Search results for: signal detection theory

Authors: Djeddi Khaled, Houssou Hind, Miloudi Abdellatif, Rabah Siham

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In the field of veterinary medicine, there is a growing application of artificial intelligence (AI) for diagnosing bovine mastitis, a prevalent inflammatory disease in dairy cattle. AI technologies, such as automated milking systems, have streamlined the assessment of key metrics crucial for managing cow health during milking and identifying prevalent diseases, including mastitis. These automated milking systems empower farmers to implement automatic mastitis detection by analyzing indicators like milk yield, electrical conductivity, fat, protein, lactose, blood content in the milk, and milk flow rate. Furthermore, reports highlight the integration of somatic cell count (SCC), thermal infrared thermography, and diverse systems utilizing statistical models and machine learning techniques, including artificial neural networks, to enhance the overall efficiency and accuracy of mastitis detection. According to a review of 15 publications, machine learning technology can predict the risk and detect mastitis in cattle with an accuracy ranging from 87.62% to 98.10% and sensitivity and specificity ranging from 84.62% to 99.4% and 81.25% to 98.8%, respectively. Additionally, machine learning algorithms and microarray meta-analysis are utilized to identify mastitis genes in dairy cattle, providing insights into the underlying functional modules of mastitis disease. Moreover, AI applications can assist in developing predictive models that anticipate the likelihood of mastitis outbreaks based on factors such as environmental conditions, herd management practices, and animal health history. This proactive approach supports farmers in implementing preventive measures and optimizing herd health. By harnessing the power of artificial intelligence, the diagnosis of bovine mastitis can be significantly improved, enabling more effective management strategies and ultimately enhancing the health and productivity of dairy cattle. The integration of artificial intelligence presents valuable opportunities for the precise and early detection of mastitis, providing substantial benefits to the dairy industry.

Keywords: artificial insemination, automatic milking system, cattle, machine learning, mastitis

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Authors: Setareh Shekarsaraei, Marjan Moridi, Nasser L. Hadipour

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In this study, nuclear magnetic resonance spectroscopy and nuclear quadrupole resonance spectroscopy parameters of 14N (Nitrogen in imidazole ring) in N–H…O hydrogen bonding for Histidine hydrochloride monohydrate were calculated via density functional theory. We considered a five-molecule model system of Histidine hydrochloride monohydrate. Also, we examined the trends of environmental effect on hydrogen bonds as well as cooperativity. The functional used in this research is M06-2X which is a good functional and the obtained results have shown good agreement with experimental data. This functional was applied to calculate the NMR and NQR parameters. Some correlations among NBO parameters, NMR, and NQR parameters have been studied which have shown the existence of strong correlations among them. Furthermore, the geometry optimization has been performed using M062X/6-31++G(d,p) method. In addition, in order to study cooperativity and changes in structural parameters, along with increase in cluster size, natural bond orbitals have been employed.

Keywords: hydrogen bonding, density functional theory (DFT), natural bond orbitals (NBO), cooperativity effect

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Authors: Yun-Tao Zhang, Jong-Yeop Bae, Whoi-Yul Kim

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Background modeling and subtraction in video analysis has been widely proved to be an effective method for moving objects detection in many computer vision applications. Over the past years, a large number of approaches have been developed to tackle different types of challenges in this field. However, the dynamic background and illumination variations are two of the most frequently occurring issues in the practical situation. This paper presents a new two-layer model based on codebook algorithm incorporated with local binary pattern (LBP) texture measure, targeted for handling dynamic background and illumination variation problems. More specifically, the first layer is designed by block-based codebook combining with LBP histogram and mean values of RGB color channels. Because of the invariance of the LBP features with respect to monotonic gray-scale changes, this layer can produce block-wise detection results with considerable tolerance of illumination variations. The pixel-based codebook is employed to reinforce the precision from the outputs of the first layer which is to eliminate false positives further. As a result, the proposed approach can greatly promote the accuracy under the circumstances of dynamic background and illumination changes. Experimental results on several popular background subtraction datasets demonstrate a very competitive performance compared to previous models.

Keywords: background subtraction, codebook model, local binary pattern, dynamic background, illumination change

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Authors: Mariam Musaddiq, Muhammad Ali Asadullah

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Psychological safety is referred as a 'nonthreatening' and 'predictable' work environment leading employees, particularly interested to contribute positively to the organization, to engage and express their true selves at work without suffering negative results. We posit that the employee who is feeling psychologically safe experiences positive emotions, feels happy and shows helping behavior towards his coworkers and supervisors. Particularly, the supervisor reciprocates this helping behavior in form of greater satisfaction to the employee showing helping behavior. We tested our hypothesis in light of Feedback system theory and functional motive theory. We collected data from 453 employees and their supervisor in Pakistani hotels and restaurants through survey method. Result showed that positive affect and helping behavior mediate the relationship between psychological safety and supervisor satisfaction. Cross sectional design of the study is a major limitation of the study. Moreover, we focused on psychological safety only that is one of three dimensions of psychological conditions.

