Journal articles: 'Estimation of connection'

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Wang, Shu Qing, Shi Yan Ma, Dian He Wang, and Fu Shun Liu. "Cross Modal Strain Energy Method for Estimation of Semi-Rigid Joints." Advanced Materials Research 243-249 (May 2011): 5386–93. http://dx.doi.org/10.4028/www.scientific.net/amr.243-249.5386.

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While rigid or pinned assumptions are adopted for steel frames in traditional modeling via finite element method, the actual behavior of the connections is usually neither. Semi-rigid joints enable connections to be modeled as partially restrained, which improves the quality of the model. To identify the connection stiffness and update the FE model, a newly-developed cross modal strain energy (CMSE) method is extended to incorporate the connection stiffness estimation. To illustrate the capability of the proposed parameter estimation and model updating algorithm, a four-story frame structure is demonstrated in the numerical studies. Several cases including Semi-rigid joint(s) on single connection and on multi-connections, are investigated. Numerical results indicate that an excellent updating is achievable and the connection stiffness can be estimated by CMSE method.

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Su, Fujia, Bingxuan Li, Qingyang Yin, Yanchen Zhang, and Sheng Li. "Proxy Tracing: Unbiased Reciprocal Estimation for Optimized Sampling in BDPT." ACM Transactions on Graphics 43, no. 4 (2024): 1–21. http://dx.doi.org/10.1145/3658216.

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Robust light transport algorithms, particularly bidirectional path tracing (BDPT), face significant challenges when dealing with specular or highly glossy involved paths. BDPT constructs the full path by connecting sub-paths traced individually from the light source and camera. However, it remains difficult to sample by connecting vertices on specular and glossy surfaces with narrow-lobed BSDF, as it poses severe constraints on sampling in the feasible direction. To address this issue, we propose a novel approach, called proxy sampling , that enables efficient sub-path connection of these challenging paths. When a low-contribution specular/glossy connection occurs, we drop out the problematic neighboring vertex next to this specular/glossy vertex from the original path, then retrace an alternative sub-path as a proxy to complement this incomplete path. This newly constructed complete path ensures that the connection adheres to the constraint of the narrow lobe within the BSDF of the specular/glossy surface. Unbiased reciprocal estimation is the key to our method to obtain a probability density function (PDF) reciprocal to ensure unbiased rendering. We derive the reciprocal estimation method and provide an efficiency-optimized setting for efficient sampling and connection. Our method provides a robust tool for substituting problematic paths with favorable alternatives while ensuring unbiasedness. We validate this approach in the probabilistic connections BDPT for addressing specular-involved difficult paths. Experimental results have proved the effectiveness and efficiency of our approach, showcasing high-performance rendering capabilities across diverse settings.

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Nie, Yimin, and Masami Tatsuno. "Information-Geometric Measures for Estimation of Connection Weight Under Correlated Inputs." Neural Computation 24, no. 12 (2012): 3213–45. http://dx.doi.org/10.1162/neco_a_00367.

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The brain processes information in a highly parallel manner. Determination of the relationship between neural spikes and synaptic connections plays a key role in the analysis of electrophysiological data. Information geometry (IG) has been proposed as a powerful analysis tool for multiple spike data, providing useful insights into the statistical interactions within a population of neurons. Previous work has demonstrated that IG measures can be used to infer the connection weight between two neurons in a neural network. This property is useful in neuroscience because it provides a way to estimate learning-induced changes in synaptic strengths from extracellular neuronal recordings. A previous study has shown, however, that this property would hold only when inputs to neurons are not correlated. Since neurons in the brain often receive common inputs, this would hinder the application of the IG method to real data. We investigated the two-neuron-IG measures in higher-order log-linear models to overcome this limitation. First, we mathematically showed that the estimation of uniformly connected synaptic weight can be improved by taking into account higher-order log-linear models. Second, we numerically showed that the estimation can be improved for more general asymmetrically connected networks. Considering the estimated number of the synaptic connections in the brain, we showed that the two-neuron IG measure calculated by the fourth- or fifth-order log-linear model would provide an accurate estimation of connection strength within approximately a 10% error. These studies suggest that the two-neuron IG measure with higher-order log-linear expansion is a robust estimator of connection weight even under correlated inputs, providing a useful analytical tool for real multineuronal spike data.

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Rashid, D. S., F. Giorgio-Serchi, N. Hosoya, and D. Garcia Cava. "Estimation of bolt tension using transverse natural frequencies of the shank and protruding end." Journal of Physics: Conference Series 2647, no. 18 (2024): 182005. http://dx.doi.org/10.1088/1742-6596/2647/18/182005.

