Search results for: Middleton Class A impulsive noise

Authors: Rahimah Saimin

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Previous research has shown that young children can learn from educational television programmes, videos or other technological media. However, the blending of any of these with traditional printed-based text appears to be omitted. Repeated viewing is an important factor in children's ability to comprehend the content or plot. The present study combined videos with traditional printed-based text and required repeated viewing and is original and distinctive. The first study was a pilot study to explore whether the intervention is implementable in ordinary classrooms. The second study explored whether the curricular embedding is important or whether the video with curricular embedding is effective. The third study explored the effect of “dosage”, i.e. whether a longer/ more intense intervention has a proportionately greater effect on outcomes. Both measured outcomes (comprehension, word sounds, and early word recognition) and unmeasured outcomes (engagement to reading traditional printed-based texts or/and multimodal texts) were obtained from this study. Observation indicated degree of engagement in reading. The theoretical framework was multimodality theory combined with Piaget’s and Vygotsky’s learning theories. An experimental design was used with 4-5-year-old children in nursery schools and primary schools. Six links to video clips exploring non-fiction science content were provided to teachers. The first session is whole-class and subsequent sessions small-group. The teacher then engaged the children in dialogue using supplementary materials. About half of each class was selected randomly for pre-post assessments. Two assessments were used the British Picture Vocabulary Scale (BPVSIII) and the York Assessment of Reading for Comprehension (YARC): Early Reading. Different programme fidelity means were deployed- observations, teacher self-reports attendance logs and post-delivery interviews. Data collection is in progress and results will be available shortly. If this multiphase study show effectiveness in one or other application, then teachers will have other tools which they can use to enhance vocabulary, letter knowledge and word reading. This would be a valuable addition to their repertoire.

Keywords: language skills, literacy skills, multimodality, video

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Authors: Sinem Bulkan

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This study introduces the construct of psychopathic manager behaviour and aims for the development of psychopathic manager behaviour (Psycho-Man B) measure. The study also aims for the understanding of the relationship between psychopathic manager behaviour and workplace deviance while investigating the mediating role of a revenge motive and the moderating roles of the core self-evaluations and the attitude importance. Data were collected from 519 employees from a wide variety of jobs and industries who currently work for or previously worked for a manager in a collectivist culture, Turkey. Psycho-Man B Measure was developed resulting in five dimensions as opposed to the proposed ten dimensions. Simple linear and hierarchical regression analyses were conducted to test the hypotheses. The results of simple linear regression analyses showed that psychopathic manager behaviour was positively significantly related to supervisor-directed and organisation-directed deviance. Revenge motive towards the manager partially mediated the relationship between psychopathic manager behaviour and supervisor-directed deviance. Similarly, revenge motive towards the organisation partially mediated the relationship between psychopathic manager behaviour and organisation-directed deviance. Furthermore, no support was found for the expected moderating role of core self-evaluations in the revenge motive towards the manager-supervisor-directed deviance and revenge motive towards the organisation-organisation-directed deviance relationships. Attitude importance moderated the relationship between revenge motive towards the manager and supervisor-directed deviance; revenge motive towards the organisation and organisation-directed deviance. Moderated-mediation hypotheses were not supported for core self-evaluations but were supported for the attitude importance. Additional analyses for sub-dimensions were conducted to further examine the hypotheses. Demographic variables were examined through independent samples t-tests, and one way ANOVA. Finally, findings are discussed; limitations, suggestions and implications are presented. The major contribution of this study is that ‘psychopathic manager behaviour’ construct was introduced to the literature and a scale for the reliable identification of psychopathic manager behaviour was developed in to evaluate managers’ level of sub-clinical psychopathy in the workforce. The study introduced that employees engage in different forms of supervisor-directed deviance and organisation-directed deviance depending on the level of the emotions and personal goals. Supervisor-directed deviant behaviours and organisation-directed deviant behaviours became distinct in a way as impulsive and premeditated, active or passive, direct and indirect actions. Accordingly, it is important for organisations to notice that employees’ level of affective state and attitude importance for psychopathic manager behaviours predetermine the certain type of employee deviant behaviours.

