Search results for: GWR techniques

Authors: A. N. Paithane, D. S. Bormane, S. D. Shirbahadurkar

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It has been seen that emotion recognition is an important research topic in the field of Human and computer interface. A novel technique for Feature Extraction (FE) has been presented here, further a new method has been used for human emotion recognition which is based on HHT method. This method is feasible for analyzing the nonlinear and non-stationary signals. Each signal has been decomposed into the IMF using the EMD. These functions are used to extract the features using fission and fusion process. The decomposition technique which we adopt is a new technique for adaptively decomposing signals. In this perspective, we have reported here potential usefulness of EMD based techniques.We evaluated the algorithm on Augsburg University Database; the manually annotated database.

Keywords: intrinsic mode function (IMF), Hilbert-Huang transform (HHT), empirical mode decomposition (EMD), emotion detection, electrocardiogram (ECG)

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Authors: Zoltan Sebestyen, Eszter Barta-Rajnai, Emma Jakab, Zsuzsanna Czegeny

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Extraction of the energy content of lignocellulosic biomass is one of the possible pathways to reduce the greenhouse gas emission derived from the burning of the fossil fuels. The application of the bioenergy can mitigate the energy dependency of a country from the foreign natural gas and the petroleum. The diversity of the plant materials makes difficult the utilization of the raw biomass in power plants. This problem can be overcome by the application of thermochemical techniques. Pyrolysis is the thermal decomposition of the raw materials under inert atmosphere at high temperatures, which produces pyrolysis gas, biooil and charcoal. The energy content of these products can be exploited by further utilization. The differences in the chemical and physical properties of the raw biomass materials can be reduced by the use of torrefaction. Torrefaction is a promising mild thermal pretreatment method performed at temperatures between 200 and 300 °C in an inert atmosphere. The goal of the pretreatment from a chemical point of view is the removal of water and the acidic groups of hemicelluloses or the whole hemicellulose fraction with minor degradation of cellulose and lignin in the biomass. Thus, the stability of biomass against biodegradation increases, while its energy density increases. The volume of the raw materials decreases so the expenses of the transportation and the storage are reduced as well. Biooil is the major product during pyrolysis and an important by-product during torrefaction of biomass. The composition of biooil mostly depends on the quality of the raw materials and the applied temperature. In this work, thermoanalytical techniques have been used to study the qualitative and quantitative composition of the pyrolysis and torrefaction oils of a woody (black locust) and two herbaceous samples (rape straw and wheat straw). The biooil contains C5 and C6 anhydrosugar molecules, as well as aromatic compounds originating from hemicellulose, cellulose, and lignin, respectively. In this study, special emphasis was placed on the formation of the lignin monomeric products. The structure of the lignin fraction is different in the wood and in the herbaceous plants. According to the thermoanalytical studies the decomposition of lignin starts above 200 °C and ends at about 500 °C. The lignin monomers are present among the components of the torrefaction oil even at relatively low temperatures. We established that the concentration and the composition of the lignin products vary significantly with the applied temperature indicating that different decomposition mechanisms dominate at low and high temperatures. The evolutions of decomposition products as well as the thermal stability of the samples were measured by thermogravimetry/mass spectrometry (TG/MS). The differences in the structure of the lignin products of woody and herbaceous samples were characterized by the method of pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS). As a statistical method, principal component analysis (PCA) has been used to find correlation between the composition of lignin products of the biooil and the applied temperatures.

Keywords: pyrolysis, torrefaction, biooil, lignin

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Authors: Mohd Anees Siddiqui, S. A. H. Jafri, Shahnawaz Alam

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Through this paper an attempt is made to review a special welding technology of friction stir welding (FSW) which is a solid-state joining. Friction stir welding is used for joining of two plates which are applied compressive force by using fixtures over the work table. This is a non consumable type welding technique in which a rotating tool of cylindrical shape is used. Process parameters such as tool geometry, joint design and process speed are discussed in the paper. Comparative study of Friction stir welding with other welding techniques such as MIG, TIG & GMAW is also done. Some light is put on several major applications of friction stir welding in different industries. Quality and environmental aspects of friction stir welding is also discussed.