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Abstract Bolted connections are crucial components in mechanical systems with the purpose of assembling different components. However, the tension of bolts may decrease due to recursive loading and environmental conditions. Monitoring the tension of bolted connections can help prevent failures and identify damage at an early stage. Vibration-based techniques have shown promising results for evaluating the tension present in a bolted connection. However, previous studies have neglected the effect of the protruding end, which can significantly affect the dynamic response of the bolted connection. In this study, a novel extended model based on an Euler-Bernoulli beam is proposed that accurately captures the effects of the protruding end on the estimation of the transverse natural frequency of the bolt. The proposed technique incorporating the transversal natural frequencies associated with the protruding end of the bolted connection provides a more representative frequency response of the bolted connection. The results show that there is a significant shift in the natural frequencies at higher modes which are associated with the protruding end. The findings have important implications for the monitoring of bolted connections and provide a basis for more accurate and reliable health and performance assessments. Further research could focus on the validation of the proposed model using experimental data and its application in practical settings.

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Sooksatra, Sorn, Toshiaki Kondo, Pished Bunnun, and Atsuo Yoshitaka. "Redesigned Skip-Network for Crowd Counting with Dilated Convolution and Backward Connection." Journal of Imaging 6, no. 5 (2020): 28. http://dx.doi.org/10.3390/jimaging6050028.

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Crowd counting is a challenging task dealing with the variation of an object scale and a crowd density. Existing works have emphasized on skip connections by integrating shallower layers with deeper layers, where each layer extracts features in a different object scale and crowd density. However, only high-level features are emphasized while ignoring low-level features. This paper proposes an estimation network by passing high-level features to shallow layers and emphasizing its low-level feature. Since an estimation network is a hierarchical network, a high-level feature is also emphasized by an improved low-level feature. Our estimation network consists of two identical networks for extracting a high-level feature and estimating the final result. To preserve semantic information, dilated convolution is employed without resizing the feature map. Our method was tested in three datasets for counting humans and vehicles in a crowd image. The counting performance is evaluated by mean absolute error and root mean squared error indicating the accuracy and robustness of an estimation network, respectively. The experimental result shows that our network outperforms other related works in a high crowd density and is effective for reducing over-counting error in the overall case.

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Locatelli, Fabiano, Konstantinos Christodoulopoulos, Michela Svaluto-Moreolo, Josep M. Fàbrega, and Salvatore Spadaro. "Machine Learning-Based in-band OSNR Estimation from Optical Spectra." IEEE Photonics Technology 31, no. 24 (2019): 1929–32. https://doi.org/10.1109/LPT.2019.2950058.

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Measuring the optical signal to noise ratio (OSNR) at certain network points is essential for failure handling, for single connection but also global network optimization. Estimating OSNR is inherently difficult in dense wavelength routed networks, where connections accumulate noise over different paths and tight filters do not allow the observation of the noise level at signal sides. We propose an in-band OSNR estimation process, which relies on a machine learning (ML) method, in particular on Gaussian process (GP) or support vector machine (SVM) regression. We acquired high-resolution optical spectra, through an experimental setup, using a Brillouin optical spectrum analyzer (BOSA), on which we applied our method and obtained excellent estimation accuracy. We also verified the accuracy of this approach for various resolution scenarios. To further validate it, we generated spectral data for different configurations and resolutions through simulations. This second validation confirmed the estimation quality of the proposed approach.

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Noda, Atsushi, Hideitsu Hino, Masami Tatsuno, Shotaro Akaho, and Noboru Murata. "Intrinsic Graph Structure Estimation Using Graph Laplacian." Neural Computation 26, no. 7 (2014): 1455–83. http://dx.doi.org/10.1162/neco_a_00603.

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A graph is a mathematical representation of a set of variables where some pairs of the variables are connected by edges. Common examples of graphs are railroads, the Internet, and neural networks. It is both theoretically and practically important to estimate the intensity of direct connections between variables. In this study, a problem of estimating the intrinsic graph structure from observed data is considered. The observed data in this study are a matrix with elements representing dependency between nodes in the graph. The dependency represents more than direct connections because it includes influences of various paths. For example, each element of the observed matrix represents a co-occurrence of events at two nodes or a correlation of variables corresponding to two nodes. In this setting, spurious correlations make the estimation of direct connection difficult. To alleviate this difficulty, a digraph Laplacian is used for characterizing a graph. A generative model of this observed matrix is proposed, and a parameter estimation algorithm for the model is also introduced. The notable advantage of the proposed method is its ability to deal with directed graphs, while conventional graph structure estimation methods such as covariance selections are applicable only to undirected graphs. The algorithm is experimentally shown to be able to identify the intrinsic graph structure.

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Chen, Chen, Yan Xing, Wei Xu, Onder Tor, Franklin Quin, and Jilei Zhang. "Ultimate direct withdrawal loads of low shear strength wooden dowels in selected wood species for furniture applications." BioResources 14, no. 4 (2019): 9214–27. http://dx.doi.org/10.15376/biores.14.4.9214-9227.

