Search results for: Statistically complete tree

Authors: Zohreh O. Akbari

Abstract:

In this paper a deterministic polynomial-time algorithm is presented for the Clique problem. The case is considered as the problem of omitting the minimum number of vertices from the input graph so that none of the zeroes on the graph-s adjacency matrix (except the main diagonal entries) would remain on the adjacency matrix of the resulting subgraph. The existence of a deterministic polynomial-time algorithm for the Clique problem, as an NP-complete problem will prove the equality of P and NP complexity classes.

Keywords: Clique problem, Deterministic Polynomial-time Algorithm, Equality of P and NP Complexity Classes.

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Authors: Raghad Jawad Ahmed

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Segmentation of a color image composed of different kinds of regions can be a hard problem, namely to compute for an exact texture fields. The decision of the optimum number of segmentation areas in an image when it contains similar and/or un stationary texture fields. A novel neighborhood-based segmentation approach is proposed. A genetic algorithm is used in the proposed segment-pass optimization process. In this pass, an energy function, which is defined based on Markov Random Fields, is minimized. In this paper we use an adaptive threshold estimation method for image thresholding in the wavelet domain based on the generalized Gaussian distribution (GGD) modeling of sub band coefficients. This method called Normal Shrink is computationally more efficient and adaptive because the parameters required for estimating the threshold depend on sub band data energy that used in the pre-stage of segmentation. A quad tree is employed to implement the multi resolution framework, which enables the use of different strategies at different resolution levels, and hence, the computation can be accelerated. The experimental results using the proposed segmentation approach are very encouraging.

Keywords: Color image segmentation, Genetic algorithm, Markov random field, Scale space filter.

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Authors: T. Mahalakshmi, Aswathi B. L., Achuthsankar S. Nair

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Transcription factors are a group of proteins that helps for interpreting the genetic information in DNA. Protein-protein interactions play a major role in the execution of key biological functions of a cell. These interactions are represented in the form of a graph with nodes and edges. Studies have showed that some nodes have high degree of connectivity and such nodes, known as hub nodes, are the inevitable parts of the network. In the present paper a method is proposed to identify hub transcription factor proteins using sequence information. On a complete data set of transcription factor proteins available from the APID database, the proposed method showed an accuracy of 77%, sensitivity of 79% and specificity of 76%.

Keywords: Transcription Factor Proteins, Hub Proteins, Shannon Index, Transfer Free Energy to Surface (TFES).

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Authors: Fatahian Dehkordi R.F, Parchami A.

Abstract:

Steroidal hormones with the efficient changes on the epiphyseal growth plate may influence tissue structure properties. Presents paper to investigate the effects of gonadectomy in the pattern distribution of the epiphyseal structure. Fifteen adult female New Zealand white rabbits were separated into three groups. One group was intact and others groups were selected for surgical operation. From these two groups, one group carried out steroidal administration. The results obtained showed that there is no statistically difference in the mean diameter of the growth plate cells between all three groups. The maximum value of the cartilage cells were allocated to the gonadectomized group and the minimum number were observed in Hormonal induced group significantly. Growth plate height was significantly greater in gonadectomized group than in two other groups.

Keywords: Steroidal hormones, Ovariectomy, Rabbit, Epiphyseal structure

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Authors: Timothy Hinchman, Carrie Taylor

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This quantitative quasi-experimental research investigated disparities in mean and median performance among millennial soccer players. According to research, the fear of failure causes millennials to struggle with difficult jobs. The application of specified limitations has been found to increase individual productivity. The study utilized the constraint-based model of novelty (C-BMN) framework and the game performance assessment instrument (GPAI) to assess data concerning constraint-type and its impact on the productivity of 18 soccer players. Individual components cooperation and trapping had statistical significance throughout the intervention, while positioning, passing, and dribbling did not. The GPAI was statistically significant between the control and both restriction types. A two-way mixed ANOVA revealed no significant interaction between limitations and temperaments, however only 72% of individuals completed the temperament exam.

Keywords: Constraints, temperament, physical performance, GPAI.

