Search results for: random variables

Authors: H. Meradi, S. Bouhouche, M. Lahreche

Abstract:

In this work, we consider an application of neural networks in LD converter. Application of this approach assumes a reliable prediction of steel temperature and reduces a reblow ratio in steel work. It has been applied a conventional model to charge calculation, the obtained results by this technique are not always good, this is due to the process complexity. Difficulties are mainly generated by the noisy measurement and the process non linearities. Artificial Neural Networks (ANNs) have become a powerful tool for these complex applications. It is used a backpropagation algorithm to learn the neural nets. (ANNs) is used to predict the steel bath temperature in oxygen converter process for the end condition. This model has 11 inputs process variables and one output. The model was tested in steel work, the obtained results by neural approach are better than the conventional model.

Keywords: LD converter, bath temperature, neural networks.

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Authors: Zixin Liu, Shu Lü, Shouming Zhong, Mao Ye

Abstract:

The problem of exponential stability and periodicity for a class of cellular neural networks (DCNNs) with time-varying delays is investigated. By dividing the network state variables into subgroups according to the characters of the neural networks, some sufficient conditions for exponential stability and periodicity are derived via the methods of variation parameters and inequality techniques. These conditions are represented by some blocks of the interconnection matrices. Compared with some previous methods, the method used in this paper does not resort to any Lyapunov function, and the results derived in this paper improve and generalize some earlier criteria established in the literature cited therein. Two examples are discussed to illustrate the main results.

Keywords: Cellular neural networks, exponential stability, time varying delays, partitioned matrices, periodic solution.

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Authors: Joshi Manohar. V., Sujatha. P., Anjaneyulu K. S. R

Abstract:

The range of the output power is a very important and evident limitation of two-level inverters. In order to overcome this disadvantage, multilevel inverters are introduced. Recently, Cascade H-Bridge inverters have emerged as one of the popular converter topologies used in numerous industrial applications. The modulation switching strategies such as phase shifted carrier based Pulse Width Modulation (PWM) technique and Stair case modulation with Selective Harmonic Elimination (SHE) PWM technique are generally used. NR method is used to solve highly non linear transcendental equations which are formed by SHEPWM method. Generally NR method has a drawback of requiring good initial guess but in this paper a new approach is implemented for NR method with any random initial guess. A three phase CHB 11-level inverter is chosen for analysis. MATLAB/SIMULINK programming environment and harmonic profiles are compared. Finally this paper presents a method at fundamental switching frequency with least % THDV.

Keywords: Cascade H-bridge 11- level Inverter, NR method, Phase shifted carrier based pulse width modulation (PSCPWM), Selective Harmonic Elimination Pulse Width Modulation (SHEPWM), Total Harmonic Distortion (%THDv).

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Authors: Ali Hajiha, Farhad Ghaffari, Nooshin Gholamali Tehrani

Abstract:

This study aims at investigating the empirical relationships between risk preference, internet preference, and internet knowledge which are known as user characteristics, in addition to perceived risk of the customers on the internet purchase intention. In order to test the relationships between the variables of model 174, a questionnaire was collected from the students with previous online experience. For the purpose of data analysis, confirmatory factor analysis (CFA) and structural equation model (SEM) was used. Test results show that the perceived risk affects the internet purchase intention, and increase or decrease of perceived risk influences the purchase intention when the customer does the internet shopping. Other factors such as internet preference, knowledge of the internet, and risk preference affect the internet purchase intention.

Keywords: Perceived risk, Internet preference, Internetknowledge, Risk preference, Internet purchase intention

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Authors: Z. Jannoo, B. W. Yap, N. Auchoybur, M. A. Lazim

Abstract:

The two common approaches to Structural Equation Modeling (SEM) are the Covariance-Based SEM (CB-SEM) and Partial Least Squares SEM (PLS-SEM). There is much debate on the performance of CB-SEM and PLS-SEM for small sample size and when distributions are nonnormal. This study evaluates the performance of CB-SEM and PLS-SEM under normality and nonnormality conditions via a simulation. Monte Carlo Simulation in R programming language was employed to generate data based on the theoretical model with one endogenous and four exogenous variables. Each latent variable has three indicators. For normal distributions, CB-SEM estimates were found to be inaccurate for small sample size while PLS-SEM could produce the path estimates. Meanwhile, for a larger sample size, CB-SEM estimates have lower variability compared to PLS-SEM. Under nonnormality, CB-SEM path estimates were inaccurate for small sample size. However, CB-SEM estimates are more accurate than those of PLS-SEM for sample size of 50 and above. The PLS-SEM estimates are not accurate unless sample size is very large.  