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The wood dowel pin is one of the common fasteners for connecting structural members in wooden furniture frame construction, such as chairs. The effects of dowel penetration depth, shear strengths of connection member and dowel materials, dowel surface texture, and member grain orientation on ultimate direct withdrawal loads of single dowels withdrawn from wooden materials were investigated. The main findings were that the connections using dowels and main members with low shear strength properties achieved the same ultimate direct withdrawal loads with connections using the materials with higher shear strength properties for dowels and main members. Additionally, the existing empirical equations, including shear strength properties for both dowel and main member materials used to construct dowel connections, tended to remarkably underestimate the ultimate direct withdrawal loads of the evaluated dowel connections withdrawn from the end and side grains of the tested wood species. The connection main members in this study when these two shear strength values were added together was less than 25 MPa. Both estimation expressions were modified to consider the lower shear strength effort on ultimate direct withdrawal loads of dowels evaluated in this experiment.

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Resmi, V., and S. Vijayalakshmi. "Kernel Fuzzy Clustering with Output Layer Self-Connection Recurrent Neural Networks for Software Cost Estimation." Journal of Circuits, Systems and Computers 29, no. 06 (2019): 2050091. http://dx.doi.org/10.1142/s0218126620500917.

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In the current world, the software cost estimation problem has been resolved using various newly developed methods. Significantly, the software cost estimation problems can be dealt with effectively with the recently grown recurrent neural network (RNN) than the other newly developed methods. In this paper, an improved approach is proposed to software cost estimation using Output layer self-connection recurrent neural networks (OLSRNN) with kernel fuzzy c-means clustering (KFCM). The proposed OLSRNN method follows the basics of traditional RNN models for integrating self-connections to the output layer; thereby, the output temporal dependencies are better captured. Also, the performance of neural networks is improved using the kernel fuzzy clustering algorithm to enhance software estimation results. Ultimately, five publicly available software cost estimation datasets are adapted to verify the efficacy of the proposed KFCM-OLSRNN method using the validation metrics such as MdMRE, PRED (0.25) and MMRE. The experimental results proved the efficiency of the proposed method for solving the software cost estimation problem.

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Zheng, Xuhui, Ziyan Liu, Jing Liang, Yingyu Wu, Yunlei Chen, and Qian Zhang. "Residual Learning and Multi-Path Feature Fusion-Based Channel Estimation for Millimeter-Wave Massive MIMO System." Entropy 24, no. 2 (2022): 292. http://dx.doi.org/10.3390/e24020292.

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Channel estimation is a challenging task in a millimeter-wave (mm Wave) massive multiple-input multiple-output (MIMO) system. The existing deep learning scheme, which learns the mapping from the input to the target channel, has great difficulty in estimating the exact channel state information (CSI). In this paper, we consider the quantized received measurements as a low-resolution image, and we adopt the deep learning-based image super-resolution technique to reconstruct the mm Wave channel. Specifically, we exploit a state-of-the-art channel estimation framework based on residual learning and multi-path feature fusion (RL-MFF-Net). Firstly, residual learning makes the channel estimator focus on learning high-frequency residual information between the quantized received measurements and the mm Wave channel, while abundant low-frequency information is bypassed through skip connections. Moreover, to address the estimator’s gradient dispersion problem, a dense connection is added to the residual blocks to ensure the maximum information flow between the layers. Furthermore, the underlying mm Wave channel local features extracted from different residual blocks are preserved by multi-path feature fusion. The simulation results demonstrate that the proposed scheme outperforms traditional methods as well as existing deep learning methods, especially in the low signal-to-noise-ration (SNR) region.

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Isomura, Takuya, Akimasa Takeuchi, Kenta Shimba, Kiyoshi Kotani, and Yasuhiko Jimbo. "Neuron Type Sorting Based on Connection-strength Estimation." IEEJ Transactions on Electronics, Information and Systems 133, no. 9 (2013): 1806–13. http://dx.doi.org/10.1541/ieejeiss.133.1806.

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Chang, Chaojie. "Research on Two-stage Estimation of Partially Linear Single-index Model with Longitudinal Data." Academic Journal of Science and Technology 5, no. 1 (2023): 112–15. http://dx.doi.org/10.54097/ajst.v5i1.5438.

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Partial linear single-index model is a kind of semi-parametric model with wide application. In this paper, we deal with the partial linear single-index model under longitudinal data. A "two-stage estimation method" without iteration by using local polynomial and bias correction generalized estimation equation is proposed. under some regularity conditions, the asymptotic properties of the connection function and unknown parameter estimator are investigated. Numerical simulation shows that the proposed method is robust.