Keywords: friction stir welding (FSW), process parameters, tool, solid state joining processes

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Authors: José L. Jiménez

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The use of technology in the classroom is an issue that is constantly evolving. Digital age students learn differently than their teachers did, so now the teacher should be constantly evolving their methods and teaching techniques to be more in touch with the student. In this paper a case study presents how were used some of these technologies by accompanying a classroom course, this in order to provide students with a different and innovative experience as their teacher usually presented the activities to develop. As students worked in the various activities, they increased their digital skills by employing unknown tools that helped them in their professional training. The twenty-first century teacher should consider the use of Information and Communication Technologies in the classroom thinking in skills that students of the digital age should possess. It also takes a brief look at the history of distance education and it is also highlighted the importance of integrating technology as part of the student's training.

Keywords: digital tools, on-line learning, social networks, technology

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Authors: Upamanyu Majumder, Angshuman Das

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Friction Stir Welding (FSW) is a Solid-State joining process. Unlike fusion welding techniques it does not involve operation above the melting point temperature of metals, but above the re-crystallization temperature. FSW also does not involve fusion of other material. FSW of ALUMINIUM has been commercialized and recent studies on joining dissimilar metals have been studied. Friction stir welding was introduced and patented in 1991 by The Welding Institute. For this paper, a total of nine samples each of copper and ALUMINIUM(Dissimilar metals) were welded using FSW process and Vickers Hardness were conducted on each of the samples.

Keywords: friction stir welding (FSW), recrystallization temperature, dissimilar metals, aluminium-copper, Vickers hardness test

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Authors: Prachi Desai, Ankita Gandhi, Mitali Acharya

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Rainfall forecast is mainly used for predictions of rainfall in a specified area and determining their future rainfall conditions. Rainfall is always a global issue as it affects all major aspects of one's life. Agricultural, fisheries, forestry, tourism industry and other industries are widely affected by these conditions. The studies have resulted in insufficient availability of water resources and an increase in water demand in the near future. We already have a new forecast system that uses the deep Convolutional Neural Network (CNN) to forecast monthly rainfall and climate changes. We have also compared CNN against Artificial Neural Networks (ANN). Machine Learning techniques that are used in rainfall predictions include ARIMA Model, ANN, LR, SVM etc. The dataset on which we are experimenting is gathered online over the year 1901 to 20118. Test results have suggested more realistic improvements than conventional rainfall forecasts.

Keywords: ANN, CNN, supervised learning, machine learning, deep learning

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Authors: Pothula Madhusudhan Reddy

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Introduction: Yoga is a way of life. of uniting the mind, body and soul. It is also an art of living the right way. The techniques of Yoga are very practical, so they can always be applied. This is the reason why Yoga has been practiced for thousands of years and is still valid today. Importance of Yoga: Yoga that helps to inculcate healthy habits and adopt a healthy lifestyle to achieve good health Research Aim: The aim of this study is to explore the potential benefits of yoga for holistic health and wellbeing, both at an individual and societal level The ultimate goal of human being is to attain the state of perfect freedom from the shackles of ignorance, which is the generator of all the pangs and miseries of life. Methodology: This research follows a thematic and practical experience approach. Yoga includes body postures and movements (stretching), breathing practices, imagery, meditation, and progressive relaxation techniques. Data Collection: The data for this research is collected through a combination of literature review, expert interviews, and practical yoga sessions. The literature review provides a comprehensive understanding of the principles and practices of yoga, while expert interviews offer insights from experienced practitioners. Practical yoga sessions allow for first hand experiences and observations, facilitating a deeper understanding of the subject matter. Analysis Procedures: The collected data is analyzed thematically, where key themes and patterns related to the benefits and effects of yoga on holistic health and wellbeing are identified. The findings are then interpreted and synthesized to draw meaningful conclusions. Questions Addressed: This research addresses the following questions: What are the potential benefits of yoga for holistic health and wellbeing? How does yoga promote rejuvenate the body, mind, and senses? What are the implications of a society embracing yoga for overall societal wellbeing and happiness? Findings: The research highlights that practicing yoga can lead to increased awareness of the body, mind, and senses. It promotes overall physical and mental health, helping individuals achieve a state of happiness and contentment. Moreover, the study emphasizes that a society embracing yoga can contribute to the development of a healthy and happy community. Theoretical Importance: The study of yoga for holistic health and wellbeing holds theoretical importance as it provides insights into the science of yoga and its impact on individuals and society. It contributes to the existing body of knowledge on the subject and further establishes yoga as a potential tool for enhancing overall wellness. Conclusion: The study concludes that yoga is a powerful practice for achieving holistic health and wellbeing. This research provides valuable insights into the science of yoga and its potential as a tool for promoting overall wellness.