Keywords: CB-SEM, Monte Carlo simulation, Normality conditions, Nonnormality, PLS-SEM.

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Authors: K. Bokreta, D. Benanaya

Abstract:

The objective of this study is to examine the relative effectiveness of monetary and fiscal policy in Algeria using the econometric modelling techniques of cointegration and vector error correction modelling to analyse and draw policy inferences. The chosen variables of fiscal policy are government expenditure and net taxes on products, while the effect of monetary policy is presented by the inflation rate and the official exchange rate. From the results, we find that in the long-run, the impact of government expenditures is positive, while the effect of taxes is negative on growth. Additionally, we find that the inflation rate is found to have little effect on GDP per capita but the impact of the exchange rate is insignificant. We conclude that fiscal policy is more powerful then monetary policy in promoting economic growth in Algeria.

Keywords: Economic growth, fiscal policy, monetary policy, VECM.

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Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

Abstract:

Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine (SVM), Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis (LDA), and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: Student performance, supervised machine learning, prediction, classification, cross-validation.

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Authors: Md. Emaj Uddin

Abstract:

Arrack is one of the forms of alcoholic beverage or liquor which is produced from palm or date juice and commonly consumed by the lower social class of all religious/ethnic communities in the north-western villages of Bangladesh. The purpose of the study was to compare arrack drinking patterns associated with socio-demographic status among the Muslim, Hindu, Santal, and Oraon communities in the Rasulpur union of Bangladesh. A total of 391 respondents (Muslim n-109, Hindu n-103, Santal n-89, Oraon n-90) selected by cluster random sampling were interviewed by ADP (Arrack Drinking Pattern) questionnaire. The results of Pearson Chi-Squire test revealed that arrack drinking patterns were significantly differed among the Muslim, Hindu, Santal, and Oraon communities- drinkers. In addition, the results of Spearman-s bivariate correlation coefficients also revealed that sociodemographic characteristics of the communities- drinkers were the significantly positive and negative associations with the arrack drinking patterns in the Rasulpur union, Bangladesh. The study suggests that further cross-cultural researches should be conducted on the consequences of arrack drinking patterns on the communities- drinkers.

Keywords: Arrack Drinking Patterns, Bangladesh, Community, Cross-Cultural Comparison, Socio-Demographic Status.

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Authors: P. Sankar, P. James Daniel Paul, Siddhant Sahu

Abstract:

A brief review of the empirical studies on the methodology of the stock market decision support would indicate that they are at a threshold of validating the accuracy of the traditional and the fuzzy, artificial neural network and the decision trees. Many researchers have been attempting to compare these models using various data sets worldwide. However, the research community is on the way to the conclusive confidence in the emerged models. This paper attempts to use the automotive sector stock prices from National Stock Exchange (NSE), India and analyze them for the intra-sectorial support for stock market decisions. The study identifies the significant variables and their lags which affect the price of the stocks using OLS analysis and decision tree classifiers.

Keywords: Indian Automotive Sector, Stock Market Decisions, Equity Portfolio Analysis, Decision Tree Classifiers, Statistical Data Analysis.

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Authors: F. Elashhab, L. Sheha, R. Fawzi Elsupikhe, A. E. A. Youssef, R. M. Sheltami, T. Alfazani

Abstract:

Chitosans, CSs, in solution are increasingly used in a range of geometric properties in various academic and industrial sectors, especially in the domain of pharmaceutical and biomedical engineering. In order to provide a tailoring guide of CSs to the applicants, gamma (γ)-irradiation technology and simple viscosity measurements have been used in this study. Accordingly, CS solid discs (0.5 cm thickness and 2.5 cm diameter) were exposed in air to Cobalt-60 (γ)-radiation, at room temperature and constant 50 kGy dose for different periods of exposer time (tγ). Diluted solutions of native and different irradiated CS were then prepared by dissolving 1.25 mg cm-3 of each polymer in 0.1 M NaCl/0.2 M CH3COOH. The single-concentration relative viscosity (ƞr) measurements were employed to obtain their intrinsic viscosity ([ƞ]) values and interrelated parameters, like: the molar mass (Mƞ), hydrodynamic radiuses (RH,ƞ), radius of gyration (RG,ƞ), and second virial coefficient (A2,ƞ) of CSs in the solution. The results show an exponential decrease of ƞr, [ƞ], Mƞ, RH,ƞ and RG,ƞ with increasing tγ. This suggests the influence of random chain-scission of CSs glycosidic bonds, with rate constant kr and kr-1 (lifetime τr ~ 0.017 min-1 and 57.14 min, respectively). The results also show an exponential decrease of A2ƞ with increasing tγ, which can be attributed to the growth of excluded volume effect in CS segments by tγ and, hence, better solution quality. The results are represented in following scaling laws as a tailoring guide to the applicants: RH,ƞ = 6.98 x 10-3 Mr0.65; RG,ƞ = 7.09 x 10-4 Mr0.83; A2,ƞ = 121.03 Mƞ,r-0.19.