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Zyga, Jacek. "Connection Between Similarity and Estimation Results of Property Values Obtained by Statistical Methods." Real Estate Management and Valuation 24, no. 3 (2016): 5–15. http://dx.doi.org/10.1515/remav-2016-0017.

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Abstract The article discusses the topic of the application range of statistical methods in estimating property value on the grounds of a comparative approach. The analysis of application effects to estimate the unitary value of properties, respectively similar and dissimilar sets of market properties, by using the method of least squares and a linear price model. The prepared test set was developed from a priori assumed explanatory variable values as well as deterministically specified dependent variables (simulated prices) which were subjected to additional modification by a random factor. On the basis of the prepared set and series of accounting experiments, the estimation effects of any property out of a tested set were analyzed, understood as the determination of the value of the function of explanatory variables in the way of extrapolation or interpolation of values describing these variables. The experiments carried out show that the estimation of an explanatory variable for a random property out of a set of elements serving as the estimation base can be reliable only when it is related to the interpolation in the set of explanatory variables of this base. The application as an estimation base – a set in relation to which explanatory variables of the estimated property exceed the limits of corresponding variables, requires the completion of a basic set with records describing properties similar or close to the estimated property so that the values of explanatory variables for the estimated property are contained in the appropriate subsections of values of corresponding explanatory variables of the basic set. The paper refers to the issue of defining property market value indicating, by the prism of conducted experiments, that the estimation results obtained by means of statistical methods do not always meet the requirements of the statutory definition of market value, and hear rather in the direction of a result corresponding to the so-called “desk appraisal” result.

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Tao, Chengkun. "Optimal Inference of Social Network Structure: A Maximum Likelihood Framework for ErdsRnyi Models." Theoretical and Natural Science 100, no. 1 (2025): 165–71. https://doi.org/10.54254/2753-8818/2025.21961.

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In contemporary society, social networks have played a conspicuous role in peoples life, yet accurately analyzing them is still challenging. This paper applies maximum likelihood estimation for ErdsRnyi graph in social network analysis. It begins with interpreting the significance of social network analysis and the objective of the research. Subsequently, theoretical knowledge of ErdsRnyi graph and Maximum Likelihood Estimation are presented, including definitions, properties, and the derivation of Maximum Likelihood Estimation calculation formula for estimating the probability of connection in ErdsRnyi graph. After that, a real-world example is involved in order to thoroughly comprehend the mechanism of this model. Through multiple trials of simulations, the accuracy of Maximum Likelihood Estimation is explored by illustrating a graph about the relationship between the number of nodes and percentage error with the help of python program, revealing the trend that a larger network size contributes to a more accurate estimation. The advantages, including simplicity and statistical rigor and disadvantages that contain the uniform assumption of connection probability and limitations are comprehensively analyzed as well, followed by a proposal of future research directions related to a more sophisticate model added by functions in order to be applied to friendship social networks, aiming to offer insights to further studies.

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Rajat Gupta. "Advanced Smart Channel Estimation Scheme for MIMO OSTBC Systems Based Wireless Communication." Journal of Electrical Systems 20, no. 7s (2024): 1853–58. http://dx.doi.org/10.52783/jes.3876.

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Labeling diversity is used in an orthogonal space-time block coded (OSTBC) scheme to improve wireless connection reliability without reducing spectral efficiency. Compared to the conventional STBC system, it achieves improved link dependability. The purpose of this work is to provide a blind wireless channel estimator that is bandwidth-efficient for the OSTBC system. Methods for channel estimation, such as least-squares (LS) & minimum mean square error (MMSE) methods typically use the channel bandwidth inefficiently. The receiver noise variance and prior broadcast pilot symbols knowledge & statistics information of channel are required for LS & MMSE channel estimating algorithms to accurately estimate the channel. An neural network machine learning (NNML) channel estimation with transmitter end power-share is suggested in order to make blind channel estimator simpler for the OSBC-based MIMO transmission & to lessen amount of bandwidth requirement for estimation of channel. By using mathematical modeling equivalent to noise power, we determine the ideal transmit fraction of power that reduces bandwidth consumption due to channel estimate. It is demonstrated that the blind NN-ML nased channel estimation with transmitter power-share uses 20% of the bandwidth of the MMSE & LS wireless channel estimators in order to achieve the OSTBC system's low bit error rate (BER) in the case of M-PSK modulation.

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Leonetti, Davide, Johan Maljaars, and H. H. (Bert) Snijder. "Reliability-based fatigue life estimation of shear riveted connections considering dependency of rivet hole failures." MATEC Web of Conferences 165 (2018): 10008. http://dx.doi.org/10.1051/matecconf/201816510008.