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Authors: Tomáš Vencúrik, Jiří Nykodým

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This study compares the intensity of game load among player positions and between the 1st and the 2nd half of the games. Two guards, three forwards, and three centers (female basketball players) participated in this study. The heart rate (HR) and its development were monitored during two competitive games. Statistically insignificant differences in the intensity of game load were recorded between guards, forwards, and centers below and above 85% of the maximal heart rate (HRmax) and in the mean HR as % of HRmax (87.81±3.79%, 87.02±4.37%, and 88.76±3.54%, respectively). Moreover, when the 1st and the 2nd half of the games were compared in the mean HR (87.89±4.18% vs. 88.14±3.63% of HRmax), no statistical significance was recorded. This information can be useful for coaching staff, to manage and to precisely plan the training process.

Keywords: Game load, heart rate, player positions, the 1st and the 2nd half of the games.

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Authors: Fabio Fabris, Alex A. Freitas

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Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Keywords: Algorithm recommendation, meta-learning, bioinformatics, hierarchical classification.

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Authors: Nittaya Kerdprasop, Kittisak Kerdprasop

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Data mining (DM) is the process of finding and extracting frequent patterns that can describe the data, or predict unknown or future values. These goals are achieved by using various learning algorithms. Each algorithm may produce a mining result completely different from the others. Some algorithms may find millions of patterns. It is thus the difficult job for data analysts to select appropriate models and interpret the discovered knowledge. In this paper, we describe a framework of an intelligent and complete data mining system called SUT-Miner. Our system is comprised of a full complement of major DM algorithms, pre-DM and post-DM functionalities. It is the post-DM packages that ease the DM deployment for business intelligence applications.

Keywords: Business intelligence, data mining, functionalprogramming, intelligent system.

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Authors: Muhammad Ridhuan Tony Lim Abdullah, Saedah Siraj

Abstract:

The learning society has currently transformed from 'wired society' to become 'mobile society' which is facilitated by wireless network. To suit to this new paradigm, m-learning was given birth and rapidly building its prospect to be included in the future curriculum. Research and studies on m-learning spruced up in numerous aspects but there is still scarcity in studies on curriculum design of m-learning. This study is a part of an ongoing bigger study probing into the m-learning curriculum for secondary schools. The paper reports on the first phase of the study which aims to probe into the needs of curriculum design for m-learning at the secondary school level and the researcher adopted the needs analysis method. Data accrued from responses on survey questionnaires based on Lickert-point scale were analyzed statistically. The findings from this preliminary study serve as a basis for m-learning curriculum development for secondary schools.

Keywords: curriculum design, e-learning, future curriculum, m-learning

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Authors: Estrella C. Damaris, Ingrid A. Olais, Gloria P. Uicab

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This study explores the relationship between the level of functionality and cognitive impairment in older adult women from the south-east of Mexico. It is a descriptive, cross-sectional study; performed with 172 participants in total who attended a health institute and live in Merida, Yucatan Mexico. After a non-probabilistic sampling, Barthel and Pfeiffer scales were applied. The results show statistically significant correlation between the cognitive impairment (Pfeiffer) and the levels of independence and function (Barthel) (r =0.489; p =0.001). Both determine a dependence level so they need either a little or a lot of help. Society needs that the older woman be healthy and that the professionals of mental health develop activities to prevent and rehabilitate because cognitive impairment and function are directly related with the quality of life.

Keywords: Functionality, cognition, routine activities, cognitive impairment.

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Authors: Kemalettin Eryeşil, Aykut Bedük, Mehtap Fındık

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The aim of this study is to determine the effect of strategic management implementations on the institutionalization levels. In this regard a field study has been made over 31 stone quarry enterprises in cement producing sector in Konya by using survey method. In this study, institutionalization levels of the enterprises have been evaluated regarding three dimensions: professionalization, management approach, participation in decisions and delegation of authority. According to the results of the survey, there is a highly positive and statistically significant relationship between the strategic management implementations and institutionalization levels of the enterprises. Additionally,-considering the results of regression analysis made for establishing the relationship between strategic management and institutionalization levels- it has been determined that strategic management implementations of the enterprises can be used as a variable to explain the institutionalization levels of them, and also strategic management implementations of the enterprises increase the institutionalization levels of them.