Keywords: Gamma irradiation, geometric properties, kinetic model, scaling laws, viscosity measurement.

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Authors: N. Nacereddine, M. Tridi, S. S. Belaïfa, M. Zelmat

Abstract:

For the characterization of the weld defect region in the radiographic image, looking for features which are invariant regarding the geometrical transformations (rotation, translation and scaling) proves to be necessary because the same defect can be seen from several angles according to the orientation and the distance from the welded framework to the radiation source. Thus, panoply of geometrical attributes satisfying the above conditions is proposed and which result from the calculation of the geometrical parameters (surface, perimeter, etc.) on the one hand and the calculation of the different order moments, on the other hand. Because the large range in values of the raw features and taking into account other considerations imposed by some classifiers, the scaling of these values to lie between 0 and 1 is indispensable. The principal component analysis technique is used in order to reduce the number of the attribute variables in the aim to give better performance to the further defect classification.

Keywords: Geometric parameters, invariant attributes, principal component analysis, weld defect image.

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Authors: Waleed Abohamad, Amr Arisha

Abstract:

Owing the fact that optimization of business process is a crucial requirement to navigate, survive and even thrive in today-s volatile business environment, this paper presents a framework for selecting a best-fit optimization package for solving complex business problems. Complexity level of the problem and/or using incorrect optimization software can lead to biased solutions of the optimization problem. Accordingly, the proposed framework identifies a number of relevant factors (e.g. decision variables, objective functions, and modeling approach) to be considered during the evaluation and selection process. Application domain, problem specifications, and available accredited optimization approaches are also to be regarded. A recommendation of one or two optimization software is the output of the framework which is believed to provide the best results of the underlying problem. In addition to a set of guidelines and recommendations on how managers can conduct an effective optimization exercise is discussed.

Keywords: Complex Business Problems, Optimization, Selection Criteria, Software Evaluation.

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Authors: Mário C. Ricci

Abstract:

A known iterative computational procedure is used for internal normal ball loads calculation in statically loaded single-row, angular-contact ball bearings, subjected to a known thrust load, which is applied in the inner ring at the geometric bearing center line. Numerical aspects of the iterative procedure are discussed. Numerical examples results for a 218 angular-contact ball bearing have been compared with those from the literature. Twenty figures are presented showing the geometrical features, the behavior of the convergence variables and the following parameters as functions of the thrust load: normal ball loads, contact angle, distance between curvature centers, and normal ball and axial deflections between the raceways.

Keywords: Ball, Bearing, Static, Load, Iterative, Numerical, Method.

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Authors: Rafat Alshorman, Walter Hussak

Abstract:

Existing work in temporal logic on representing the execution of infinitely many transactions, uses linear-time temporal logic (LTL) and only models two-step transactions. In this paper, we use the comparatively efficient branching-time computational tree logic CTL and extend the transaction model to a class of multistep transactions, by introducing distinguished propositional variables to represent the read and write steps of n multi-step transactions accessing m data items infinitely many times. We prove that the well known correspondence between acyclicity of conflict graphs and serializability for finite schedules, extends to infinite schedules. Furthermore, in the case of transactions accessing the same set of data items in (possibly) different orders, serializability corresponds to the absence of cycles of length two. This result is used to give an efficient encoding of the serializability condition into CTL.

Keywords: computational tree logic, serializability, multi-step transactions.

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Authors: Rashid S. S., Alam M. Z.