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Standards and guidelines for the fatigue design of riveted connections make use of a stress range-endurance (S-N) curve based on the net section stress range regardless of the number and the position of the rivets. Almost all tests on which S-N curves are based, are performed with a minimum number of rivets. However, the number of rivets in a row is expected to increase the fail-safe behaviour of the connection, whereas the number of rows is supposed to decrease the theoretical stress concentration at the critical locations, and hence these aspects are not considered in the S-N curves. This paper presents a numerical model predicting the fatigue life of riveted connections by performing a system reliability analysis on a double cover plated riveted butt joint. The connection is considered in three geometries, with different number of rivets in a row and different number of rows. The stress state in the connection is evaluated using a finite element model in which the friction coefficient and the clamping force in the rivets are considered in a deterministic manner. The probability of failure is evaluated for the main plate, and fatigue failure is assumed to be originating at the sides of the rivet holes, the critical locations, or hot-spots. The notch stress approach is applied to assess the fatigue life, considered to be a stochastic quantity. Unlike other system reliability models available in the literature, the evaluation of the probability of failure takes into account the stochastic dependence between the failures at each critical location modelled as a parallel system, which means considering the change of the state of stress in the connection when a ligament between two rivets fails. A sensitivity study is performed to evaluate the effect of the pretension in the rivet and the friction coefficient on the fatigue life.

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Mahajan, Ankush, Konstantinos Christodoulopoulos, Ricardo Martínez, Salvatore Spadaro, and Raül Muñoz. "Modeling EDFA Gain Ripple and Filter Penalties with Machine Learning for Accurate QoT Estimation." Journal of Lightwave Technology, 38, no. 9 (2020): 2616–29. https://doi.org/10.1109/JLT.2020.2975081.

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For reliable and efficient network planning and operation, accurate estimation of Quality of Transmission (QoT) before establishing or reconfiguring the connection is necessary. In optical networks, a design margin is generally included in a QoT estimation tool (Qtool) to account for modeling and parameter inaccuracies, ensuring the acceptable performance. In this article, we use monitoring information from an operating network combined with supervised machine learning (ML) techniques to understand the network conditions. In particular, we model the penalties generated due to i) Erbium Doped Fiber Amplifier (EDFA) gain ripple effect, and ii) filter spectral shape uncertainties at Reconfigurable Optical Add and Drop Multiplexer (ROADM) nodes. Enhancing the Qtool with the proposed ML regression models yields estimates for new or reconfigured connections that account for these two effects, resulting in more accurate QoT estimation and a reduced design margin. We initially propose two supervised ML regression models, implemented with Support Vector Machine Regression (SVMR), to estimate the individual penalties of the two effects and then a combined model. On Deutsche Telekom (DT) network topology with 12 nodes and 40 bidirectional links, we achieve a design margin reduction of ~1 dB for new connection requests.

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Li, Zhen, Junfeng Tian, and Pengyuan Zhao. "Software Reliability Estimate with Duplicated Components Based on Connection Structure." Cybernetics and Information Technologies 14, no. 3 (2014): 3–13. http://dx.doi.org/10.2478/cait-2014-0028.

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Abstract Reliability testing of complex software at the system level is impossible due to the environmental constraint or the time limitation, so its reliability estimate is often obtained based on the reliability of subsystems or components. The connection structure was defined and the component-based software reliability was estimated based on it. For the present popular software with duplicated components, an approach to variance estimation of software reliability for complex structure systems was proposed, which has improved the hierarchical decomposition approach of variance estimation just for series-parallel systems. Experimental results indicated that the approach to variance estimation for reliability of software with duplicated components has advantages, such as the simple calculation process, small error result, and suitability for complex structure systems. Finally, the sensitivity analysis, used to identify critical components for resource allocation, could better improve the software reliability

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Bandiyono, Agus. "The Effect of Good Corporate Governance and Political Connection on Value Firm." Jurnal Akuntansi 23, no. 3 (2020): 333. http://dx.doi.org/10.24912/ja.v23i3.599.

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This study aims to determine the effect of applying good corporate governance and political connections to firm value. The data of this study are secondary data of manufacturing companies listed on the Indonesia Stock Exchange in 2014-2016. Data were analyzed using panel data estimation. The results of this study indicate that partial corporate governance has a positive and significant effect on firm value, political connection variables have a positive and significant effect on firm value and together corporate governance and political connections have a positive and significant effect on firm value.

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Arlekar, Jaswant N., and C. V. R. Murty. "P-V-M Interaction Curves for Seismic Design of Steel Column Base Connections." Engineering Journal 39, no. 3 (2002): 154–65. http://dx.doi.org/10.62913/engj.v39i3.779.

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Recent studies on connections have shown that the beam bending theory cannot predict the flow of forces near the connection regions. In this paper, a new truss analogy model has been proposed to better represent the flow of forces near the column base connections. Also, shear moment strength envelopes, generated for different levels of axial load using the hysteretic stress-strain curves for steel, are presented. The moment and shear demand for the design of column base connection elements are calculated using the normalized P-V-M interaction curves. Appropriate strength factors applied to the moment capacity of the column section to account for the uncertainty in the estimation of yield stress, strain hardening, compactness of the section, and slenderness of the member are discussed. Finally, a generalized procedure for the capacity design of column base connections is proposed.