Keywords: attitude importance, core self evaluations, psychopathic manager behaviour, revenge motive, workplace deviance

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Authors: Walid S. Alfuhaid, Saud A. Alghamdi, John M. Watkins, M. Edwin Sawan

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Designing a controller for stochastic decentralized interconnected large scale systems usually involves a high degree of complexity and computation ability. Noise, observability, and controllability of all system states, connectivity, and channel bandwidth are other constraints to design procedures for distributed large scale systems. The quasi-steady state model investigated in this paper is a reduced order model of the original system using singular perturbation techniques. This paper results in an optimal control synthesis to design an observer based feedback controller by standard stochastic control theory techniques using Linear Quadratic Gaussian (LQG) approach and Kalman filter design with less complexity and computation requirements. Numerical example is given at the end to demonstrate the efficiency of the proposed method.

Keywords: decentralized, optimal control, output, singular perturb

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Authors: Meriam Khelifa

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In recent years, many studies have focused on the harvesting of the vibrations energy to produce electrical energy using contact separation (CS) triboelectric nanogenerators (TENG). The simplest design for a TENG consists of a capacitor comprising a single moving electrode. The conversion efficiency of vibration energy into electrical energy can, in principle, reach 100%. But to actually achieve this objective, it is necessary to optimize the parameters of the TENG, such as the dielectric constant and the thickness of the insulator, the load resistance, etc. In particular, the use of a switch which is actioned at optimal times within the TENG cycle is essential. Using numerical modeling and experimental design, we applied a methodology to find the TENG parameters which optimize the energy transfer efficiency (ETE) to almost 100% for any vibration frequency and amplitude. The rather simple design of a TENG is promising as an environment friendly device. It opens the doors for harvesting acoustic vibrations from the environment and to design effective protection against environmental noise.

Keywords: vibrations, CS TENG, efficiency, design of experiments

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Authors: Chaitanya Chawla, Divya Panwar, Gurneesh Singh Anand, M. P. S Bhatia

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This paper presents a deep-learning mechanism for classifying computer generated images and photographic images. The proposed method accounts for a convolutional layer capable of automatically learning correlation between neighbouring pixels. In the current form, Convolutional Neural Network (CNN) will learn features based on an image's content instead of the structural features of the image. The layer is particularly designed to subdue an image's content and robustly learn the sensor pattern noise features (usually inherited from image processing in a camera) as well as the statistical properties of images. The paper was assessed on latest natural and computer generated images, and it was concluded that it performs better than the current state of the art methods.

Keywords: image forensics, computer graphics, classification, deep learning, convolutional neural networks

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Authors: Ivan Baravy

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Interpolation problem, as it was initially posed in terms of polynomials, is well researched. However, further mathematical developments extended it significantly. Trigonometric interpolation is widely used in Fourier analysis, while its generalized representation as exponential interpolation is applicable to such problem of mathematical physics as modelling of Ziegler-Biersack-Littmark repulsive interatomic potentials. Formulated for finite fields, this problem arises in decoding Reed--Solomon codes. This paper shows the relation between different interpretations of the problem through the class of matrices of special structure - Hankel matrices.

Keywords: Berlekamp-Massey algorithm, exponential interpolation, finite fields, Hankel matrices, Hankel polynomials

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Authors: Ahmed Amin Mousa, Tamer M. Ismail, M. Abd El Salam

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This work presents a robot called Conceptual Robotic Cube, CR-Cube. The robot can be used as an educational tool for children from the age of three. It has a cube shape attached with a camera colours sensor. In addition, it contains four wheels to move smoothly. The researchers prepared a questionnaire to measure the efficiency of the robot. The design and the questionnaire was presented to 11 experts who agreed that the robot is appropriate for learning numbering and colours for preschool children.

