1,541 research outputs found

    On the Crystal Structure of Phthalimide. Part I.-Determination of the Space-Group

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    Analysis of Generalized Inverted Exponential Distribution under Adaptive Type-I Progressive Hybrid Censored Competing Risks Data

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    The estimation of the unknown parameters of generalized inverted exponential distribution under adaptive type-I progressive hybrid censored scheme (AT-I PHCS) with competing risks data will be discussed. The reason why AT-I PHCS has exceeded other failure censored types; Time censored types enable analysts to accomplish their trials and experiments in a shorter time and with higher efficiency. In this regards, we obtain the maximum likelihood estimation of the parameters and the asymptotic confidence intervals for the unknown parameters. Further, Bayes estimates of the parameters which obtained based on squared error and LINEX loss functions under the assumptions of independent gamma priors of the scale parameters. For Bayesian estimation, we take advantage of Markov Chain Monte Carlo techniques to derive Bayesian estimators and the credible intervals. Finally, two data sets with Monte Carlo simulation study and a real data set are analyzed for illustrative purposes

    Étude du rapport entre la géométrie des fils et la rugosité des tissus

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    La suavidad de los tejidos es difícilmente cuantificable puesto que está asociada a una serie de sensaciones subjetivas. Se ha intentado evaluar objetivamente mediante diversos métodos. Uno de los parámetros cuantificables más importantes, que diversos autores relacionan con el tacto de los tejidos es su aspereza o rugosidad superficial. En este trabajo se estudia la relación entre la rugosidad superficial de una serie de tejidos y la deformación filar de los hilados que los constituyen; la deformación filar depende de la geometría de los hilados y esta, a su vez está condicionada por diversas variables. En el trabajo se establecen las relaciones entre la deformación filar y la composición, título y torsión de los hilados de PES/CV, en un intento de poder establecer como influyen estas variables en la rugosidad de los tejidos.The smoothness of the fabrics is hardly quantifies since is associated to a series of subjective sensations. It has been tried to evaluate objectively by means of diverse methods. One of the more important measurable parameters that diverse authors relate to the smoothless of a fabric is its superficial roughness. The present work studies the relationship between the superficial roughness of a series of fabrics and the deformation of the yarns that constitute them. The yarn deformation depends on the geometry of the yarn and this is, as well, depending of diverse variables. In the work the relationships between the yarn deformation and the account and torsion of yarns of different PES/CV compositions are also studied in an attempt of how these variables influence the superficial roughness of the fabrics.La douceur des tissus est difficilement quantifiable car elle est associée à une série de sensations subjectives. Elle a fait l'objet d'une tentative d'évaluation objective à l'aide de plusieurs méthodes. L'un des paramètres quantifiables les plus importants, que divers auteurs associent au tact des tissus, est leur âpreté ou rugosité superficielle. Cette étude porte sur le rappot entre la rugosité superficielle d'un série de tissus et la déformation filaire des filés qui les constituent; la déformation filaie dépend de la géométrie des filés et celle-ci est, à son tour, conditionnée par plusieurs variables. Des rapports son établis entre la déformation filaire et la composition, le titre et la torsion des filés de PES/CV, pour tenter d'établir comment ces variables jouent sur la rugosité des tissus

    Inferential Survival Analysis for Type II Censored Truncated Exponential Topp Leone Exponential Distribution with Application to Engineering Data

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    This study focuses on estimating the unknown parameters of the truncated exponential Topp-Leon distribution using a type II scheme. We estimate the unknown parameters, survival, and hazard functions using maximum likelihood estimation methods. Additionally, we derive the approximate variance covariance matrix and asymptotic confidence intervals. Furthermore, we compute Bayesian estimates of the unknown parameters under squared error and linear loss functions. To generate samples from the posterior density functions, we use the Metropolies-Hastings algorithm. We demonstrate the effectiveness of the proposed distribution by applying it to two data sets: Monte Carlo simulation and real data set. Our results show that the proposed distribution provides accurate estimates of the unknown parameters and performs well in fitting the data. Our findings also indicate that Bayesian estimation can provide more precise estimates with narrower confidence intervals compared to maximum likelihood estimation method. In summary, the study provides a comprehensive analysis of the estimation of the unknown parameters for the truncated exponential Topp-Leone distribution using a type II scheme. Also, the results demonstrate the potential of this distribution in modeling real data and the usefulness of both maximum likelihood and Bayesian estimation methods in obtaining accurate parameter estimates

    Parameters and Reliability Estimation of Left Truncated Gumbel Distribution under Progressive Type II Censored with Repairable Mechanical Equipment Data

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    The estimation of two parameters of the left truncated Gumbel distribution using the progressive type II censoring scheme is discussed. We first derived the maximum likelihood estimators of the unknown parameters. The approximate asymptotic variance-covariance matrix and approximate confidence intervals based on the asymptotic normality of the classical estimators are calculated. Also, the survival and hazard functions are derived. Further, the delta method is used to construct approximate confidence intervals for survival and hazard functions. Using the left truncated normal prior for the location parameter and an inverted gamma prior for the scale parameter, several Bayes estimates based on squared error and general entropy loss functions are computed. Bayes estimators of the unknown parameters cannot be calculated in closed forms. Markov chain Monte Carlo method, namely Metropolis-Hastings algorithm, has been used to derive the approximate Bayes estimates. Also, the credible intervals are constructed by using Markov chain Monte Carlo samples. Finally, The Monte Carlo simulation study compares the performances among various estimates in terms of their root mean squared errors, mean absolute biased, average confidence lengths, and coverage probabilities under different sets of values of sample sizes, number of failures and censoring schemes. Moreover, a numerical example with a real data set and Markov chain Monte Carlo data sets are tackled to highlight the importance of the proposed methods. Bayes Markov chain Monte Carlo estimates have performed better than those obtained based on the likelihood function