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Dal Lago, Bruno, Francesco Foti, and Luca Martinelli. "Seismic actions induced by cladding panels on precast concrete frame structures." International Journal of Business & Technology 6, no. 3 (2018): 1–6. http://dx.doi.org/10.33107/ijbte.2018.6.3.15.

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The strong earthquakes occurred in Southern Europe in the last decade pointed out a poor seismic performance of the connection system of the cladding of precast industrial structures. The cladding of these buildings usually consists of sandwich concrete panels of remarkable mass, connected to the frame structure with mechanical devices. The estimation of the out-of-plane seismic action on these connections is a key step for their correct proportioning. However, the formulation currently provided in the Eurocode 8 for the estimation of the seismic action on non-structural elements was calibrated with different objectives. Furthermore, given there is no in-plane structure-panel interaction, a quote of the panel mass is lumped in correspondence of their connection for a correct proportioning of the frame structure. The designers need to make assumptions on both aspects that often bring to remarkably different solutions. The paper presents a consistent dynamic formulation of the problem of the vibration of rigid bodies connected with cantilever columns. The solution brings to closed-form equations to evaluate the exact out-of-plane action on the connections and the correct amount of panel mass to be lumped.

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Yu, Xiaohong, Chen Chen, Samet Demirel, and Jilei Zhang. "Static lateral load resistance of parallel bamboo strand panel-to-metal single-bolt connections – Part 2: Fracture model." BioResources 14, no. 3 (2019): 5747–63. http://dx.doi.org/10.15376/biores.14.3.5747-5763.

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The effect of end distance was evaluated relative to the static ultimate lateral resistance load of single-shear unconstrained metal-to-parallel bamboo strand panel (PBSP) single-bolt connections that failed in end tear-out, net cross-section tension modes. Empirical equations for estimation of the static ultimate lateral resistance loads of the evaluated connections were derived. The connection consisted of a PBSP main member fastened to a metal plate as a side member using a 6 mm diameter bolt without a nut or washer. The stress concentration factor was considered in the process of deriving the estimation equations for static ultimate lateral resistance loads. The experimental results indicated that the stress concentration factor was a linear function of end-distance to bolt-diameter ratio, (e/d), for connections that failed in end tear-out mode, while a quadratic function of (e/d) for connections that failed in net cross-section tension mode. The derived estimation equations including stress concentration factor can reasonably estimate the static ultimate lateral resistance load of single-shear unconstrained metal-to-PBSP single-bolt connections evaluated in this study.

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Li, Yifan. "Parameter Recovery in Erds-Rnyi Graphs via Maximum Likelihood Estimations." Theoretical and Natural Science 105, no. 1 (2025): None. https://doi.org/10.54254/2753-8818/2025.23351.

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This study investigates the feasibility of using maximum likelihood estimation to recover the connection probability parameter in the Erdos Renyi graph model. In this model every possible edge between nodes is assumed to appear with the same probability, providing a simplified mathematical description of network structure. By deriving the probability model for the occurrence of edges in a random graph and then develop an estimation formula based on the maximum likelihood principle. A series of simulations are conducted on graphs with a fixed number of nodes and various connection probabilities. The connection probability is estimated by comparing the actual number of observed edges with the maximum number of possible edges. The simulation results indicate that when the connection probability is high the network tends to be dense and the estimated value closely matches the true value. In contrast when the connection probability is low the estimated value is more affected by random fluctuations although it still reflects the basic characteristics of the network. The findings provide theoretical support for parameter estimation in both social and computer networks and lay the foundation for further studies on parameter recovery in more complex network models.

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Ngo, Hung Q. "RECENT RESULTS ON CARDINALITY ESTIMATION AND INFORMATION THEORETIC INEQUALITIES." Journal of Computer Science and Cybernetics 37, no. 3 (2021): 223–38. http://dx.doi.org/10.15625/1813-9663/37/3/16129.

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I would like to dedicate this little exposition to Prof. Phan Dinh Dieu, one of the giants and pioneers of Mathematics in Computer Science in Vietnam. In the past 15 years or so, new and exciting connections between fundamental problems in database theory and information theory have emerged. There are several angles one can take to describe this connection. This paper takes one such angle, influenced by the author's own bias and research results. In particular, we will describe how the cardinality estimation problem -- a corner-stone problem for query optimizers -- is deeply connected to information theoretic inequalities. Furthermore, we explain how inequalities can also be used to derive a couple of classic geometric inequalities such as the Loomis-Whitney inequality. A purpose of the article is to introduce the reader to these new connections, where theory and practice meet in a wonderful way. Another objective is to point the reader to a research area with many new open questions.