Keywords: yoga, asana, pranayama, meditation

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Authors: M. Pallikonda Rajasekaran, J. Joshapath, Abhishek Prasad Shaw

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Various techniques has been employed to find location such as GPS, GLONASS, Galileo, and Beidou (compass). This paper currently deals with finding location using the existing FM signals that operates between 88-108 MHz. The location can be determined based on the received signal strength of nearby existing FM stations by mapping the signal strength values using trilateration concept. Thus providing security to users data and maintains eco-friendly environment at zero installation cost as this technology already existing FM stations operating in commercial FM band 88-108 MHZ. Along with the signal strength based trilateration it also finds azimuthal angle of the transmitter by employing directional antenna like Yagi-Uda antenna at the receiver side.

Keywords: location, existing FM signals, received signal strength, trilateration, security, eco-friendly, direction, privacy, zero installation cost

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Authors: Zaid Jamal Saeed Almahmoud

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Smart grid is emerging as the future power grid, with smart techniques to optimize power consumption and electricity generation. Minimizing peak power consumption under a fixed delay requirement is a significant problem in the smart grid.For this problem, all appliances must be scheduled within a given finite time duration. We consider the problem of minimizing the peak demand under appliances constraints by scheduling power jobs with uniform release dates and deadlines. As the problem is known to be NP-hard, we analyze the performance of a version of the natural greedy heuristic for solving this problem. Our theoretical analysis and experimental results show that the proposed heuristic outperforms existing methods by providing a better approximation to the optimal solution.

Keywords: peak demand scheduling, approximation algorithms, smart grid, heuristics

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Authors: Manoj Gupta, Nirmendra Singh Bhadauria

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Most of the applications in image processing require high spatial and high spectral resolution in a single image. For example satellite image system, the traffic monitoring system, and long range sensor fusion system all use image processing. However, most of the available equipment is not capable of providing this type of data. The sensor in the surveillance system can only cover the view of a small area for a particular focus, yet the demanding application of this system requires a view with a high coverage of the field. Image fusion provides the possibility of combining different sources of information. In this paper, we have decomposed the image using DTCWT and then fused using average and hybrid of (maxima and average) pixel level techniques and then compared quality of both the images using PSNR.

Keywords: image fusion, DWT, DT-CWT, PSNR, average image fusion, hybrid image fusion

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Authors: Yanmin Zhao, Siu Ming Yiu

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To claim the ownership for an executable program is a non-trivial task. An emerging direction is to add a watermark to the program such that the watermarked program preserves the original program’s functionality and removing the watermark would heavily destroy the functionality of the watermarked program. In this paper, the first watermarking signature scheme with the watermark and the constraint function hidden in the symmetric key setting is constructed. The scheme uses well-known techniques of lattice trapdoors and a lattice evaluation. The watermarking signature scheme is unforgeable under the Short Integer Solution (SIS) assumption and satisfies other security requirements such as the unremovability security property.