Keywords: affect, helping behavior, psychological safety, supervisor, supervisor satisfaction

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Authors: Salem El-Tohami Ashoor

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A novel new vanadium (IV) complexes incorporating the chelating diamido cyclopentadienyl {ArN(CH2)3NAr)}2-((ηn-Cp)Cp)} (Ar = 2,6-Pri2C6H3)(Cp = C5H5 and n = 1,2,3,4 and 5) have been studied with calculation of the properties of species involved in various of cyclopentadienyl reaction. These were carried out under investigation of density functional theory (DFT) calculation, and comparing together. Other methods, explicitly including electron correlation, are necessary for more accurate calculations; MB3LYP (Becke) (Lee–Yang–Parr) level of theory often being used to obtain more exact results. These complexes were estimated of electronic energy for molecular system, because it accounts for all electron correlation interactions. The optimised of [V(ArN(CH2)3NAr)2Cl(η5-Cp)] (Ar = 2,6-Pri2C6H3 and Cp= C5H5) was found to be thermally more stable than others of vanadium cyclopentadienyl. In the meantime the complex [V(ArN(CH2)3NAr)2Cl(η1-Cp)] (Ar = 2,6-Pri2C6H3 and Cp= C5H5) which is showed a low thermal stability in case of the just one carbon of cyclopentadienyl can be insertion with vanadium metal centre. By using Dewar-Chatt-Duncanson model, as a basis of the molecular orbital (MO) analysis and showed the highest occupied molecular orbital (HOMO) and lowest occupied molecular orbital LUMO.

Keywords: vanadium (IV) cyclopentadienyl complexes, DFT, MO, HOMO, LUMO

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Authors: Mukunda Bastola, Frank Nyame-Asiamah

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Economics explanation for privatisation, drawing on neo-liberal market structures and technical efficiency principles has failed to address social imbalance and, distribute the efficiency benefits accrued from privatisation equitably among service users and different classes of people in society. Stakeholders’ interest, which cover ethical values and changing human needs are ignored due to shareholders’ profit maximising strategy with higher service charges. The consequence of these is that, the existing justifications for privatisation have fallen short of customer quality expectations because the underlying plan-based models fail to account for the nuances of customer expectations. We draw on the theory of deferred action to develop a context-based privatisation model, the deferred-based privatisation model, to explain how privatisation could be strategised for the emergent reality of the wider stakeholders’ interests and everyday quality demands of customers which are unpredictable.

Keywords: privatisation, service quality, shareholders, deferred action, deferred-based privatisation model

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Authors: Muriel Canas-Walker

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The 2012 TV series "The Legend of Zhen Huan" is one of the most popular and influential historical dramas on Chinese television and is regularly discussed on Chinese social media such as Weibo. Set in the Qing dynasty, the 76 episodes series features palace intrigues focused on female characters. In the Forbidden City, concubines must survive the cruelty of an extreme polygamy system, constantly competing against each other. The patriarchal oppression of the women sequestred in the harem relies on fierce female competition and does not leave much room for compassion. Using Michel Foucault’s theory of power, feminist theories, and visual anthropology, this paper analyzes the complex relationships between the female characters, from their rise to power to their fall from grace, from alliances to betrayals, from sorority to sororicide. This analysis aims to understand what makes this series particularly popular with young female audiences in China and explain its importance in Chinese media.

Keywords: Chinese TV Drama, feminism, popular culture, Theory of Power

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Authors: Roy. H. A. Lindelauf

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Cyberattacks are complex processes consisting of multiple interwoven tasks conducted by a set of agents. Interdictions and defenses against such attacks often rely on cyber kill chain (CKC) models. A CKC is a framework that tries to capture the actions taken by a cyber attacker. There exists a growing body of literature on CKCs. Most of this work either a) describes the CKC with respect to one or more specific cyberattacks or b) discusses the tools and technologies used by the attacker at each stage of the CKC. Defenders, facing scarce resources, have to decide where to allocate their resources given the CKC and partial knowledge on the tools and techniques attackers use. In this presentation CKCs are analyzed through the lens of covert projects, i.e., interrelated tasks that have to be conducted by agents (human and/or computer) with the aim of going undetected. Various aspects of covert project models have been studied abundantly in the operations research and game theory domain, think of resource-limited interdiction actions that maximally delay completion times of a weapons project for instance. This presentation has investigated both cooperative and non-cooperative game theoretic covert project models and elucidated their relation to CKC modelling. To view a CKC as a covert project each step in the CKC is broken down into tasks and there are players of which each one is capable of executing a subset of the tasks. Additionally, task inter-dependencies are represented by a schedule. Using multi-glove cooperative games it is shown how a defender can optimize the allocation of his scarce resources (what, where and how to monitor) against an attacker scheduling a CKC. This study presents and compares several cooperative game theoretic solution concepts as metrics for assigning resources to the monitoring of agents.