Keywords: Institutionalization, Management, Strategic Management.

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Authors: Lijia Wang, Xuexi Huo

Abstract:

This study analyzes characteristics determining member’s willingness to invest in cooperatives using ordered logit model. The data were collected in a field survey among 122 cooperative members in north-central China. The descriptive analysis of survey evidence suggests that cooperatives in China generally having poor ability to deliver the processing services related to product package, grading, and storage, performing worse in profitability, inability of providing returns to capital and obtaining agricultural loan. The regression results demonstrate that members’ farm size, their satisfaction with cooperative price preferential services, attitudes toward cooperative operational scale and development potential have statistically significant impact on willingness to invest.

Keywords: Cooperatives, investment willingness, member, ordered logit.

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Authors: Neelima Gupta, Seema Aggarwal

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Most of the biclustering/projected clustering algorithms are based either on the Euclidean distance or correlation coefficient which capture only linear relationships. However, in many applications, like gene expression data and word-document data, non linear relationships may exist between the objects. Mutual Information between two variables provides a more general criterion to investigate dependencies amongst variables. In this paper, we improve upon our previous algorithm that uses mutual information for biclustering in terms of computation time and also the type of clusters identified. The algorithm is able to find biclusters with mixed relationships and is faster than the previous one. To the best of our knowledge, none of the other existing algorithms for biclustering have used mutual information as a similarity measure. We present the experimental results on synthetic data as well as on the yeast expression data. Biclusters on the yeast data were found to be biologically and statistically significant using GO Tool Box and FuncAssociate.

Keywords: Biclustering, mutual information.

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Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

Abstract:

Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: Classification algorithms; data mining; tourism; knowledge discovery.

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Authors: S. Khanpour, A. Movaghar

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The one of best robust search technique on large scale search area is heuristic and meta heuristic approaches. Especially in issue that the exploitation of combinatorial status in the large scale search area prevents the solution of the problem via classical calculating methods, so such problems is NP-complete. in this research, the problem of winner determination in combinatorial auctions have been formulated and by assessing older heuristic functions, we solve the problem by using of genetic algorithm and would show that this new method would result in better performance in comparison to other heuristic function such as simulated annealing greedy approach.

Keywords: Bids, genetic algorithm, heuristic, metaheuristic, simulated annealing greedy.

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Authors: Masoud Saeedi, Shirin Rahimi Kazerooni, Vahid Parvaresh

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Validity is an overriding consideration in language testing. If a test score is intended for a particular purpose, this must be supported through empirical evidence. This article addresses the validity of a multiple-choice achievement test (MCT). The test is administered at the end of each semester to decide about students' mastery of a course in general English. To provide empirical evidence pertaining to the validity of this test, two criterion measures were used. In so doing, a Cloze test and a C-test which are reported to gauge general English proficiency were utilized. The results of analyses show that there is a statistically significant correlation among participants' scores on the MCT, Cloze, and Ctest. Drawing on the findings of the study, it can be cautiously deduced that these tests measure the same underlying trait. However, allowing for the limitations of using criterion measures to validate tests, we cannot make any absolute claim as to the validity of this MCT test.

Keywords: C-test, cloze test, multiple-choice test, validity argument.

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Authors: Hamed Zakikhani, Mohd Khanif Yusop, Amin Soltangheisi

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A hydroponic trial was carried out to investigate the effect of molybdenum (Mo) on uptake of phosphorus (P) in different rice cultivars. The experiment was conducted using a randomized complete-block design, with a split-plot arrangement of treatments and three replications. Four rates of Mo (0, 0.01, 0.1 and 1 mg L⁻¹) and five cultivars (MR219, HASHEMI, MR232, FAJRE and MR253) provided the main and sub-plots, respectively. Interaction of molybdenum×variety was significant on shoot phosphorus uptake (p≤0.01). Highest and lowest shoot phosphorus uptake were seen in Mo₃V₃ (0.6% plant^-1) and Mo₀V₃ (0.14% plant^-1) treatments, respectively. Molybdenum did not have a significant effect on root phosphorus content. According to results, application of molybdenum has a synergistic effect on uptake of phosphorus by rice plants.