Keywords: short integer solution (SIS) problem, symmetric-key setting, watermarking schemes, watermarked signatures

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Authors: Fonseca Jully, Chia Maribel, Rodríguez Ilba

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This paper is a qualitative research report. A group of students form a public university in a small town in Colombia participated in this study which aimed at describing to what extend the use of social ads, published on the internet, helped to develop their critical thinking skills. Students’ productions, field notes, video recordings and direct observation were the instruments and techniques used by the researches in order to gather the data which was analyzed under the principles of grounded theory and triangulation. The implementation of social ads into the classroom evidenced a noticeable improvement in students’ ability to interpret and argue social issues, as well as, their self-improvement in oral and written production in English, as a foreign language.

Keywords: Ads, critical argumentation, critical thinking, social issues

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Authors: Lukman O. Alimi, Vincent J. Smith, Leonard J. Barbour

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The thermosalient effect is an extremely rare propensity of certain crystalline solids for self-actuation by elastic deformation or a ballistic event1. Thermosalient compounds, colloquially known as ‘jumping crystals’ are promising materials for fabrication of actuators that are also being considered as materials for clean energy conversion because of their capabilities to convert thermal energy into mechanical motion directly. Herein, an organic aminonitrile and its derivatives have been probed by a combination of structural, microscopic and thermoanalytical techniques. Crystals of these compounds were analysed by means of single crystal XRD and hotstage microscopy in the temperature range of 100 to 298 K and found to exhibit the thermosalient effect. We also carried out differential scanning calorimetric analysis at the temperature corresponding to that at which the crystal jumps as observed under a hotstage microscope.

Keywords: aminonitrile, jumping crystal, self actuation, thermosalient effect

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Authors: Zeineb Ben Azzouz, Wahiba Ben Abdessalem Karaa

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The automated extraction of UML class diagram from natural language requirements is a highly challenging task. Many approaches, frameworks and tools have been presented in this field. Nonetheless, the experiments of these tools have shown that there is no approach that can work best all the time. In this context, we propose a new accurate approach to facilitate the automatic mapping from textual requirements to UML class diagram. Our new approach integrates the best properties of statistical Natural Language Processing (NLP) techniques to reduce ambiguity when analysing natural language requirements text. In addition, our approach follows the best practices defined by conceptual modelling experts to determine some patterns indispensable for the extraction of basic elements and concepts of the class diagram. Once the relevant information of class diagram is captured, a XMI document is generated and imported with a CASE tool to build the corresponding UML class diagram.

Keywords: class diagram, user’s requirements, XMI, software engineering

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Authors: Khaleel Saleh Al-Rababah

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Amyloid fibril forming regions, which are known as protein aggregates, in sequences of some protein families are associated with a number of diseases known as amyloidosis. Mutations play a role in forming fibrils by accelerating the fibril formation process. In this paper we want to extract diseases that caused by those mutations as a result of the impact of the mutations on structural and functional properties of the aggregated protein. We propose a text mining system, to automatically extract mutations, diseases and relations between mutations and diseases. We presented an algorithm based on finite state to cluster mutations found in the same sentence as a sentence could contain different mutation cause different diseases. Also, we presented a co reference algorithm that enables cross-link sentences.

Keywords: amyloid, amyloidosis, co reference, protein, text mining

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Authors: Fiúza A., Góis J. Leite M., Braga H., Lima A., Jorge P., Moutela P., Martins L., Futuro A.

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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, 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 are used to minimize the laboratory effort required by conventional approaches and also allow phenomenological comprehension.

Keywords: artificial intelligence, tailings free process, ferroelectric electrolyte battery, life cycle assessment

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Authors: Ramon Sancibrian, Carlos Redondo-Figuero, Maria C. Gutierrez-Diez, Esther G. Sarabia, Maria A. Benito-Gonzalez, Jose C. Manuel-Palazuelos

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In this paper, the design and evaluation of a handle for laparoscopic surgery is presented. The design of the handle is based on ergonomic principles and tries to avoid awkward postures for surgeons. The handle combines the so-called power-grip and accurate-grip in order to provide strength and accuracy in the performance of surgery. The handle is tested using both objective and subjective approaches. The objective approach uses motion capture techniques to obtain the angles of forearm, arm, wrist and hand. The muscular effort is obtained with electromyography electrodes. On the other hand, a subjective survey has been carried out using questionnaires. Results confirm that the handle is preferred by the majority of the surgeons.