Keywords: CR-Cube, robotic cube, conceptual robot, conceptual cube, colour concept, early childhood education

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Authors: Ouerchefani Dalel, Mahdhaoui Basma

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Land use change is one of the important factors needed to evaluate later on the impact of human actions on land degradation. This work present the application of a methodology based on remote sensing for evaluation land use change in an arid region of Tunisia. This methodology uses Landsat TM and ETM+ images to produce land use maps by supervised classification based on ground truth region of interests. This study showed that it was possible to rely on radiometric values of the pixels to define each land use class in the field. It was also possible to generate 3 land use classes of the same study area between 1988 and 2011.

Keywords: land use, change, remote sensing, GIS

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Authors: Michał Glet, Kamil Kaczyński

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Counterfeit goods and documents are a global problem, which needs more and more sophisticated methods of resolving it. Existing techniques using watermarking or embedding symbols on objects are not suitable for all use cases. To address those special needs, we created complete system allowing authentication of paper documents and physical objects with flat surface. Objects are marked using orientation independent and resistant to camera noise 2D graphic codes, named DotAuth. Based on the identifier stored in 2D code, the system is able to perform basic authentication and allows to conduct more sophisticated analysis methods, e.g., relying on augmented reality and physical properties of the object. In this paper, we present the complete architecture, algorithms and applications of the proposed system. Results of the features comparison of the proposed solution and other products are presented as well, pointing to the existence of many advantages that increase usability and efficiency in the means of protecting physical objects.

Keywords: anti-forgery, authentication, paper documents, security

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Authors: Tunahan Sapmaz, Harun Etçi, İbrahim Şenol, Yasemin Öner

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Rotor bar dimensions have a great influence on the air-gap magnetic flux density. Therefore, poor selection of this parameter during the machine design phase causes the air-gap magnetic flux density to be distorted. Thus, it causes noise, torque fluctuation, and losses in the induction motor. On the other hand, the change in rotor bar dimensions will change the resistance of the conductor, so the current will be affected. Therefore, the increase and decrease of rotor bar current affect operation, starting torque, and efficiency. The aim of this study is to examine the effect of rotor bar dimensions on the electromagnetic performance criteria of the induction motor. Modeling of the induction motor is done by the finite element method (FEM), which is a very powerful tool. In FEM, the results generally focus on performance criteria such as torque, torque fluctuation, efficiency, and current.

Keywords: induction motor, finite element method, optimization, rotor bar

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Authors: David Rafetseder, Walter Bauer, Florian Poltschak, Wolfgang Amrhein

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A flat double-stator linear induction machine (DSLIM) with a short squirrel-cage mover is designed for high thrust force at moderate speed < 5m/s. The performance and motor parameters are determined on the basis of a 2D time-transient simulation with the finite element (FE) software Maxwell 2015. Design guidelines and transformation rules for space vector theory of the LIM are presented. Resulting thrust calculated by flux and current vectors is compared with the FE results showing good coherence and reduced noise. The parameters of the equivalent circuit model are obtained.

Keywords: equivalent circuit model, finite element model, linear induction motor, space vector theory

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Authors: Olesya Bolkhovskaya, Alexey Davydov, Alexander Maltsev

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In this paper two approaches to joint signal detection, time of arrival (ToA) and angle of arrival (AoA) estimation in multi-element antenna array are investigated. Two scenarios were considered: first one, when the waveform of the useful signal is known a priori and, second one, when the waveform of the desired signal is unknown. For first scenario, the antenna array signal processing based on multi-element matched filtering (MF) with the following non-coherent detection scheme and maximum likelihood (ML) parameter estimation blocks is exploited. For second scenario, the signal processing based on the antenna array elements covariance matrix estimation with the following eigenvector analysis and ML parameter estimation blocks is applied. The performance characteristics of both signal processing schemes are thoroughly investigated and compared for different useful signals and noise parameters.