    Analysis of Two Generalized Exponential Populations Under Joint Type-I Progressive Hybrid Censoring Scheme

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    This paper discussed inference for two generalized exponential using the joint type-I progressively hybrid censoring (JPHC-I) scheme. It assumed that the lifetime distribution of the items from the two populations follow generalized exponential distribution. Based on the JPHC-I scheme, we first consider the maximum likelihood estimators of the unknown parameters along with thier asymptotic confidence intervals. Next, we provide the Bayesian inferences of the unknown parameters under the assumptions of independent gamma priors on the scale parameters using squared error (SE) and linear-exponential (LINEX) loss functions. Markov Chain Monte Carlo (MCMC) techniques is applied to carry out the Bayesian estimation procedure and in turn calculate the credible intervals. To evaluate the performance of the estimators, numerical example is carried out

    RESPONSE OF SYNGONIUM PODOPHYLLUM PLANT TO SOME SYNTHETIC CYTOKININ TYPES AND CONCENTRATIONS AS A FOLIAR APPLICATION

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    This investigation was executed to assess the effects of three synthetic cytokinins [6-benzylaminopurine (BAP), 6-(γ,γ-dimethylallylamino) purine (2iP) and furfurylamino-purine (kinetin)] at three concentrations for each type (100, 200 and 300 mg/l), beside the control one (tap water) on vegetative growth and some chemical analysis of Syngonium podophyllum plants. Two pot experiments were executed during the two successive seasons of 2019 and 2020 in a commercial farm in Belqas Khamis, Dakahlia Governorate, Egypt. The obtained results generally revealed that spraying of the three types and concentrations of synthetic cytokinins significantly enhanced plant height, number of leaves/plant, leaf area, foliage fresh and dry weight, root length, root fresh and dry weight compared to the control plants. Moreover, spraying of synthetic cytokinins was superior and significantly increased N%, P%, K%, total carbohydrates, total phenolics, chlorophylls and carotenoids content in leaves. Meanwhile, spraying of 2iP at 200 mg/l gave the highest values for most of the vegetative growth characters (plant height, leaves number and foliage fresh weight) and chemical composition (chlorophyll a, b, a+b, carotenoids, total carbohydrates and N, P and K contents in leaves) compared to other treatments. However, applying of kinetin at 200 mg/l gave higher values of foliage fresh and dry weight and chlorophyll a than other concentrations. Besides, spraying of BAP at 100 mg/l gave the highest roots fresh and dry weight. While spraying of BAP at 200 mg/l gave the highest value of total phenolics content compared to other treatments. Generally, the examined cytokinin types and concentrations could be arranged for their positive effects on Syngonium podophyllum descendingly as 2iP at 200 mg/l, BAP at 100 or 200 mg/l and kinetin at 200 mg/l

    Laser-Induced Breakdown Spectroscopy in Africa

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    Laser-induced breakdown spectroscopy (LIBS), known also as laser-induced plasma spectroscopy (LIPS), is a well-known spectrochemical elemental analysis technique. The field of LIBS has been rapidly matured as a consequence of growing interest in real-time analysis across a broad spectrum of applied sciences and recent development of commercial LIBS analytical systems. In this brief review, we introduce the contributions of the research groups in the African continent in the field of the fundamentals and applications of LIBS. As it will be shown, the fast development of LIBS in Africa during the last decade was mainly due to the broad environmental, industrial, archaeological, and biomedical applications of this technique

    Deep Learning based Defect classification and detection in SEM images: A Mask R-CNN approach

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    In this research work, we have demonstrated the application of Mask-RCNN (Regional Convolutional Neural Network), a deep-learning algorithm for computer vision and specifically object detection, to semiconductor defect inspection domain. Stochastic defect detection and classification during semiconductor manufacturing has grown to be a challenging task as we continuously shrink circuit pattern dimensions (e.g., for pitches less than 32 nm). Defect inspection and analysis by state-of-the-art optical and e-beam inspection tools is generally driven by some rule-based techniques, which in turn often causes to misclassification and thereby necessitating human expert intervention. In this work, we have revisited and extended our previous deep learning-based defect classification and detection method towards improved defect instance segmentation in SEM images with precise extent of defect as well as generating a mask for each defect category/instance. This also enables to extract and calibrate each segmented mask and quantify the pixels that make up each mask, which in turn enables us to count each categorical defect instances as well as to calculate the surface area in terms of pixels. We are aiming at detecting and segmenting different types of inter-class stochastic defect patterns such as bridge, break, and line collapse as well as to differentiate accurately between intra-class multi-categorical defect bridge scenarios (as thin/single/multi-line/horizontal/non-horizontal) for aggressive pitches as well as thin resists (High NA applications). Our proposed approach demonstrates its effectiveness both quantitatively and qualitatively.Comment: arXiv admin note: text overlap with arXiv:2206.1350
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