Keywords: laparoscopic surgery, ergonomics, mechanical design, biomechanics

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Authors: M. Moradi Dalini, M. R. Talebi

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This research revolves around a technical method according to combines econometric and multiobjective programming to select and obtain optimal solutions to management problems. It is taken for a generation that; it is important to analyze which combination of values of the explanatory variables -in an econometric method- would point to the simultaneous achievement of the best values of the response variables. In this case, if a certain degree of conflict is viewed among the response variables, we suggest a multiobjective method in order to the results obtained from a regression analysis. In fact, with the use of a multiobjective method, we will have the best decision about the conflicting relationship between the response variables and the optimal solution. The combined multiobjective programming and econometrics benefit is an assessment of a balanced “optimal” situation among them because a find of information can hardly be extracted just by econometric techniques.

Keywords: econometrics, multiobjective optimization, management problem, optimization

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Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

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Authors: Dan Geneau, Mary Claire Geneau, Seth Lenetsky, Ming -Chang Tsai, Marc Klimstra

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Introduction— Horizontal force-velocity profiling (HFVP) involves modeling an athletes linear sprint kinematics to estimate valuable maximum force and velocity metrics. This approach to performance modeling has been used in field-based team sports and has recently been introduced to ice-hockey as a forward skating performance assessment. While preliminary data has been collected on ice, distance constraints of the on-ice test restrict the ability of the athletes to reach their maximal velocity which result in limits of the model to effectively estimate athlete performance. This is especially true of more elite athletes. This report explores whether athletes on-ice are able to reach a velocity plateau similar to what has been seen in overground trials. Fourteen male Major Junior ice-hockey players (BW= 83.87 +/- 7.30 kg, height = 188 ± 3.4cm cm, age = 18 ± 1.2 years n = 14) were recruited. For on-ice sprints, participants completed a standardized warm-up consisting of skating and dynamic stretching and a progression of three skating efforts from 50% to 95%. Following the warm-up, participants completed three on ice 45m sprints, with three minutes of rest in between each trial. For overground sprints, participants completed a similar dynamic warm-up to that of on-ice trials. Following the warm-up participants completed three 40m overground sprint trials. For each trial (on-ice and overground), radar was used to collect instantaneous velocity (Stalker ATS II, Texas, USA) aimed at the participant’s waist. Sprint velocities were modelled using custom Python (version 3.2) script using a mono-exponential function, similar to previous work. To determine if on-ice tirals were achieving a maximum velocity (plateau), minimum acceleration values of the modeled data at the end of the sprint were compared (using paired t-test) between on-ice and overground trials. Significant differences (P<0.001) between overground and on-ice minimum accelerations were observed. It was found that on-ice trials consistently reported higher final acceleration values, indicating a maximum maintained velocity (plateau) had not been reached. Based on these preliminary findings, it is suggested that reliable HFVP metrics cannot yet be collected from all ice-hockey populations using current methods. Elite male populations were not able to achieve a velocity plateau similar to what has been seen in overground trials, indicating the absence of a maximum velocity measure. With current velocity and acceleration modeling techniques, including a dependency of a velocity plateau, these results indicate the potential for error in on-ice HFVP measures. Therefore, these findings suggest that a greater on-ice sprint distance may be required or the need for other velocity modeling techniques, where maximal velocity is not required for a complete profile.   

Keywords: ice-hockey, sprint, skating, power

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Authors: Austyn Snowden

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Aim: To examine the construct validity of the Trait Emotional Intelligence Questionnaire Short form. Background: Emotional intelligence involves the identification and regulation of our own emotions and the emotions of others. It is therefore a potentially useful construct in the investigation of recruitment and retention in nursing and many questionnaires have been constructed to measure it. Design: Secondary analysis of existing dataset of responses to TEIQue-SF using concurrent application of Rasch analysis and confirmatory factor analysis. Method: First year undergraduate nursing and computing students completed Trait Emotional Intelligence Questionnaire-Short Form. Responses were analysed by synthesising results of Rasch analysis and confirmatory factor analysis.