Keywords: cyber defense, cyber kill chain, game theory, information warfare techniques

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Authors: Can Mungan, Gokhan Kilic

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Structural engineers and tunnel owners have good reason to attach importance to the assessment and inspection of tunnels. Regular inspection is necessary to maintain and monitor the health of the structure not only at the present time but throughout its life cycle. Detection of flaws within the structure, such as corrosion and the formation of cracks within the internal elements of the structure, can go a long way to ensuring that the structure maintains its integrity over the course of its life. Other issues that may be detected earlier through regular assessment include tunnel surface delamination and the corrosion of the rebar. One advantage of new technology such as the ground penetrating radar (GPR) is the early detection of imperfections. This study will aim to discuss and present the effectiveness of GPR as a tool for assessing the structural integrity of the heavily used tunnel. GPR is used with various antennae in frequency and application method (2 GHz and 500 MHz GPR antennae). The paper will attempt to produce a greater understanding of structural defects and identify the correct tool for such purposes. Conquest View with 3D scanning capabilities was involved throughout the analysis, reporting, and interpretation of the results. This study will illustrate GPR mapping and its effectiveness in providing information of value when it comes to rebar position (lower and upper reinforcement). It will also show how such techniques can detect structural features that would otherwise remain unseen, as well as moisture ingress.

Keywords: tunnel, GPR, health monitoring, moisture ingress, rebar position

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Authors: Mohammad R. Jalali, Mohammad M. Jalali

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The earliest theories of sloshing waves and solitary waves based on potential theory idealisations and irrotational flow have been extended to be applicable to more realistic domains. To this end, the computational fluid dynamics (CFD) methods are widely used. Three-dimensional CFD methods such as Navier-Stokes solvers with volume of fluid treatment of the free surface and Navier-Stokes solvers with mappings of the free surface inherently impose high computational expense; therefore, considerable effort has gone into developing depth-averaged approaches. Examples of such approaches include Green–Naghdi (GN) equations. In Cartesian system, GN velocity profile depends on horizontal directions, x-direction and y-direction. The effect of vertical direction (z-direction) is also taken into consideration by applying weighting function in approximation. GN theory considers the effect of vertical acceleration and the consequent non-hydrostatic pressure. Moreover, in GN theory, the flow is rotational. The present study illustrates the application of GN equations to propagation of sloshing waves and solitary waves. For this purpose, GN equations solver is verified for the benchmark tests of Gaussian hump sloshing and solitary wave propagation in shallow basins. Analysis of the free surface sloshing of even harmonic components of an initial Gaussian hump demonstrates that the GN model gives predictions in satisfactory agreement with the linear analytical solutions. Discrepancies between the GN predictions and the linear analytical solutions arise from the effect of wave nonlinearities arising from the wave amplitude itself and wave-wave interactions. Numerically predicted solitary wave propagation indicates that the GN model produces simulations in good agreement with the analytical solution of the linearised wave theory. Comparison between the GN model numerical prediction and the result from perturbation analysis confirms that nonlinear interaction between solitary wave and a solid wall is satisfactorilly modelled. Moreover, solitary wave propagation at an angle to the x-axis and the interaction of solitary waves with each other are conducted to validate the developed model.

Keywords: Green–Naghdi equations, nonlinearity, numerical prediction, sloshing waves, solitary waves

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Authors: Bashir Ahmad Aasim, Abdul Khaliq Karimi, Jun Tomiyama

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Material aging is one of the vital issues among all the civil, mechanical, and aerospace engineering societies. Sustenance and reliability of concrete, which is the widely used material in the world, is the focal point in civil engineering societies. For few decades, researchers have been able to present some form algorithms that could lead to evaluate a structure globally rather than locally without harming its serviceability and traffic interference. The algorithms could help presenting different methods for evaluating structures non-destructively. In this paper, a non-destructive vibration-based damage detection method is adopted to evaluate two concrete beams, one being in a healthy state while the second one contains a crack on its bottom vicinity. The study discusses that damage in a structure affects modal parameters (natural frequency, mode shape, and damping ratio), which are the function of physical properties (mass, stiffness, and damping). The assessment is carried out to acquire the natural frequency of the sound beam. Next, the vibration response is recorded from the cracked beam. Eventually, both results are compared to know the variation in the natural frequencies of both beams. The study concludes that damage can be detected using vibration characteristics of a structural member considering the decline occurred in the natural frequency of the cracked beam.