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Savostyanova, O. V., and O. F. Vyacheslavova. "The Theory of Fractals as an Effective Tool for Solving Applied (engineering) Problems." Izvestiya MGTU MAMI 2, no. 1 (2008): 191–93. http://dx.doi.org/10.17816/2074-0530-69713.

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Creation of surfaces with specific properties necessary for stable product operation is an urgent need for the surface quality management of such products. Surface roughness influences joint surface performance, also influences fatigue durability and connection tightness, and in motionless connections durability depends on size of part roughness. Fractal analysis allows to estimate surface roughness irrespective of the form of its elements and distribution density that would give universality for estimation.

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Maurice Junior, Ekendeke Ndiomo, and Bin Guo. "Research on the Lifetime Estimation of Secondary Connections Using the PRP M/G/1 Queuing Network Model." Applied Mechanics and Materials 347-350 (August 2013): 2095–99. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.2095.

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Allocated Spectrum band has always been a limited resource; being later a more challenging issue due to the growth of user demands. The past decade is marked by important changes in spectrum access through especially cognitive radio technology. Here, spectrum access issue can be studied in all the different aspects of cognitive capabilities. This paper focuses on spectrum handoff in spectrum mobility. We will then study secondary connections behaviors after multiple interruptions providing from multiple secondary connections. In the IEEE 802.22 standards [, two Spectrum Handoff Sequences have been defined to characterize Secondary Connections behaviors after each Primary Connections interruption. These sequences are known as always-leaving and always-staying sequences. A recent analysis uses the extended data delivery time metric to analyze these Spectrum Handoff Sequences. It shows the exponential value of connections service time in the first sequence (always-leaving sequence) and in the other (always-staying sequence), the lack of fairness due to the acquisition of channels low-priority queue by the ongoing secondary connection (i.e. the secondary connection actually being served in the low-priority queue). Weve also noticed that the Extended Data Delivery Time is a good but limited metric because of the lack of prevision, which is a quality needed in cognitive radio networks, especially when implementing spectrum handoff sequences. Our present study aims to analyze these limitations. In what follows, we use the PRP M/G/1 queuing model in cognitive radio network to evaluate latency-sensitive traffic of Secondary Connections through a novel performance metric that we name Lifetime of Secondary Connections.

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Abed, Ghassan A., and Sawsan N. Abdullah. "Estimation of Available Bandwidth for High Capacity Links Over Industrial Applications." Journal of University of Human Development 1, no. 3 (2015): 346. http://dx.doi.org/10.21928/juhd.v1n3y2015.pp346-350.

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Transmission Control Protocol (TCP) is built on the concept of self-clocking technique and this concept based on several characteristics. The slow-start mechanism represents the prime technique for usage the operative network resource. The objective of the slow start mechanism is to create a TCP connection in an optimal state - run for network route rapidly without giving a disproportionate load to the network. Due to the rate of packet transferred is limited by the bandwidth of the narrowest bottleneck alongside the connection pipe, then, the transferring rate cannot exceed this bandwidth and the maximum rate competitions the permissible bandwidth of the link that own narrowest bandwidth over end-to-end connections. In large bandwidth networks, the mechanism of slow-start does not perform suitably and may cause considerable degradation in network performance. Therefore, it's necessary to develop a new slow-start technique that can increase the packet transferring over large bandwidth links environments. This article investigates the behaviour of TCP protocol after applying a technique based on using available bandwidth estimation to detect the current level of the network slow-start threshold (ssthresh) in high capacity links used over industrial application.

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Czepiżak, Dariusz, and Rajmund Ignatowicz. "Load capacity analysis of unsymmetrical welded overlay connection." Inżynieria i Budownictwo LXXIX, no. 9-10 (2023): 458–62. http://dx.doi.org/10.5604/01.3001.0053.8867.

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The paper analyses the load capacity of an atypical tensile connection with an overlay placed asymmetrically and welded to the connected flat bars with a 3 mm thick one-sided L-shaped fillet weld. Tensile force is applied to the axis of the flat bars. In this asymmetrical connection, a double eccentricity of load transfer appears. The purpose of the analysis is to check whether standard norm models to estimate the load capacity of these connections are appropriate and safe. The article compares the results of the analysis according to Eurocode 3, the SOFiSTiK program, IDEA StatiCa program, and the experimental tests. Eurocode 3 calculation procedures proved to be conservative. The estimation of the load carrying capacity of the joint closest to the results of experimental studies was obtained in the SOFiSTiK program

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Bannor, Gyasi Alfred, Samuel Kwaku Boadu, and Yarhands Dissou Arthur. "EFFECTS OF TEACHING QUALITY, TEACHING COMPETENCE, AND MATHEMATICS CONNECTION ON MATHEMATICS ACHIEVEMENT MOTIVATION AMONG SENIOR HIGH SCHOOL STUDENTS IN GHANA." Matrix Science Mathematic 7, no. 2 (2023): 63–68. http://dx.doi.org/10.26480/msmk.02.2023.63.68.