Keywords: emotional intelligence, rasch analysis, factor analysis, nurse recruiters

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Authors: Ali Reza Tahavvor, Saeed Hosseini, Nazli Jowkar, Behnam Amiri

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Heat transfer of leaves is a crucial factor in optimal operation of metabolic functions in plants. In order to quantify this phenomenon in different leaves and investigate the influence of leaf shape on heat transfer, natural convection for pine, orange and olive leaves was simulated as representatives of different groups of leaf shapes. CFD techniques were used in this simulation with the purpose to calculate heat transfer of leaves in similar environmental conditions. The problem was simulated for steady state and three-dimensional conditions. From obtained results, it was concluded that heat fluxes of all three different leaves are almost identical, however, total rate of heat transfer have highest and lowest values for orange leaves and pine leaves, respectively.

Keywords: computational fluid dynamic, heat flux, heat transfer, natural convection

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Authors: F. Benhamida, A. Graa, L. Benameur, I. Ziane

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The state estimation of the electrical power system operation state is very important for supervising task. With the nonlinearity of the AC power flow model, the state estimation problem (SEP) is a nonlinear mathematical problem with many local optima. This paper treat the mathematical model for the SEP and the monitoring of the nonlinear systems of great dimensions with an application on power electrical system, the modelling, the analysis and state estimation synthesis in order to supervise the power system behavior. in fact, it is very difficult, to see impossible, (for reasons of accessibility, techniques and/or of cost) to measure the excessive number of the variables of state in a large-sized system. It is thus important to develop software sensors being able to produce a reliable estimate of the variables necessary for the diagnosis and also for the control.

Keywords: power system, state estimation, robustness, observability

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Authors: Bharat Singh Om Prakash Vyas

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Now a day’s applications deal with High Dimensional Data have tremendously used in the popular areas. To tackle with such kind of data various approached has been developed by researchers in the last few decades. To tackle with such kind of data various approached has been developed by researchers in the last few decades. One of the problems with the NMF approaches, its randomized valued could not provide absolute optimization in limited iteration, but having local optimization. Due to this, we have proposed a new approach that considers the initial values of the decomposition to tackle the issues of computationally expensive. We have devised an algorithm for initializing the values of the decomposed matrix based on the PSO (Particle Swarm Optimization). Through the experimental result, we will show the proposed method converse very fast in comparison to other row rank approximation like simple NMF multiplicative, and ACLS techniques.

Keywords: ALS, NMF, high dimensional data, RMSE

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Authors: Abdelaziz Ghrib, Samir Hattali, Mouloud Ghrib, Mohamed Lamine Aouissia, David Ruch

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In the present study, the solid solutions with a chemical composition of Zr0.8Y0.2-xLaxO2 (x=0, 0.1, 0.2) were synthesized via two routes, by hydrothermal method using NaOH as precipitating agent at 230°C for 15h and by the sol–gel process using citric acid as complexing agent. Compounds have been characterized by powder X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), Thermo gravimetric Analysis (TGA) and Differential Thermal Analysis (DTA) techniques for appropriate characterization of the distinct thermal events occurring during synthesis. All the compounds crystallize in cubic fluorite structure, as indicated by X-ray diffraction studie. The microstructure of oxides synthesized by sol-gel showed porosity that increased with the lanthanum La3+ contents compared to hydrothermal method which gives a single crystal oxide.