Keywords: Molybdenum, Phosphorus, Uptake, rice.

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Authors: Tarik H. Badi, Amer A. Boushaala

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The purpose of this study was to measure the maximal isometric strength and to investigate the effects of different handleheights and elbow angles with respect to Mid. sagittal plane on the pushing and pulling strength in vertical direction. Eight male subjects performed a series of static strength measurement for each subject. The highest isometric strength was found in pulling at shoulder height (S.H.) (Mean = 60.29 lb., SD = 16.78 lb.) and the lowest isometric strength was found also in pulling at elbow height (E.H.) (Mean = 33.06 lb., SD = 6.56 lb.). Although the isometric strengths were higher at S.H than at E.H. for both activities, the maximal isometric strengths were compared statistically. ANOVA was performed. The results of the experiment revealed that there was a significant different between handle heights. However, there were no significant different between angles and activities, also no correlation between grip strength and activities.

Keywords: Pushing and pulling, one arm, vertical direction, isometric strength.

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Authors: Hyeondal Jeong, Yoonjung Baek

Abstract:

This research examines the effects of positive psychological capital (or PsyCap) on employee’s outcomes (satisfaction, commitment, organizational citizenship behavior, innovation behavior and individual creativity). This study conducted a meta-analysis of articles published in the Republic of Korea. As a result, positive psychological capital has a positive effect on the behavior of employees. Heterogeneity was identified among the studies included in the analysis and the context factors were analyzed; the study proposes contextual factors such as team tenure. The moderating effect of team tenure was not statistically significant. The implications were discussed based on the analysis results.

Keywords: Positive psychological capital, satisfaction, commitment, OCB, creativity, meta-analysis.

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Authors: Amir-Massoud Bidgoli, Mehdi Naseri Parsa

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In this paper a combined feature selection method is proposed which takes advantages of sample domain filtering, resampling and feature subset evaluation methods to reduce dimensions of huge datasets and select reliable features. This method utilizes both feature space and sample domain to improve the process of feature selection and uses a combination of Chi squared with Consistency attribute evaluation methods to seek reliable features. This method consists of two phases. The first phase filters and resamples the sample domain and the second phase adopts a hybrid procedure to find the optimal feature space by applying Chi squared, Consistency subset evaluation methods and genetic search. Experiments on various sized datasets from UCI Repository of Machine Learning databases show that the performance of five classifiers (Naïve Bayes, Logistic, Multilayer Perceptron, Best First Decision Tree and JRIP) improves simultaneously and the classification error for these classifiers decreases considerably. The experiments also show that this method outperforms other feature selection methods.

Keywords: feature selection, resampling, reliable features, Consistency Subset Evaluation.

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Authors: Jung–Min Yang

Abstract:

In this paper, fault recovery for parallel interconnected asynchronous sequential machines is studied. An adversarial input can infiltrate into one of two submachines comprising parallel composition of the considered asynchronous sequential machine, causing an unauthorized state transition. The control objective is to elucidate the condition for the existence of a corrective controller that makes the closed-loop system immune against any occurrence of adversarial inputs. In particular, an efficient existence condition is presented that does not need the complete modeling of the interconnected asynchronous sequential machine.

Keywords: Asynchronous sequential machines, parallel composition, corrective control, fault tolerance.

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Authors: Hans H. Diel

Abstract:

A computer model of Quantum Theory (QT) has been developed by the author. Major goal of the computer model was support and demonstration of an as large as possible scope of QT. This includes simulations for the major QT (Gedanken-) experiments such as, for example, the famous double-slit experiment. Besides the anticipated difficulties with (1) transforming exacting mathematics into a computer program, two further types of problems showed up, namely (2) areas where QT provides a complete mathematical formalism, but when it comes to concrete applications the equations are not solvable at all, or only with extremely high effort; (3) QT rules which are formulated in natural language and which do not seem to be translatable to precise mathematical expressions, nor to a computer program. The paper lists problems in all three categories and describes also the possible solutions or circumventions developed for the computer model.

Keywords: Computability, Foundation of Quantum Mechanics, Measurement Process, Modeling.