Keywords: concrete beam, natural frequency, non-destructive testing, vibration characteristics

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Authors: Tarek Dandashi

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WSNs may provide a fast and reliable solution for the early detection of environment events like forest fires. This is crucial for alerting and calling for fire brigade intervention. Sensor nodes communicate sensor data to a host station, which enables a global analysis and the generation of a reliable decision on a potential fire and its location. A WSN with TinyOS and nesC for the capturing and transmission of a variety of sensor information with controlled source, data rates, duration, and the records/displaying activity traces is presented. We propose a similarity distance (SD) between the distribution of currently sensed data and that of a reference. At any given time, a fire causes diverging opinions in the reported data, which alters the usual data distribution. Basically, SD consists of a metric on the Cumulative Distribution Function (CDF). SD is designed to be invariant versus day-to-day changes of temperature, changes due to the surrounding environment, and normal changes in weather, which preserve the data locality. Evaluation shows that SD sensitivity is quadratic versus an increase in sensor node temperature for a group of sensors of different sizes and neighborhood. Simulation of fire spreading when ignition is placed at random locations with some wind speed shows that SD takes a few minutes to reliably detect fires and locate them. We also discuss the case of false negative and false positive and their impact on the decision reliability.

Keywords: forest fire, WSN, wireless sensor network, algortihm

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Authors: Sahani Rathnasiri, Pritee Ray, Sardar M. N. Isalm, Carlos A. Vega-Mejia

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This study develops a cooperative game theory-based cost-sharing contract model for a business to consumer (B2C) e-commerce supply chain to minimize the overall supply chain costs and the individual costs within an information asymmetry scenario. The objective of this study is to address the issues of strategic interactions among the key players of the e-commerce supply chain operation, which impedes the optimal operational outcomes. Game theory has been included in the field of supply chain management to resolve strategic decision-making issues; however, most of the studies are limited only to two-echelons of the supply chains. Multi-echelon supply chain optimizations based on game-theoretic models are less explored in the previous literature. This study adopts a cooperative game model to focus on the common payoff of operations and addresses the issues of information asymmetry and coordination of a three-echelon e-commerce supply chain. The cost-sharing contract model integrates operational features such as production, inventory management and distribution with the contract related constraints. The outcomes of the model highlight the importance of maintaining lower operational costs by all players to obtain benefits from the cost-sharing contract. Further, the cost-sharing contract ensures true cost revelation, and hence eliminates the information asymmetry issues among the players. Comparing the results of the contract model with the de-centralized e-commerce supply chain operation further emphasizes that the cost-sharing contract derives Pareto-improved outcomes and minimizes the costs of overall e-commerce supply chain operation.

Keywords: cooperative game theory, cost-sharing contract, e-commerce supply chain, information asymmetry

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Authors: Farmesk Abubaker, Francesco Tortorici, Marco Capogni, Concetta Sutera, Vincenzo Bellini

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This project concerns with the detection efficiency of the portable triple-to-double coincidence ratio (TDCR) at the National Institute of Metrology of Ionizing Radiation (INMRI-ENEA) which allows direct activity measurement and radionuclide standardization for pure-beta emitter or pure electron capture radionuclides. The dependency of the simulated detection efficiency of the TDCR, by using Monte Carlo simulation Geant4 code, on the Birks factor (kB) and defocusing parameter has been examined especially for low energy beta-emitter radionuclides such as 3H and 14C, for which this dependency is relevant. The results achieved in this analysis can be used for selecting the best kB factor and the defocusing parameter for computing theoretical TDCR parameter value. The theoretical results were compared with the available ones, measured by the ENEA TDCR portable detector, for some pure-beta emitter radionuclides. This analysis allowed to improve the knowledge of the characteristics of the ENEA TDCR detector that can be used as a traveling instrument for in-situ measurements with particular benefits in many applications in the field of nuclear medicine and in the nuclear energy industry.