Keywords: antenna array, signal detection, ToA, AoA estimation

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Authors: Zeina Bou Diab, Arij Daou

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The neural mechanisms of sequential behaviors are intensively studied, with songbirds a focus for learned vocal production. We are studying the premotor nucleus HVC at a nexus of multiple pathways contributing to song learning and production. The HVC consists of multiple classes of neuronal populations, each has its own cellular, electrophysiological and functional properties. During singing, a large subset of motor cortex analog-projecting HVCRA neurons emit a single 6-10 ms burst of spikes at the same time during each rendition of song, a large subset of basal ganglia-projecting HVCX neurons fire 1 to 4 bursts that are similarly time locked to vocalizations, while HVCINT neurons fire tonically at average high frequency throughout song with prominent modulations whose timing in relation to song remains unresolved. This opens the opportunity to define models relating explicit HVC circuitry to how these neurons work cooperatively to control learning and singing. We developed conductance-based Hodgkin-Huxley models for the three classes of HVC neurons (based on the ion channels previously identified from in vitro recordings) and connected them in several physiologically realistic networks (based on the known synaptic connectivity and specific glutaminergic and gabaergic pharmacology) via different architecture patterning scenarios with the aim to replicate the in vivo firing patterning behaviors. We are able, through these networks, to reproduce the in vivo behavior of each class of HVC neurons, as shown by the experimental recordings. The different network architectures developed highlight different mechanisms that might be contributing to the propagation of sequential neural activity (continuous or punctate) in the HVC and to the distinctive firing patterns that each class exhibits during singing. Examples of such possible mechanisms include: 1) post-inhibitory rebound in HVCX and their population patterns during singing, 2) different subclasses of HVCINT interacting via inhibitory-inhibitory loops, 3) mono-synaptic HVCX to HVCRA excitatory connectivity, and 4) structured many-to-one inhibitory synapses from interneurons to projection neurons, and others. Replication is only a preliminary step that must be followed by model prediction and testing.

Keywords: computational modeling, neural networks, temporal neural sequences, ionic currents, songbird

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Authors: Enoch Kudoahor, Nan Zheng

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We describe the use of readily available self-doped TiO2 and visible light, under a mild condition to synthesize a class of monocyclic, bicyclic, and benzocyclobutene amino compounds containing the endoperoxide bridges; their derivatives and further test their effective clinical activities against malaria, cancer, and their resistances. Considering their stable under photooxidation conditions and recyclability, we use a self-doped TiO2 under a visible condition to synthesize these classes of amino endoperoxides. These amino endoperoxides are stable over a period compared to classes of endoperoxides.

Keywords: catalysis, endoperoxides, titanium dioxide, visible light

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Authors: Arash Golzari Koloor

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Feedback seems to be an inseparable part of teaching a second/foreign language. One type of feedback is corrective feedback which is one type of error treatment in second language classrooms. This study is a report on the types of corrective feedback employed in an IELTS preparation course. The types of feedback, their frequencies, and their effectiveness are enlisted, enumerated, and interpreted. The results showed that explicit correction and recast were the most frequent types of feedback while repetition and elicitation were the least. The results also revealed that metalinguistic feedback, elicitation, and explicit correction were the most effective types of feedback and affected learners performance greatly.

Keywords: classroom interaction, corrective feedback, error treatment, oral performance

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Authors: George Bocean

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In the mainstream academic spheres of thought, there is a tendency to associate the writings of Russian Marxists as being constantly against the practice of religion itself. Such arguments mainly stem from how the attitude of the Russian Marxists, specifically the Bolsheviks, towards the concept of religion supposedly originates from its own Marxist ideology. Although Marxism is critical of religion as an institution, the approach that Marxism would have on the question of religion is not as clear. Such aspect is specifically observed in the use of language of major leading Russian Marxist figures, such as Lenin and Trotsky, throughout the early 20th century, where the use of religious metaphors was widely used in their philosophical writings and speeches, as well as in propaganda posters of general left-wing movements in Russia as a whole. The methodology of the research will consist of a sociolinguistic and sociology of language approach within a sociohistorical framework of late Tsarist and early Soviet Russia, 1905-1926. The purpose of such approaches are not simply to point out the religious metaphors used in the writings and speeches of Marxists in Russia, but rather in order to analyse how the use of such metaphors represent an important socio-political connection with the context of Russia at the time. In other words, the use of religious metaphors was not only more akin to Russian culture at the time, but this also resonated and was more familiar with the conditions of the working class and peasantry. An example in this study can be observed in the writings of Lenin, where the theme of chudo (miracle) is often mentioned in his writings, and such a word is commonly associated with an idealist philosophy rather than a materialist one, which represents a common theme in Russian culture in regards to the principle of hope for a better life. A further and even more obvious example is Trotsky’s writings about how the revolution of 1905 “would be revived”, which not only resonates with the theme of resurrection, but also prophesises the “second coming” of a future revolution. Such metaphors are important in the writings of such authors, as they simultaneously contain Marxist ideas, as well as religious themes. In doing this research, this paper will demonstrate two aspects. Firstly, the paper will analyse the use of the metaphors by Russian Marxists as a whole in regards to a socio-political and ideological perspectives akin to those of Marxism. Secondly, it will also demonstrate the role that such metaphors have in regards to their impact on the left-wing movements within Russia itself, as well as their relation to the working class and peasantry of Russia within the historical context.