Keywords: oxide, hydrothermal, rare earth, solubility, sol-gel, ternary mixture

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Authors: Vasilios Kanellopoulos

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The present paper examines the effect of innovation efficiency on the production of new knowledge from a firm level perspective. It resorts to the Greek version of community innovation survey (CIS 2012-2014 microdata) and employs 1274 firms of the manufacturing, which constitutes the main sector of examination. It assumes a knowledge production function (KPF) and finds that R&D spillovers related to the expenditures on innovation activities, internal R&D, external R&D, skilled labor, and the expenditures in the acquisition of machinery have a positive and significant effect on the production of new knowledge when OLS techniques are applied. However, innovation efficiency comes from a Banker and Morey (1986) data envelopment analysis (DEA) with categorical variables has a statistically insignificant impact on the production of new knowledge measured by firm’s turnover.

Keywords: firms, innovation efficiency, production of new knowledge, R&D spillovers

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Authors: Sabri Serkan Gulluoglu

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It is possible with Geographic Information Systems (GIS) that the information about all natural and artificial resources on the earth is obtained taking advantage of satellite images are obtained by remote sensing techniques. However, determination of unknown sources, mapping of the distribution and efficient evaluation of resources are defined may not be possible with the original image. For this reasons, some process steps are needed like transformation, pre-processing, image enhancement and classification to provide the most accurate assessment numerically and visually. Many studies which present the phases of obtaining and processing of the satellite images have examined in the literature study. The research showed that the determination of the process steps may be followed at this subject with the existence of a common whole may provide to progress the process rapidly for the necessary and possible studies which will be.

Keywords: remote sensing, satellite imaging, gis, computer science, information

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Authors: Khaled Harrar, Rachid Jennane

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The purpose of this study is the discrimination of 28 postmenopausal with osteoporotic femoral fractures from an age-matched control group of 28 women using texture analysis based on fractals. Two pre-processing approaches are applied on radiographic images; these techniques are compared to highlight the choice of the pre-processing method. Furthermore, the values of the fractal dimension are compared to those of the fractal signature in terms of the classification of the two populations. In a second analysis, the BMD measure at proximal femur was compared to the fractal analysis, the latter, which is a non-invasive technique, allowed a better discrimination; the results confirm that the fractal analysis of texture on calcaneus radiographs is able to discriminate osteoporotic patients with femoral fracture from controls. This discrimination was efficient compared to that obtained by BMD alone. It was also present in comparing subgroups with overlapping values of BMD.

Keywords: osteoporosis, fractal dimension, fractal signature, bone mineral density

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Authors: G. Usha, S. Kannimuthu, K. Mahalakshmi

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Mobile Adhoc Network (MANET) is one of the most promising technologies that have applications ranging from various portable devices to military networks. MANET has no fixed infrastructure and the security of such network is a big concern. Therefore, in order to operate MANET’s securely, the misbehavior and intrusions should be detected before the attackers affect the network communication. In this article, we make a comprehensive survey against black hole attack that is a serious threat against MANET that exploits the routing behavior of the MANET. We have given broad survey solutions that detect black hole attacks in MANET. This is achieved by analyzing the techniques involved in detecting the attacks in each scheme. Furthermore, we examine about the challenges to the researchers for constructing an in-depth solution against black hole attack.

Keywords: AODV, cross layer security, mobile Adhoc network (MANET), packet delivery ratio, single layer security

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Authors: Abdelaziz Moujane, Abedelali Boulli, Abdellah Ouigmane

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The present work focuses on the assessment of forestlandscape changes in the region of ZaouitAhansal, usingmultitemporal satellite images at high spatial resolution.Severalremotesensingmethodswereappliednamely: The supervised classification algorithm and NDVI whichwerecombined in a GIS environment to quantify the extent and change in density of forest stands (holmoak, juniper, thya, Aleppo pine, crops, and others).The resultsobtainedshowedthat the forest of ZaouitAhansal has undergonesignificantdegradationresulting in a decrease in the area of juniper, cedar, and zeenoak, as well as an increase in the area of baresoil and agricultural land. The remotesensing data providedsatisfactoryresults for identifying and quantifying changes in forestcover. In addition, thisstudycould serve as a reference for the development of management strategies and restoration programs.

Keywords: remote sensing, GIS, satellite image, NDVI, deforestation, zaouit ahansal

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