Keywords: Birks constant, defocusing parameter, GEANT4 code, TDCR parameter

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Authors: Ganesh B. Shinde, Vijaya B. Musande

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Cotton crop identification based on the timely information has significant advantage to the different implications of food, economic and environment. Due to the significant advantages, the accurate detection of cotton crop regions using supervised learning procedure is challenging problem in remote sensing. Here, classifiers on the direct image are played a major role but the results are not much satisfactorily. In order to further improve the effectiveness, variety of vegetation indices are proposed in the literature. But, recently, the major challenge is to find the better vegetation indices for the cotton crop identification through the proposed methodology. Accordingly, fuzzy c-means clustering is combined with neural network algorithm, trained by Levenberg-Marquardt for cotton crop classification. To experiment the proposed method, five LISS-III satellite images was taken and the experimentation was done with six vegetation indices such as Simple Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green Atmospherically Resistant Vegetation Index, Wide-Dynamic Range Vegetation Index, Green Chlorophyll Index. Along with these indices, Green Leaf Area Index is also considered for investigation. From the research outcome, Green Atmospherically Resistant Vegetation Index outperformed with all other indices by reaching the average accuracy value of 95.21%.

Keywords: Fuzzy C-Means clustering (FCM), neural network, Levenberg-Marquardt (LM) algorithm, vegetation indices

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Authors: Himanshu Sharma, Karthik Kumar, Harish Kumar

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The major problem in crop cultivation is the occurrence of multiple crop diseases. During the growth stage, timely identification of crop diseases is paramount to ensure the high yield of crops, lower production costs, and minimize pesticide usage. In most cases, crop diseases produce observable characteristics and symptoms. The Surveyors usually diagnose crop diseases when they walk through the fields. However, surveyor inspections tend to be biased and error-prone due to the nature of the monotonous task and the subjectivity of individuals. In addition, visual inspection of each leaf or plant is costly, time-consuming, and labour-intensive. Furthermore, the plant pathologists and experts who can often identify the disease within the plant according to their symptoms in early stages are not readily available in remote regions. Therefore, this study specifically addressed early detection of leaf scald, red rot, and eyespot types of diseases within sugarcane plants. The study proposes a computer vision-based approach using a convolutional neural network (CNN) for automatic identification of crop diseases. To facilitate this, firstly, images of sugarcane diseases were taken from google without modifying the scene, background, or controlling the illumination to build the training dataset. Then, the testing dataset was developed based on the real-time collected images from the sugarcane field from India. Then, the image dataset is pre-processed for feature extraction and selection. Finally, the CNN-based Visual Geometry Group (VGG) model was deployed on the training and testing dataset to classify the images into diseased and healthy sugarcane plants and measure the model's performance using various parameters, i.e., accuracy, sensitivity, specificity, and F1-score. The promising result of the proposed model lays the groundwork for the automatic early detection of sugarcane disease. The proposed research directly sustains an increase in crop yield.

Keywords: automatic classification, computer vision, convolutional neural network, image processing, sugarcane disease, visual geometry group

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Authors: R. Bennai, H. Ait Atmane, H. Fourne, B. Ayache

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In this work, an analytical approach using a refined theory of hyperbolic shear deformation of a beam was developed to study the buckling of graduated sandwiches beams under different boundary conditions. The effects of transverse shear strains and the transverse normal deformation are considered. The constituent materials of the beam are supposed gradually variable depending on the height direction based on a simple power distribution law in terms of the volume fractions of the constituents; the two materials with which we worked are metals and ceramics. The core layer is taken homogeneous and made of an isotropic material; while the banks layers consist of functionally graded materials with a homogeneous fraction compared to the middle layer. In the end, illustrative examples are presented to show the effects of changes in different parameters such as (material graduation, the stretching effect of the thickness, boundary conditions and thickness ratio-length) on the vibration free of an FGM sandwich beams.

Keywords: FGM materials, refined shear deformation theory, stretching effect, buckling

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Authors: Thapanee Musiget

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Ethnic minority children’s language learning is believed that it can be developed through school system. However, many cases prove that these kids are left to challenge with multicultural context at school and sometimes decreased the ability to acquire new learning. Consequently, it is significant for ethnicity parents to consider that prompting their children at home before their actual school age can eliminate negative outcome of children's language acquisition. This paper discusses the approach of instructional use of parents and children language learning in the context of minority language group in Thailand. By conducting this investigation, secondary source of data was gathered with the purpose to point out some primary methods for parents and children in ethnicity. The process of language learning is based on the sociocultural theory of Vygotsky, which highlights expressive communication among individuals as the best motivating force in human development and learning. The article also highlights the role of parents as they lead the instruction approach. In the discussion part, the role of ethnic minority parents as a language instructor is offered as mediator.