Keywords: language and politics, Marxism, Russian history, social history, sociology of language

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Authors: Hyun-Woo Cho

Abstract:

The detection and identification of multivariate manufacturing processes are quite important in order to maintain good product quality. Unusual behaviors or events encountered during its operation can have a serious impact on the process and product quality. Thus they should be detected and identified as soon as possible. This paper focused on the efficient representation of process measurement data in detecting and identifying abnormalities. This qualitative method is effective in representing fault patterns of process data. In addition, it is quite sensitive to measurement noise so that reliable outcomes can be obtained. To evaluate its performance a simulation process was utilized, and the effect of adopting linear and nonlinear methods in the detection and identification was tested with different simulation data. It has shown that the use of a nonlinear technique produced more satisfactory and more robust results for the simulation data sets. This monitoring framework can help operating personnel to detect the occurrence of process abnormalities and identify their assignable causes in an on-line or real-time basis.

Keywords: detection, monitoring, identification, measurement data, multivariate techniques

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Authors: Muleya Nqobile, Winston Garira

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We presented a compartmental deterministic multi-scale model which encompass internal plant defensive mechanism and pathogen interaction, then we consider nesting the model into the epidemiological model. The objective was to improve our understanding of the transmission dynamics of within host and between host of Guignardia citricapa Kiely. The inflow of infected class was scaled down to individual level while the outflow was scaled up to average population level. Conceptual model and mathematical model were constructed to display a theoretical framework which can be used for predicting or identify disease pattern.

Keywords: epidemiological model, mathematical modelling, multi-scale modelling, immunological model

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Authors: Jérôme de Reffye, Marc Antoni

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Following the development of the ERTMS system, we think it is interesting to develop another software-based track circuit system which would fit secondary railway lines with an easy-to-work implementation and a low sensitivity to rail-wheel impedance variations. We called this track circuit 'Track Railway by Automatic Circuits.' To be internationally implemented, this system must not have any mechanical component and must be compatible with existing track circuit systems. For example, the system is independent from the French 'Joints Isolants Collés' that isolate track sections from one another, and it is equally independent from component used in Germany called 'Counting Axles,' in French 'compteur d’essieux.' This track circuit is fully interoperable. Such universality is obtained by replacing the train detection mechanical system with a space-time filtering of train position. The various track sections are defined by the frequency of a continuous signal. The set of frequencies related to the track sections is a set of orthogonal functions in a Hilbert Space. Thus the failure probability of track sections separation is precisely calculated on the basis of signal-to-noise ratio. SNR is a function of the level of traction current conducted by rails. This is the reason why we developed a very powerful algorithm to reject noise and jamming to obtain an SNR compatible with the precision required for the track circuit and SIL 4 level. The SIL 4 level is thus reachable by an adjustment of the set of orthogonal functions. Our major contributions to railway engineering signalling science are i) Train space localization is precisely defined by a calibration system. The operation bypasses the GSM-R radio system of the ERTMS system. Moreover, the track circuit is naturally protected against radio-type jammers. After the calibration operation, the track circuit is autonomous. ii) A mathematical topology adapted to train space localization by following the train through a linear time filtering of the received signal. Track sections are numerically defined and can be modified with a software update. The system was numerically simulated, and results were beyond our expectations. We achieved a precision of one meter. Rail-ground and rail-wheel impedance sensitivity analysis gave excellent results. Results are now complete and ready to be published. This work was initialised as a research project of the French Railways developed by the Pi-Ramses Company under SNCF contract and required five years to obtain the results. This track circuit is already at Level 3 of the ERTMS system, and it will be much cheaper to implement and to work. The traffic regulation is based on variable length track sections. As the traffic growths, the maximum speed is reduced, and the track section lengths are decreasing. It is possible if the elementary track section is correctly defined for the minimum speed and if every track section is able to emit with variable frequencies.