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Authors: Hanieh Tarbiat Khosrowshahi, Mojtaba Shakeri

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Wireless Sensor Networks (WSNs) consist of a set of sensor nodes with limited capability. WSNs may suffer from multiple node failures when they are exposed to harsh environments such as military zones or disaster locations and lose connectivity by getting partitioned into disjoint segments. Relay nodes (RNs) are alternatively introduced to restore connectivity. They cost more than sensors as they benefit from mobility, more power and more transmission range, enforcing a minimum number of them to be used. This paper addresses the problem of RN placement in a multiple disjoint network by developing a genetic algorithm (GA). The problem is reintroduced as the Steiner tree problem (which is known to be an NP-hard problem) by the aim of finding the minimum number of Steiner points where RNs are to be placed for restoring connectivity. An upper bound to the number of RNs is first computed to set up the length of initial chromosomes. The GA algorithm then iteratively reduces the number of RNs and determines their location at the same time. Experimental results indicate that the proposed GA is capable of establishing network connectivity using a reasonable number of RNs compared to the best existing work.

Keywords: Connectivity restoration, genetic algorithms, multiple-node failure, relay nodes, wireless sensor networks.

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Authors: Takaaki Ishibashi

Abstract:

Independent component analysis can estimate unknown source signals from their mixtures under the assumption that the source signals are statistically independent. However, in a real environment, the separation performance is often deteriorated because the number of the source signals is different from that of the sensors. In this paper, we propose an estimation method for the number of the sources based on the joint distribution of the observed signals under two-sensor configuration. From several simulation results, it is found that the number of the sources is coincident to that of peaks in the histogram of the distribution. The proposed method can estimate the number of the sources even if it is larger than that of the observed signals. The proposed methods have been verified by several experiments.

Keywords: blind source separation, independent component analysys, estimation for the number of the blind sources, voice activity detection, target extraction.

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Authors: D. Goustouridis, A. Sideris, I. Sdrolias, G. Loizos, N.-Alexander Tatlas, S. M. Potirakis

Abstract:

Both daily and long-term management of a heavy-duty vehicles and construction machinery fleet is an extremely complicated and hard to solve issue. This is mainly due to the diversity of the fleet vehicles – machinery, which concerns not only the vehicle types, but also their age/efficiency, as well as the fleet volume, which is often of the order of hundreds or even thousands of vehicles/machineries. In the present paper we present “InteligentLogger”, a holistic heavy-duty fleet management system covering a wide range of diverse fleet vehicles. This is based on specifically designed hardware and software for the automated vehicle health status and operational cost monitoring, for smart maintenance. InteligentLogger is characterized by high adaptability that permits to be tailored to practically any heavy-duty vehicle/machinery (of different technologies -modern or legacy- and of dissimilar uses). Contrary to conventional logistic systems, which are characterized by raised operational costs and often errors, InteligentLogger provides a cost-effective and reliable integrated solution for the e-management and e-maintenance of the fleet members. The InteligentLogger system offers the following unique features that guarantee successful heavy-duty vehicles/machineries fleet management: (a) Recording and storage of operating data of motorized construction machinery, in a reliable way and in real time, using specifically designed Internet of Things (IoT) sensor nodes that communicate through the available network infrastructures, e.g., 3G/LTE; (b) Use on any machine, regardless of its age, in a universal way; (c) Flexibility and complete customization both in terms of data collection, integration with 3rd party systems, as well as in terms of processing and drawing conclusions; (d) Validation, error reporting & correction, as well as update of the system’s database; (e) Artificial intelligence (AI) software, for processing information in real time, identifying out-of-normal behavior and generating alerts; (f) A MicroStrategy based enterprise BI, for modeling information and producing reports, dashboards, and alerts focusing on vehicles– machinery optimal usage, as well as maintenance and scraping policies; (g) Modular structure that allows low implementation costs in the basic fully functional version, but offers scalability without requiring a complete system upgrade.

Keywords: E-maintenance, predictive maintenance, IoT sensor nodes, cost optimization, artificial intelligence, heavy-duty vehicles.

