj

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Unified Modelling Language (UML) is a software modelling language that is widely used and accepted. One significant drawback, of which, is that the language lacks formality. This makes carrying out any type of rigorous analysis difficult process. Many researchers attempt to introduce their approaches to formalize UML diagrams. However, it is always hard to decide what language and/or approach to use. Therefore, in this paper, we highlight some of the advantages and disadvantages of number of those approaches. We also try to compare different counterpart approaches. In addition, we draw some guidelines to help in choosing the suitable approach. Special concern is given to the formalization of the static aspects of UML shown is class diagrams.

Keywords: UML formalization, object constraints language, description logic, z language

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Authors: Petar Sarajcev, Josip Vasilj, Damir Jakus

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This paper presents a novel statistical description of the counterpoise effective length due to lightning surges, where the (impulse) effective length had been obtained by means of regressive formulas applied to the transient simulation results. The effective length is described in terms of a statistical distribution function, from which median, mean, variance, and other parameters of interest could be readily obtained. The influence of lightning current amplitude, lightning front duration, and soil resistivity on the effective length has been accounted for, assuming statistical nature of these parameters. A method for determining the optimal counterpoise length, in terms of the statistical impulse effective length, is also presented. It is based on estimating the number of dangerous events associated with lightning strikes. Proposed statistical description and the associated method provide valuable information which could aid the design engineer in optimising physical lengths of counterpoises in different grounding arrangements and soil resistivity situations.

Keywords: counterpoise, grounding conductor, effective length, lightning, Monte Carlo method, statistical distribution

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Authors: Maurice Steinhoff, Lucas Costantino, Dominik Kanbach

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Measurement approaches to corporate venturing (CV) success are highly diverse in the extant literature. Furthermore, these approaches rarely build on each other, making it difficult to derive comparable conclusions about CV outcomes. Employing a systematic literature review of three decades of research, the objective of this study is to provide transparency and structure in the broad field of CV research. Subsequently, the paper examines 28 studies in detail, resulting in two main contributions to the research field. First, three structural dimensions of measurement approaches are derived from the studies in the sample, namely, “level of analysis” (parent, program, and venture levels), “measurement perspective” (objective, subjective, and mixed measurement), and “locus of opportunity” (internal, external, and general CV activities). Second, an integrated overview of nine unique clusters structures the different measurement approaches. These clusters allow to encapsulate measurement approaches, but also make visible the approaches’ heterogeneity, as well as specific measurement items. Thereby, the study contributes to CV research by revealing and reconciling the variety of CV success-measurement approaches. The study also provides relevant insights for practitioners, by making transparent the various approaches to measuring the success of CV activities and presenting a list of 114 concrete and distinct measurement items.

Keywords: corporate venturing, measurement items, success measurement, structured literature review

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Authors: Jihye Jeon

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This paper analyzes the conceptual framework of three statistical methods, multiple regression, path analysis, and structural equation models. When establishing research model of the statistical modeling of complex social phenomenon, it is important to know the strengths and limitations of three statistical models. This study explored the character, strength, and limitation of each modeling and suggested some strategies for accurate explaining or predicting the causal relationships among variables. Especially, on the studying of depression or mental health, the common mistakes of research modeling were discussed.

Keywords: multiple regression, path analysis, structural equation models, statistical modeling, social and psychological phenomenon

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Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri

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Performance of different filtering approaches depends on modeling of dynamical system and algorithm structure. For modeling and smoothing the data the evaluation of posterior distribution in different filtering approach should be chosen carefully. In this paper different filtering approaches like filter KALMAN, EKF, UKF, EKS and smoother RTS is simulated in some trajectory tracking of path and accuracy and limitation of these approaches are explained. Then probability of model with different filters is compered and finally the effect of the noise variance to estimation is described with simulations results.

Keywords: Gaussian approximation, Kalman smoother, parameter estimation, noise variance

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Authors: Abdulmumin Isah

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Over the years, researchers have employed different approaches in the study of usage of library services in the traditional library system, such approaches have provided explanations on the users’ perception, attitude, and usage of library services. Findings of such studies which often employed survey research approach have guided librarians and library stakeholders in their drive to improve library services to patrons. However, with the advent of digital library services, librarians and information science researchers have been experiencing methodological issues in the study of digital library services. While some quantitative approaches have been employed to understand adoption and usage of digital library services, conflicting results from such studies have increased the need to employ qualitative approaches. The appropriateness of the qualitative approaches has also been questioned. This study intends to review methodological approaches in the studies of digital libraries and provides a framework for the selection of appropriate research approach for the study of digital libraries using Nigerian university systems as case study.