Keywords: track section, track circuits, space-time crossing, adaptive track section, automatic railway signalling

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Authors: Madaki Umar Yusuf, Mohd Rizam B. Abubakar

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The survival censored data with incomplete covariate data is a common occurrence in many studies in which the outcome is survival time. With model when the missing covariates are categorical, a useful technique for obtaining parameter estimates is the EM by the method of weights. The survival outcome for the class of generalized linear model is applied and this method requires the estimation of the parameters of the distribution of the covariates. In this paper, we propose some clinical trials with ve covariates, four of which have some missing values which clearly show that they were fully censored data.

Keywords: EM algorithm, incomplete categorical covariates, ignorable missing data, missing at random (MAR), Weibull Distribution

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Authors: Liang Zhao, Chong-quan Zhong

Abstract:

In order to improve the control performance of vector inverter, an improved parameter identification solution for induction motor is proposed in this paper. Dc or AC voltage is applied to the induction motor using the SVPWM through the inverter. Then stator resistance, stator leakage inductance, rotor resistance, rotor leakage inductance and mutual inductance are obtained according to the signal response. The discrete Fourier transform (DFT) is used to deal with the noise and harmonic. The impact on parameter identification caused by delays in the inverter switch tube, tube voltage drop and dead-time is avoided by effective compensation measures. Finally, the parameter identification experiment is conducted based on the vector inverter which using TMS320F2808 DSP as the core processor and results show that the strategy is verified.

Keywords: vector inverter, parameter identification, SVPWM; DFT, dead-time compensation

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Authors: Asha Gupta, Ramandeep Kaur

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

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

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Authors: Yousra Zakaria Ahmed, Ahmed El Gendy, Salah El Haggar

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In this paper, our methodology to assess sustainability of wastewater treatment technologies in Egypt is presented. The preliminary list of factors to be considered, as well as their ranking listed. The factors include, but are not limited to pollutants removal efficiency and energy consumption under the environmental dimension, construction cost, operation and maintenance costs and required land area cost under the economic dimension and public acceptance, noise and generating job opportunities for local residents. This methodology is intended to be a user-friendly screening tool to support the decision making process when investigating different wastewater treatment technologies in Egypt. Based on the research work results presented in this paper, it can be generally concluded that the categorization of some of the social and environmental aspects of sustainability is subjective and highly dependent on the local conditions and researchers’ background.

Keywords: sustainability, wastewater treatment, sustainability assessment, Egypt

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Authors: Safeer Hussain Khan

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In this paper, we introduce a two-step iterative algorithm to prove a strong convergence result for approximating common fixed points of three contractive-like operators. Our algorithm basically generalizes an existing algorithm..Our iterative algorithm also contains two famous iterative algorithms: Mann iterative algorithm and Ishikawa iterative algorithm. Thus our result generalizes the corresponding results proved for the above three iterative algorithms to a class of more general operators. At the end, we remark that nothing prevents us to extend our result to the case of the iterative algorithm with error terms.