Keywords: ethnic minority, language learning, multicultural context, sociocultural theory

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Authors: Amir Moslemi, Amir movafeghi, Shahab Moradi

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One of the most important challenging factors in medical images is nominated as noise.Image denoising refers to the improvement of a digital medical image that has been infected by Additive White Gaussian Noise (AWGN). The digital medical image or video can be affected by different types of noises. They are impulse noise, Poisson noise and AWGN. Computed tomography (CT) images are subjected to low quality due to the noise. The quality of CT images is dependent on the absorbed dose to patients directly in such a way that increase in absorbed radiation, consequently absorbed dose to patients (ADP), enhances the CT images quality. In this manner, noise reduction techniques on the purpose of images quality enhancement exposing no excess radiation to patients is one the challenging problems for CT images processing. In this work, noise reduction in CT images was performed using two different directional 2 dimensional (2D) transformations; i.e., Curvelet and Contourlet and Discrete wavelet transform(DWT) thresholding methods of BayesShrink and AdaptShrink, compared to each other and we proposed a new threshold in wavelet domain for not only noise reduction but also edge retaining, consequently the proposed method retains the modified coefficients significantly that result in good visual quality. Data evaluations were accomplished by using two criterions; namely, peak signal to noise ratio (PSNR) and Structure similarity (Ssim).

Keywords: computed tomography (CT), noise reduction, curve-let, contour-let, signal to noise peak-peak ratio (PSNR), structure similarity (Ssim), absorbed dose to patient (ADP)

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Authors: Gubhinder Kundhi, Paul Rilstone

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Refined procedures for higher-order asymptotic theory for non-linear models are developed. These include a new method for deriving stochastic expansions of arbitrary order, new methods for evaluating the moments of polynomials of sample averages, a new method for deriving the approximate moments of the stochastic expansions; an application of these techniques to gather improved inferences with the weak instruments problem is considered. It is well established that Instrumental Variable (IV) estimators in the presence of weak instruments can be poorly behaved, in particular, be quite biased in finite samples. In our application, finite sample approximations to the distributions of these estimators are obtained using Edgeworth and Saddlepoint expansions. Departures from normality of the distributions of these estimators are analyzed using higher order analytical corrections in these expansions. In a Monte-Carlo experiment, the performance of these expansions is compared to the first order approximation and other methods commonly used in finite samples such as the bootstrap.

Keywords: edgeworth expansions, higher order asymptotics, saddlepoint expansions, weak instruments

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Authors: Lin Wenli, Fu Linchun, Zhang Yi, Wu Ming

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To meet the demands of long-life and high-intelligence for satellites, the electrical power system should be provided with self-health condition evaluation capability. Any over-stress events in operations should be recorded. Based on Linear stresses accumulation damage theory, accumulative damage analysis was performed on thermal-mechanical-electrical united stresses for three components including the solar array, the batteries and the power conditioning unit. Then an overall health percentage evaluation model for satellite electrical power system was built. To obtain the accurate quantity for system health percentage, an automatic feedback closed-loop correction method for all coefficients in the evaluation model was present. The evaluation outputs could be referred as taking earlier fault-forecast and interventions for Ground Control Center or Satellites self.

Keywords: satellite electrical power system, health percentage, linear stresses accumulation damage, evaluation model

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Authors: Shizra Waris, Bilal Shoaib, Munib Ahmad

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Background; The using of clinical decision support systems (CDSSs) may recover unceasing disease organization, which requires regular visits to multiple health professionals, treatment monitoring, disease control, and patient behavior modification. The objective of this survey is to determine if these CDSSs improve the processes of unceasing care including diagnosis, treatment, and monitoring of diseases. Though artificial intelligence is not a new idea it has been widely documented as a new technology in computer science. Numerous areas such as education business, medical and developed have made use of artificial intelligence Methods: The survey covers articles extracted from relevant databases. It uses search terms related to information technology and viral hepatitis which are published between 2000 and 2016. Results: Overall, 80% of studies asserted the profit provided by information technology (IT); 75% of learning asserted the benefits concerned with medical domain;25% of studies do not clearly define the added benefits due IT. The CDSS current state requires many improvements to hold up the management of liver diseases such as HCV, liver fibrosis, and cirrhosis. Conclusion: We concluded that the planned model gives earlier and more correct calculation of hepatitis B and it works as promising tool for calculating of custom hepatitis B from the clinical laboratory data.

Keywords: detection, hapataties, observation, disesese

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Authors: Mohamed Ayoub

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We perform computational investigation using density functional theory, B3LYP with aug-cc-pVTZ basis set followed by natural bond orbital analysis (NBO), which provides best single “natural Lewis structure” (NLS) representation of chosen wavefunction (Ψ) with natural resonance theory (NRT) to provide an analysis of molecular electron density in terms of resonance structures (RS) and weights (w). We selected for the study a wide range of gas phase dimers (B…HA), with hydrogen bond dissociation energies (ΔEB…H) that span more than two orders of magnitude. We demonstrate that charge transfer from a donor Lewis-type NBO (nB:) to an acceptor non-Lewis-type NBO (σHA*) is the primary cause for H-bonding not classical electrostatic (dipole-dipole or ionic). We provide a variety of structure, and spectroscopic descriptors to support the conclusion, such as IR frequency shift (ΔνHA), H-bond penetration distance (ΔRB..H), bond order (bB..H), charge-transfer (CTB→HA) and the corresponding donor-acceptor stabilization energy (ΔE(2)).