Keywords: digital library, university library, methodological issues, research approaches, quantitative, qualitative, Nigeria

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Authors: Butta Singh

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This paper presents a chaotic map based approach for secured embedding of patient’s confidential data in electrocardiogram (ECG) signal. The chaotic map generates predefined locations through the use of selective control parameters. The sample value difference method effectually hides the confidential data in ECG sample pairs at these predefined locations. Evaluation of proposed method on all 48 records of MIT-BIH arrhythmia ECG database demonstrates that the embedding does not alter the diagnostic features of cover ECG. The secret data imperceptibility in stego-ECG is evident through various statistical and clinical performance measures. Statistical metrics comprise of Percentage Root Mean Square Difference (PRD) and Peak Signal to Noise Ratio (PSNR). Further, a comparative analysis between proposed method and existing approaches was also performed. The results clearly demonstrated the superiority of proposed method.

Keywords: chaotic maps, ECG steganography, data embedding, electrocardiogram

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Authors: Queen Suraajini Rajendran, Sai Hung Cheung

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Statistical down scaling models are required to connect the global climate model outputs and the local weather variables for climate change impact prediction. For reliable climate change impact studies, the uncertainty associated with the model including natural variability, uncertainty in the climate model(s), down scaling model, model inadequacy and in the predicted results should be quantified appropriately. In this work, a new approach is developed by the authors for statistical classification, statistical down scaling and uncertainty assessment and is applied to Singapore rainfall. It is a robust Bayesian uncertainty analysis methodology and tools based on coupling dependent modeling error with classification and statistical down scaling models in a way that the dependency among modeling errors will impact the results of both classification and statistical down scaling model calibration and uncertainty analysis for future prediction. Singapore data are considered here and the uncertainty and prediction results are obtained. From the results obtained, directions of research for improvement are briefly presented.

Keywords: statistical downscaling, global climate model, climate change, uncertainty

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Authors: Hassan S. Naeini, Hashem Mosaddad

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Industrial design as a multidisciplinary science has a vast field in which some different aspects are involved. In this regard, aspects of art, technology and engineering, social and economics are known as the main related fields. Also, state of the art scientific areas and also art based files have been making the new conditions for industrial design discipline. Furthermore, there are some new approaches and branches of industrial design. However, there is not any categorized style for these industrial design sub-groups. Undoubtedly, if there is an appropriate chart for the main industrial design approaches and branches, the related groups such as industrial designers, manufacturers, and industrial design students will have practical ideas to categorize their activities. In this case study, we developed a scientific umbrella for industrial design in which most of current approaches and branches and related association are introduced. For data gathering, some interviews were done among volunteer industrial design lecturers who are teaching at some well-known universities in Iran. Also, according to the inventory of industrial design, theses which are in university libraries, thesis approaches, and titles were assessed. Based on gathered data, we introduced a scientific umbrella for industrial design in which most of related branches and approaches are categorized. In this umbrella, the hierarchy of related branches is highlighted as well.

Keywords: industrial design, art, industrial design approaches, scientific umbrella

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Authors: Rishikesh Yadav, Ramakanta Meher, Vishnu Narayan Mishra

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The main aim of this article is to investigate the statistical convergence of the summation of integral type operators and to obtain the weighted statistical convergence. The rate of statistical convergence by means of modulus of continuity and function belonging to the Lipschitz class are also studied. We discuss the convergence of the defined operators by graphical representation and put a better rate of convergence than the Szasz-Mirakjan-Kantorovich operators. In the last section, we extend said operators into bivariate operators to study about the rate of convergence in sense of modulus of continuity and by means of Lipschitz class by using function of two variables.

Keywords: The Szasz-Mirakjan-Kantorovich operators, statistical convergence, modulus of continuity, Peeters K-functional, weighted modulus of continuity

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Authors: S. H. R. Sadeghi, A. Sadoddin, A. Najafinejad

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Expansionism and ever-increasing population menace all different resources worldwide. The issue, hence, is critical in developing countries like Iran where new technologies are rapidly luxuriated and unguardedly applied, resulting in unexpected outcomes. However, uncommon and comprehensive approaches are introduced to take all the different aspects involved into consideration. In the last decade, few approaches such as community-based, stakeholders-oriented, adaptive and ultimately integrated management, have emerged and are developing for efficient, Co-management or best management, economic and sustainable development and management of watershed resources in Iran. In the present paper, an attempt has been made to focus on state-of-the-art approaches for the management of watershed resources applied in Iran. The study has been then supported by reports of some case studies conducted throughout the country involving previously mentioned approaches. Scrutinizing results of the researches verified a progressive tendency of the managerial approaches in watershed management strategies leading to a general approaching balance situation. The approaches are firmly rooted in educational, research, executive, legal and policy-making sectors leading to some recuperation at different levels. However, there is a long way ahead to naturalize detrimental effects of unscientific, illegal and over exploitation of the watershed resources in Iran.

Keywords: comprehensive management, ecosystem balance, integrated watershed management, land resources optimization

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Authors: Omar Alzeley, Sergey Utev

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Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

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