Keywords: contractive-like operator, iterative algorithm, fixed point, strong convergence

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Authors: Shreeyam, Ranjan Kumar Sah, Shivangi

Abstract:

Recognizing and solving handwritten mathematical expressions can be a challenging task, particularly when certain characters are segmented and classified. This project proposes a solution that uses Convolutional Neural Network (CNN) and image processing techniques to accurately solve various types of equations, including arithmetic, quadratic, and trigonometric equations, as well as logical operations like logical AND, OR, NOT, NAND, XOR, and NOR. The proposed solution also provides a graphical solution, allowing users to visualize equations and their solutions. In addition to equation solving, the platform, called CNNCalc, offers a comprehensive learning experience for students. It provides educational content, a quiz platform, and a coding platform for practicing programming skills in different languages like C, Python, and Java. This all-in-one solution makes the learning process engaging and enjoyable for students. The proposed methodology includes horizontal compact projection analysis and survey for segmentation and binarization, as well as connected component analysis and integrated connected component analysis for character classification. The compact projection algorithm compresses the horizontal projections to remove noise and obtain a clearer image, contributing to the accuracy of character segmentation. Experimental results demonstrate the effectiveness of the proposed solution in solving a wide range of mathematical equations. CNNCalc provides a powerful and user-friendly platform for solving equations, learning, and practicing programming skills. With its comprehensive features and accurate results, CNNCalc is poised to revolutionize the way students learn and solve mathematical equations. The platform utilizes a custom-designed Convolutional Neural Network (CNN) with image processing techniques to accurately recognize and classify symbols within handwritten equations. The compact projection algorithm effectively removes noise from horizontal projections, leading to clearer images and improved character segmentation. Experimental results demonstrate the accuracy and effectiveness of the proposed solution in solving a wide range of equations, including arithmetic, quadratic, trigonometric, and logical operations. CNNCalc features a user-friendly interface with a graphical representation of equations being solved, making it an interactive and engaging learning experience for users. The platform also includes tutorials, testing capabilities, and programming features in languages such as C, Python, and Java. Users can track their progress and work towards improving their skills. CNNCalc is poised to revolutionize the way students learn and solve mathematical equations with its comprehensive features and accurate results.

Keywords: AL, ML, hand written equation solver, maths, computer, CNNCalc, convolutional neural networks

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Authors: Dominik Szczesniak, Sabre Kais

Abstract:

In the present communication, we analyze selected local aspects of the metal-induced gap states (MIGSs) that may be responsible for the magnetic flux noise in some of the superconducting qubit modalities at low-dimension. The presented theoretical analysis stems from the earlier bulk considerations and is aimed at further explanation of the decoherence effect by recognizing its universal character. Specifically, the analysis is carried out by using the complex band structure method for arbitrary low-dimensional junctions. This allows us to provide the most fundamental and general observations for the systems of interest. In particular, herein, we investigate in detail the MIGSs behavior in the momentum space as a function of the potential fluctuations and the electron-electron interaction magnitude at the interface. In what follows, this study is meant to provide a direct relationship between the MIGSs behavior, the discussed decoherence effect, and the intrinsic properties of the low-dimensional Josephson junctions.

Keywords: superconducting qubits, metal-induced gap states, decoherence, low-dimension

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Authors: Hedia Mhiri Sellami

Abstract:

This case study used the principles of the flipped classroom (FC) in courses dealing with the use of the Information and Communication Technology (ICT) in three business curricula. The FC was used because our first goal is to devote more time to practice the theoretical concepts, so, before the class session, students had to watch videos introducing the concept they will learn. The videos weren't designed for our course, they are on Youtube and correspond to real cases of the ICT use in companies. This choice was also made in order to meet our second goal; it was to motivate students by showing them that the aspects covered by the course are very useful in the business. This case study reinforced the positive reputation of the FC as it was globally appreciated by our students. Beside, we managed to achieve our objectives relating to the motivation and application of concepts studied.

Keywords: flipped classroom, business, ICT, video, learning

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Authors: Noor Arda Adrina Daud, Mohd Hanafi Ali

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The compensating filter is placed between the patient and X-ray tube to compensate various density and thickness of human body. The main purpose of this project is to study the effect of compensating filter on image quality in lateral projection of thoracolumbar radiography. The study was performed by an X-ray unit where different thicknesses of aluminum were used as compensating filter. Specifically the relationship between thickness of aluminum, density and noise were evaluated. Results show different thickness of aluminum compensating filter improved the image quality of lateral projection thoracolumbar radiography. The compensating filter of 8.2 mm was considered as the optimal filter to compensate the thoracolumbar junction (T12-L1), 1 mm to compensate lumbar region and 5.9 mm to compensate thorax region. The aluminum wedge compensating filter was designed resulting in an acceptable image quality.