Keywords: natural bond orbital, hydrogen bonding, electron donor, electron acceptor

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Authors: Morteza Keshavarz

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In this work, using density functional theory (DFT) thermodynamic stability and quantum molecular descriptors of cyclophoshphamide (an anticancer drug)-functionalized zigzag (8,0) CNT, armchair (4,4) CNT and nanocone complexes in water, for two attachment namely the sidewall and tip, is considered. Calculation of the total electronic energy (Et) and binding energy (Eb) of all complexes indicates that the most thermodynamic stability belongs to the sidewall-attachment of cyclophosphamide into functional nanocone. On the other hand, results from chemical hardness show that drug-functionalized zigzag (8,0) and armchair (4,4) complexes in the tip-attachment configuration possess the smallest and greatest chemical hardness, respectively. By computing the solvation energy, it is found that the solution of the drug and all complexes are spontaneous in water. Furthermore, chirality, type of nanovector (nanotube or nanocone), or attachment configuration have no effects on solvation energy of complexes.

Keywords: carbon nanotube, drug delivery, cyclophosphamide drug, density functional theory (DFT)

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Authors: Mai Alshareef

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The Saudi government considers the modernisation of the education system as a critical component of the national development plan, Saudi Vision 2030; however, this sudden reform creates tension amongst Saudis. This study examines first the reflection of the social and digital education reform on stakeholders and the general Saudi public, and second, the influence of information and communication technologies (ICTs) on the ethnoreligious conflict in Saudi Arabia. This study employs Cyberconflict theory to examine conflicts in the real world and cyberspace. The findings are based on a qualitative case study methodology that uses netnography, an analysis of 3,750 Twitter posts and semi-structural interviews with 30 individuals, including key actors in the Saudi education sector and Twitter activists during 2019\2020. The methods utilised are guided by thematic analysis to map an understanding of factors that influence societal conflicts in Saudi Arabia, which in this case include religious, national, and gender identity. Elements of Cyberconflict theory are used to better understand how conflicting groups build their identities in connection to their ethnic/religious/cultural differences and competing national identities. The findings correspond to the ethnoreligious components of the Cyberconflict theory. Twitter became a battleground for liberals, conservatives, the Saudi public and elites, and it is used in a novel way to influence public opinion and to challenge the media monopoly. Opposing groups relied heavily on a discourse of exclusion and inclusion and showed ethnic and religious affiliations, national identity, and chauvinism. The findings add to existing knowledge in the cyberconflict field of study, and they also reveal outcomes that are critical to the Saudi Arabian national context.

Keywords: education, cyberconflict, Twitter, national identity

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Authors: J. J. Rickard, A. Belli, P. Goldberg Oppenheimer

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Medical diagnostics, environmental monitoring, homeland security and forensics increasingly demand specific and field-deployable analytical technologies for quick point-of-care diagnostics. Although technological advancements have made optical methods well-suited for miniaturization, a highly-sensitive detection technique for minute sample volumes is required. Raman spectroscopy is a well-known analytical tool, but has very weak signals and hence is unsuitable for trace level analysis. Enhancement via localized optical fields (surface plasmons resonances) on nanoscale metallic materials generates huge signals in surface-enhanced Raman scattering (SERS), enabling single molecule detection. This enhancement can be tuned by manipulation of the surface roughness and architecture at the sub-micron level. Nevertheless, the development and application of SERS has been inhibited by the irreproducibility and complexity of fabrication routes. The ability to generate straightforward, cost-effective, multiplex-able and addressable SERS substrates with high enhancements is of profound interest for SERS-based sensing devices. While most SERS substrates are manufactured by conventional lithographic methods, the development of a cost-effective approach to create nanostructured surfaces is a much sought-after goal in the SERS community. Here, a method is established to create controlled, self-organized, hierarchical nanostructures using electrohydrodynamic (HEHD) instabilities. The created structures are readily fine-tuned, which is an important requirement for optimizing SERS to obtain the highest enhancements. HEHD pattern formation enables the fabrication of multiscale 3D structured arrays as SERS-active platforms. Importantly, each of the HEHD-patterned individual structural units yield a considerable SERS enhancement. This enables each single unit to function as an isolated sensor. Each of the formed structures can be effectively tuned and tailored to provide high SERS enhancement, while arising from different HEHD morphologies. The HEHD fabrication of sub-micrometer architectures is straightforward and robust, providing an elegant route for high-throughput biological and chemical sensing. The superior detection properties and the ability to fabricate SERS substrates on the miniaturized scale, will facilitate the development of advanced and novel opto-fluidic devices, such as portable detection systems, and will offer numerous applications in biomedical diagnostics, forensics, ecological warfare and homeland security.