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Authors: M. Wu, S. M. Feroz, A. Hagihara, L. Xue, Z. L. Huang

Abstract:

In order to compare vertical stratification, floristic composition, and woody species diversity of subtropical evergreen broadleaf forests between the Ryukyu Archipelago, Japan, and South China, tree censuses in a 400 m2 plot in Ishigaki Island and a 1225 m2 plot in Dinghushan Nature Reserve were performed. Both of the subtropical forests consisted of five vertical strata. The floristic composition of the Ishigaki forest was quite different from that of the Dinghushan forest in terms of similarity on a species level (Kuno-s similarity index r0 = 0.05). The values of Shannon-s index H' and Pielou-s index J ' tended to increase from the bottom stratum upward in both forests, except H' for the top stratum in the Ishigaki forest and the upper two strata in the Dinghushan forest. The woody species diversity in the Dinghushan forest (H'= 3.01 bit) was much lower than that in the Ishigaki forest (H'= 4.36 bit).

Keywords: Floristic similarity, subtropical evergreen broadleaf forest, vertical stratification, woody species diversity.

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Authors: Gilberto Gonzalez-A, Noe Barrera-G

Abstract:

An analysis of a synchronous generator in a bond graph approach is proposed. This bond graph allows to determine the simplified models of the system by using singular perturbations. Firstly, the nonlinear bond graph of the generator is linearized. Then, the slow and fast state equations by applying singular perturbations are obtained. Also, a bond graph to get the quasi-steady state of the slow dynamic is proposed. In order to verify the effectiveness of the singularly perturbed models, simulation results of the complete system and reduced models are shown.

Keywords: Bond graph modelling, synchronous generator, singular perturbations

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Authors: Mustafa A. Al-Refai

Abstract:

This paper investigates the energy storage  technologies that can potentially enhance the use of solar energy.  Water electrolysis systems are seen as the principal means of  producing a large amount of hydrogen in the future. Starting from the  analysis of the models of the system components, a complete  simulation model was realized in the Matlab-Simulink environment.  Results of the numerical simulations are provided. The operation of  electrolysis and photovoltaic array combination is verified at various  insulation levels. It is pointed out that solar cell arrays and  electrolysers are producing the expected results with solar energy  inputs that are continuously varying.

Keywords: Electrolyzer, Simulink, solar energy, storage system.

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Authors: R. Andreola, O. A. A. Santos, L. M. M, Jorge

Abstract:

An industrial system for the production of white liquor of a paper industry, Klabin Paraná Papéis, formed by ten reactors was modeled, simulated, and analyzed. The developed model considered possible water losses by evaporation and reaction, in addition to variations in volumetric flow of lime mud across the reactors due to composition variations. The model predictions agreed well with the process measurements at the plant and the results showed that the slaking reaction is nearly complete at the third causticizing reactor, while causticizing ends by the seventh reactor. Water loss due to slaking reaction and evaporation occurs more pronouncedly in the slaking reaction than in the final causticizing reactors; nevertheless, the lime mud flow remains nearly constant across the reactors.

Keywords: Causticizing, lime, prediction, process.

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Authors: D. SuganyaDevi, G. Padmavathi

Abstract:

Reliable secure multicast communication in mobile adhoc networks is challenging due to its inherent characteristics of infrastructure-less architecture with lack of central authority, high packet loss rates and limited resources such as bandwidth, time and power. Many emerging commercial and military applications require secure multicast communication in adhoc environments. Hence key management is the fundamental challenge in achieving reliable secure communication using multicast key distribution for mobile adhoc networks. Thus in designing a reliable multicast key distribution scheme, reliability and congestion control over throughput are essential components. This paper proposes and evaluates the performance of an enhanced optimized multicast cluster tree algorithm with destination sequenced distance vector routing protocol to provide reliable multicast key distribution. Simulation results in NS2 accurately predict the performance of proposed scheme in terms of key delivery ratio and packet loss rate under varying network conditions. This proposed scheme achieves reliability, while exhibiting low packet loss rate with high key delivery ratio compared with the existing scheme.

Keywords: Key Distribution, Mobile Adhoc Network, Multicast and Reliability.

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