Abstract:

A statistical optimization of the saccharification process of EFB was studied. The statistical analysis was done by applying faced centered central composite design (FCCCD) under response surface methodology (RSM). In this investigation, EFB dose, enzyme dose and saccharification period was examined, and the maximum 53.45% (w/w) yield of reducing sugar was found with 4% (w/v) of EFB, 10% (v/v) of enzyme after 120 hours of incubation. It can be calculated that the conversion rate of cellulose content of the substrate is more than 75% (w/w) which can be considered as a remarkable achievement. All the variables, linear, quadratic and interaction coefficient, were found to be highly significant, other than two coefficients, one quadratic and another interaction coefficient. The coefficient of determination (R2) is 0.9898 that confirms a satisfactory data and indicated that approximately 98.98% of the variability in the dependent variable, saccharification of EFB, could be explained by this model.

Keywords: Face centered central composite design (FCCCD), Liquid state bioconversion (LSB), Palm oil mill effluent, Trichoderma reesei RUT C-30.

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Authors: Hary Sulistyo, Suprihastuti S. Rahayu, Gatot Winoto, I M. Suardjaja

Abstract:

Transesterification of candlenut (aleurites moluccana) oil with methanol using potassium hydroxide as catalyst was studied. The objective of the present investigation was to produce the methyl ester for use as biodiesel. The operation variables employed were methanol to oil molar ratio (3:1 – 9:1), catalyst concentration (0.50 – 1.5 %) and temperature (303 – 343K). Oil volume of 150 mL, reaction time of 75 min were fixed as common parameters in all the experiments. The concentration of methyl ester was evaluated by mass balance of free glycerol formed which was analyzed by using periodic acid. The optimal triglyceride conversion was attained by using methanol to oil ratio of 6:1, potassium hydroxide as catalyst was of 1%, at room temperature. Methyl ester formed was characterized by its density, viscosity, cloud and pour points. The biodiesel properties had properties similar to those of diesel oil, except for the viscosity that was higher.

Keywords: biodiesel, candlenut, methyl ester, transestrification

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Authors: Hang-cheong Wong, Pak-kin Wong, Chi-man Vong, Zhengchao Xie, Shaojia Huang

Abstract:

Automotive engine air-ratio plays an important role of emissions and fuel consumption reduction while maintains satisfactory engine power among all of the engine control variables. In order to effectively control the air-ratio, this paper presents a model predictive fuzzy control algorithm based on online least-squares support vector machines prediction model and fuzzy logic optimizer. The proposed control algorithm was also implemented on a real car for testing and the results are highly satisfactory. Experimental results show that the proposed control algorithm can regulate the engine air-ratio to the stoichiometric value, 1.0, under external disturbance with less than 5% tolerance.

Keywords: Air-ratio, Fuzzy logic, online least-squares support vector machine, model predictive control.

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Authors: M. Govindarajan, R. M.Chandrasekaran

Abstract:

Text data mining is a process of exploratory data analysis. Classification maps data into predefined groups or classes. It is often referred to as supervised learning because the classes are determined before examining the data. This paper describes proposed radial basis function Classifier that performs comparative crossvalidation for existing radial basis function Classifier. The feasibility and the benefits of the proposed approach are demonstrated by means of data mining problem: direct Marketing. Direct marketing has become an important application field of data mining. Comparative Cross-validation involves estimation of accuracy by either stratified k-fold cross-validation or equivalent repeated random subsampling. While the proposed method may have high bias; its performance (accuracy estimation in our case) may be poor due to high variance. Thus the accuracy with proposed radial basis function Classifier was less than with the existing radial basis function Classifier. However there is smaller the improvement in runtime and larger improvement in precision and recall. In the proposed method Classification accuracy and prediction accuracy are determined where the prediction accuracy is comparatively high.

Keywords: Text Data Mining, Comparative Cross-validation, Radial Basis Function, runtime, accuracy.

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Authors: Mahdieh Allahviranloo

Abstract:

This paper introduces a mixed integer programming model to find the optimum development plan for port Anzali. The model minimizes total system costs taking into account both port infrastructure costs and shipping costs. Due to the multipurpose function of the port, the model consists of 1020 decision variables and 2490 constraints. Results of the model determine the optimum number of berths that should be constructed in each period and for each type of cargo. In addition to, the results of sensitivity analysis on port operation quantity provide useful information for managers to choose the best scenario for port planning with the lowest investment risks. Despite all limitations-due to data availability-the model offers a straightforward decision tools to port planners aspiring to achieve optimum port planning steps.

Keywords: MILP, Multipurpose Terminal, Port Operation Optimization, Port Anzali.