Keywords: hierarchical electrohydrodynamic patterning, medical diagnostics, point-of care devices, SERS

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Authors: Anne Kariuki, Kellen Kiambati

Abstract:

The broad objective of this study was to establish the mediating effect of media visibility on the relationship between corporate Social Responsibility (CSR) and the corporate performance of firms listed on the Nairobi Securities Exchange. The review of the literature provided conceptual and empirical gaps that formed the basis of the conceptual hypotheses. A survey questionnaire was distributed to the 50 heads of human resource departments in the different firms. A survey was conducted on fifty (50) companies listed on the Nairobi Securities Exchange. The study findings reported a significant relationship between CSR and non-financial performance and the mediating role of media visibility on the relationship between CSR and performance. The findings of the study support the signaling theory and stakeholder’s theory. Conclusively, CSR activities have an effect on media visibility, which in turn affects performance.

Keywords: corporate social responsibility, media visibility, corporate performance, non-financial performance

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Authors: A. I. Khalafalla, K. A. Al-Busada, I. M. El-Sabagh

Abstract:

Pox and pox-like diseases of camels are a group of exanthematous skin conditions that have become increasingly important economically. They may be caused by three distinct viruses: camelpox virus (CMPV), camel contagious ecthyma virus (CCEV) and camel papillomavirus (CAPV). These diseases are difficult to differentiate based on clinical presentation in disease outbreaks. Molecular methods such as PCR targeting species-specific genes have been developed and used to identify CMPV and CCEV, but not simultaneously in a single tube. Recently, multiplex PCR has gained reputation as a convenient diagnostic method with cost- and time–saving benefits. In the present communication, we describe the development, optimization and validation a multiplex PCR assays able to detect simultaneously the genome of the three viruses in one single test allowing for rapid and efficient molecular diagnosis. The assay was developed based on the evaluation and combination of published and new primer sets, and was applied to the detection of 110 tissue samples. The method showed high sensitivity, and the specificity was confirmed by PCR-product sequencing. In conclusion, this rapid, sensitive and specific assay is considered a useful method for identifying three important viruses in specimens from camels and as part of a molecular diagnostic regime.

Keywords: multiplex PCR, diagnosis, pox and pox-like diseases, camels

Procedia PDF Downloads 468

Authors: Ehsan Vaziri Goodarzi, Mahmood Houshmand, Omid Fatahi Valilai, Vahidreza Ghezavati, Shahrooz Bamdad

Abstract:

One important paradigm of industry 4.0 is Cloud Manufacturing (CM). In CM everything is considered as a service, therefore, the CM platform should consider all service provider's capabilities and tries to integrate services in an equilibrium state. This research develops a framework for implementing manufacturing cloud service composition in the equilibrium state. The developed framework using well-known tools called axiomatic design (AD) and game theory. The research has investigated the factors for forming equilibrium for measures of the manufacturing cloud service composition. Functional requirements (FRs) represent the measures of manufacturing cloud service composition in the equilibrium state. These FRs satisfied by related Design Parameters (DPs). The FRs and DPs are defined by considering the game theory, QoS, consumer needs, parallel and cooperative services. Ultimately, four FRs and DPs represent the framework. To insure the validity of the framework, the authors have used the first AD’s independent axiom.

Keywords: axiomatic design, manufacturing cloud service composition, cloud manufacturing, industry 4.0

Procedia PDF Downloads 173

Authors: Neda Razavi Kaleibar, Bahloul Salmani

Abstract:

The present study dealt with the multimodal analysis of two cinematic adaptations of The Great Gatsby as intersemiotic translation. The assessment in this study went beyond the faithfulness based on repetition, addition, deletion, and creation which limit the analysis from other aspects. In fact, this research aimed to pinpoint the role of multimodality in examining the intersemiotic translations of the novel into film by means of analyzing different applied modes. Through a qualitative type of research, the analysis was conducted based on the theory proposed by Burn as Kineikonic mode theory derived from the concept of multimodality. The results of the study revealed that due to the applied modes, each adaptation represents a sense and meaning different from the other one. Analyzing the results and discussions, it was concluded that not only the modes have an undeniable role in film adaptations, but rather multimodal analysis including different nonverbal modes can be a useful and functional choice for analyzing the intersemiotic translations.

Keywords: cinematic adaptation, intersemiotic translation, kineikonic mode, multimodality

Procedia PDF Downloads 421