Keywords: compensating filter, aluminum, image quality, lateral, thoracolumbar

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Authors: J. G. Batista, T. S. Santiago, E. A. Ribeiro, G. A. P. Thé

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This work deals with parameter identification of permanent magnet motors, a class of ac motor which is particularly important in industrial automation due to characteristics like applications high performance, are very attractive for applications with limited space and reducing the need to eliminate because they have reduced size and volume and can operate in a wide speed range, without independent ventilation. By using experimental data and genetic algorithm we have been able to extract values for both the motor inductance and the electromechanical coupling constant, which are then compared to measure and/or expected values.

Keywords: modeling, AC servomotor, permanent magnet synchronous motor-PMSM, genetic algorithm, vector control, robotic manipulator, control

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Authors: Alexander Zotov, Ilkin Osmanov, Emil Sakharov, Oleg Shelest, Aleksander Troitskiy, Robert Khabazov

Abstract:

Objective: Thoracoscopic surgical ablation of atrial fibrillation (AF) includes two technologies in performing of operation. 1st strategy used is the AtriCure device (bipolar, nonirrigated, non clamping), 2nd strategy is- the Medtronic device (bipolar, irrigated, clamping). The study presents a comparative analysis of clinical outcomes of two strategies in thoracoscopic ablation of AF using AtriCure vs. Medtronic devices. Methods: In 2 center study, 123 patients underwent thoracoscopic ablation of AF for the period from 2016 to 2020. Patients were divided into two groups. The first group is represented by patients who applied the AtriCure device (N=63), and the second group is - the Medtronic device (N=60), respectively. Patients were comparable in age, gender, and initial severity of the condition. Among the patients, in group 1 were 65% males with a median age of 57 years, while in group 2 – 75% and 60 years, respectively. Group 1 included patients with paroxysmal form -14,3%, persistent form - 68,3%, long-standing persistent form – 17,5%, group 2 – 13,3%, 13,3% and 73,3% respectively. Median ejection fraction and indexed left atrial volume amounted in group 1 – 63% and 40,6 ml/m2, in group 2 - 56% and 40,5 ml/m2. In addition, group 1 consisted of 39,7% patients with chronic heart failure (NYHA Class II) and 4,8% with chronic heart failure (NYHA Class III), when in group 2 – 45% and 6,7%, respectively. Follow-up consisted of laboratory tests, chest Х-ray, ECG, 24-hour Holter monitor, and cardiopulmonary exercise test. Duration of freedom from AF, distant mortality rate, and prevalence of cerebrovascular events were compared between the two groups. Results: Exit block was achieved in all patients. According to the Clavien-Dindo classification of surgical complications fraction of adverse events was 14,3% and 16,7% (1st group and 2nd group, respectively). Mean follow-up period in the 1st group was 50,4 (31,8; 64,8) months, in 2nd group - 30,5 (14,1; 37,5) months (P=0,0001). In group 1 - total freedom of AF was in 73,3% of patients, among which 25% had additional antiarrhythmic drugs (AADs) therapy or catheter ablation (CA), in group 2 – 90% and 18,3%, respectively (for total freedom of AF P<0,02). At follow-up, the distant mortality rate in the 1st group was – 4,8%, and in the 2nd – no fatal events. Prevalence of cerebrovascular events was higher in the 1st group than in the 2nd (6,7% vs. 1,7% respectively). Conclusions: Despite the relatively shorter follow-up of the 2nd group in the study, applying the strategy using the Medtronic device showed quite encouraging results. Further research is needed to evaluate the effectiveness of this strategy in the long-term period.

Keywords: atrial fibrillation, clamping, ablation, thoracoscopic surgery

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