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Authors: Majid Forghani, Michael Khachay

Abstract:

In genetics, the impact of neighboring amino acids on a target site is referred as the nearest-neighbor effect or simply neighbor effect. In this paper, a new method called wavelet particle decomposition representing the one-dimensional neighbor effect using wavelet packet decomposition is proposed. The main idea lies in known dependence of wavelet packet sub-bands on location and order of neighboring samples. The method decomposes the value of a signal sample into small values called particles that represent a part of the neighbor effect information. The results have shown that the information obtained from the particle decomposition can be used to create better model variables or features. As an example, the approach has been applied to improve the correlation of test and reference sequence distance with titer in the hemagglutination inhibition assay.

Keywords: Antigenic variants, neighbor effect, wavelet packet, wavelet particle decomposition.

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Authors: Abbas Vahedian, Rijun Shrestha, Keith Crews

Abstract:

The bond mechanism between timber and fibre reinforced polymer (FRP) is relatively complex and is influenced by a number of variables including bond thickness, bond width, bond length, material properties, and geometries. This study investigates the influence of bond thickness on the behaviour of interface, failure mode, and bond strength of externally bonded FRP-to-timber interface. In the present study, 106 single shear joint specimens have been investigated. Experiment results showed that higher layers of FRP increase the ultimate load carrying capacity of interface; conversely, such increase led to decrease the slip of interface. Moreover, samples with more layers of FRPs may fail in a brittle manner without noticeable warning that collapse is imminent.

Keywords: FRP, single shear test, bond thickness, bond strength.

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Authors: Nino Abesadze, Marine Mindorashvili, Nino Paresashvili

Abstract:

At present actual tourism indicators cannot be calculated in Georgia, making it impossible to perform their quantitative analysis. Therefore, the study conducted by us is highly important from a theoretical as well as practical standpoint. The main purpose of the article is to make complex statistical analysis of tourist expenses of foreign visitors and to calculate statistical attractiveness indices of the tourism potential of Georgia. During the research, the method involving random and proportional selection has been applied. Computer software SPSS was used to compute statistical data for corresponding analysis. Corresponding methodology of tourism statistics was implemented according to international standards. Important information was collected and grouped from major Georgian airports, and a representative population of foreign visitors and a rule of selection of respondents were determined. The results show a trend of growth in tourist numbers and the share of tourists from post-soviet countries are constantly increasing. The level of satisfaction with tourist facilities and quality of service has improved, but still we have a problem of disparity between the service quality and the prices. The design of tourist expenses of foreign visitors is diverse; competitiveness of tourist products of Georgian tourist companies is higher. Attractiveness of popular cities of Georgia has increased by 43%.

Keywords: Tourist, expenses, indexes, statistics, analysis.

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Authors: Saravana Kannan Thangavelu

Abstract:

Fuel and oxidant gas delivery plate, or fuel cell plate, is a key component of a Proton Exchange Membrane (PEM) fuel cell. To manufacture low-cost and high performance fuel cell plates, advanced computer modeling and finite element structure analysis are used as virtual prototyping tools for the optimization of the plates at the early design stage. The present study examines thermal stress analysis of the fuel cell plates that are produced using a patented, low-cost fuel cell plate production technique based on screen-printing. Design optimization is applied to minimize the maximum stress within the plate, subject to strain constraint with both geometry and material parameters as design variables. The study reveals the characteristics of the printed plates, and provides guidelines for the structure and material design of the fuel cell plate.

Keywords: Design optimization, FEA, PEM fuel cell, Thermal stress

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Authors: K. Patanarapelert, I.M. Tang

Abstract:

The effect of a time delay on the transmission on dengue fever is studied. The time delay is due to the presence of an incubation period for the dengue virus to develop in the mosquito before the mosquito becomes infectious. The conditions for the existence of a Hopf bifurcation to limit cycle behavior are established. The conditions are different from the usual one and they are based on whether a particular third degree polynomial has positive real roots. A theorem for determining whether for a given set of parameter values, a critical delay time exist is given. It is found that for a set of realistic values of the parameters in the model, a Hopf bifurcation can not occur. For a set of unrealistic values of some of the parameters, it is shown that a Hopf bifurcation can occur. Numerical solutions using this last set show the trajectory of two of the variables making a transition from a spiraling orbit to a limit cycle orbit.

Keywords: Dengue fever transmission, time delay, Hopfbifurcation, limit cycle behavior

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Authors: S. Ghorbani, N. I. Polushin

Abstract:

Vibration during machining process is crucial since it affects cutting tool, machine, and workpiece leading to a tool wear, tool breakage, and an unacceptable surface roughness. This paper applies a nonparametric statistical method, single decision tree (SDT), to identify factors affecting on vibration in machining process. Workpiece material (AISI 1045 Steel, AA2024 Aluminum alloy, A48-class30 Gray Cast Iron), cutting tool (conventional, cutting tool with holes in toolholder, cutting tool filled up with epoxy-granite), tool overhang (41-65 mm), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev) and depth of cut (0.05-0.15 mm) were used as input variables, while vibration was the output parameter. It is concluded that workpiece material is the most important parameters for natural frequency followed by cutting tool and overhang.

Keywords: Cutting condition, vibration, natural frequency, decision tree, CART algorithm.

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Authors: R. Sudhesh Solomon, P. Y. K. L. Srinivas, Abhay Narayan, Amitava Das

Abstract:

Users in social networks either unicast or broadcast their messages. At mention is the popular way of unicasting for Twitter whereas general tweeting could be considered as broadcasting method. Understanding the information flow and dynamics within a Social Network and modeling the same is a promising and an open research area called Information Diffusion. This paper seeks an answer to a fundamental question - understanding if the at-mention network or the unicasting pattern in social media is purely random in nature or is there any user specific selectional preference? To answer the question we present an empirical analysis to understand the sociological aspects of Twitter mentions network within a social network community. To understand the sociological behavior we analyze the values (Schwartz model: Achievement, Benevolence, Conformity, Hedonism, Power, Security, Self-Direction, Stimulation, Traditional and Universalism) of all the users. Empirical results suggest that values traits are indeed salient cue to understand how the mention-based communication network functions. For example, we notice that individuals possessing similar values unicast among themselves more often than with other value type people. We also observe that traditional and self-directed people do not maintain very close relationship in the network with the people of different values traits.

Keywords: Social network analysis, information diffusion, personality and values, Twitter Mentions Network.

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

Abstract:

Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: Anomaly detection, autoencoder, data centers, deep learning.

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Authors: M. Alwetaishi, Giulia Sonetti

Abstract:

It is architecturally accepted that building form and design is considered as one of the most important aspects in affecting indoor temperature. The total area of building plan might be identical, but the design will have a major influence on the total area of external walls. This will have a clear impact on the amount of heat exchange with outdoor. Moreover, it will affect the position and area of glazing system. This has not received enough consideration in research by the specialists, since most of the publications are highlighting the impact of building envelope in terms of physical heat transfer in buildings. This research will investigate the impact of orientation of various building forms in various climatic regions. It will be concluded that orientation and glazing to wall ratio were recognized to be the most effective variables despite the shape of the building. However, linear ad radial forms were found more appropriate shapes almost across the continent.

Keywords: Architectural building design, building form, indoor air temperature, building design in different climate.

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Authors: D. Yilmaz, M.R. Usal

Abstract:

Nozzle is the main part of various spinning systems such as air-jet and Murata air vortex systems. Recently, many researchers worked on the usage of the nozzle on different spinning systems such as conventional ring and compact spinning systems. In these applications, primary purpose is to improve the yarn quality. In present study, it was produced the yarns with two different nozzle types and determined the changes in yarn properties. In order to explain the effect of the nozzle, airflow structure in the nozzle was modelled and airflow variables were determined. In numerical simulation, ANSYS 12.1 package program and Fluid Flow (CFX) analysis method was used. As distinct from the literature, Shear Stress Turbulent (SST) model is preferred. And also air pressure at the nozzle inlet was measured by electronic mass flow meter and these values were used for the simulation of the airflow. At last, the yarn was modelled and the area from where the yarn is passing was included to the numerical analysis.

Keywords: Nozzle, compressed air, swirling airflow, yarn properties.

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Authors: Javadi Alimohammad, Javadi Maryam, Feizi Fereidoon

Abstract:

A review of the literature found that Domestic violence and child maltreatment co-occur in many families, the purpose of this study attempts to emphasize the factors relating to intra-family relationships (order point of view) on violence against the children, For this purpose a survey technique on the sample size amounted 200 students of governmental guidance schools of city of Gilanegharb in country of Iran were considered. For measurement of violence against the children (VAC) the CTS scaled has been used .The results showed that children have experienced the violence more than once during the last year. degree of order in family is high. Explanation result indicated that the order variables in family including collective thinking, empathy, communal co-circumstance have significant effects on VAC.

Keywords: Violence, domestic violence, violence against children, order, guidance school, family, children.

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