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This survey assessed the direct effects of teaching quality, teaching competence and mathematics connection on mathematics achievement motivation in Senior high School students in Ghana. A descriptive survey was used in the study, which included 329 senior high school students from Barekese Senior High School. Prior to the main model estimation, preliminary studies such as Confirmatory Factor Analysis, convergent validity, discriminant validity, and internal consistency (Cronbach’s Alpha) were computed. Amos (v.23) was used to do structural equation modeling (SEM) in order to assess the various assumptions. The results of path estimations revealed that mathematics connection positively and significantly influenced mathematics achievement motivation. However, teaching quality and teaching competence has no significant impact on mathematics achievement motivation.

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Hu, Ying, Zi Xiong Chen, Ming Kui Xiao, Ying Ming Li, and Yong Jun Liu. "Assessment of Connection Ductility in Fire." Applied Mechanics and Materials 353-356 (August 2013): 2305–12. http://dx.doi.org/10.4028/www.scientific.net/amm.353-356.2305.

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Catenary action has been regarded as a viable load-carrying mechanism in fire for providing structural robustness to steel framed buildings, and this loading mechanism heavily relies on connection strength and ductility under exceptional loading conditions. However, the current code of practice has no detailed guidance on estimation of the connection ductility. This paper is dedicated to demonstration of how to quantify connection ductility in a fire or non-fire situation through the component-based approach. Connection ductility has been evaluated with emphasis on elongation and strength of connection components in each bolt row, and response of brittle components has been identified as an index for connection ductility and failure mechanism in a fire situation.

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Riera, Marc, José María Arnau, and Antonio González. "DNN pruning with principal component analysis and connection importance estimation." Journal of Systems Architecture 122 (January 2022): 102336. http://dx.doi.org/10.1016/j.sysarc.2021.102336.

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Venables, W. N., and K. W. Morris. "A Connection Between Minimum Variance Unbiased Estimation and Maximum Likelihood." American Statistician 43, no. 2 (1989): 118. http://dx.doi.org/10.2307/2684516.

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Venables, W. N., and K. W. Morris. "A Connection between Minimum Variance Unbiased Estimation and Maximum Likelihood." American Statistician 43, no. 2 (1989): 118–21. http://dx.doi.org/10.1080/00031305.1989.10475633.

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KOBAYASHI, Takashi, and Yoshikazu KAWAMORI. "329 Estimation of Leak Rate of a Gasketed Flanged Connection." Proceedings of Yamanashi District Conference 2001 (2001): 101–2. http://dx.doi.org/10.1299/jsmeyamanashi.2001.101.

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Eden, Talya, Dana Ron, and C. Seshadhri. "Sublinear Time Estimation of Degree Distribution Moments: The Arboricity Connection." SIAM Journal on Discrete Mathematics 33, no. 4 (2019): 2267–85. http://dx.doi.org/10.1137/17m1159014.

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Liao, Kefei, Zerui Yu, Ningbo Xie, and Junzheng Jiang. "Joint Estimation of Azimuth and Distance for Far-Field Multi Targets Based on Graph Signal Processing." Remote Sensing 14, no. 5 (2022): 1110. http://dx.doi.org/10.3390/rs14051110.

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Target position estimation is one of the important research directions in array signal processing. In recent years, the research of target azimuth estimation based on graph signal processing (GSP) has sprung up, which provides new ideas for the Direction of Arrival (DoA) application. In this article, by extending GSP-based DOA to joint azimuth and distance estimation and constructing a fully connected graph signal model, a multi-target joint azimuth and distance estimation method based on GSP is proposed. Firstly, the fully connection graph model is established related to the phase information of a linear array. For the fully connection graph, the Fourier transform method is used to solve the estimated response function, and the one-dimensional estimation of azimuth and distance is completed, respectively. Finally, the azimuth and distance estimation information are combined, and the false points in the merging process are removed by using CLEAN algorithm to complete the two-dimensional estimation of targets. The simulation results show that the proposed method has a smaller mean square error than the Multiple Signal Classification (MUSIC) algorithm in azimuth estimation under the condition of a low signal-to-noise ratio and more accurate response values than the MUSIC algorithm in distance estimation under any signal-to-noise ratio in multi-target estimation.

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Uehara, Kiyohiko, and Kaoru Hirota. "Fuzzy Inference Based Connection Admission Control in ATM Networks." Journal of Advanced Computational Intelligence and Intelligent Informatics 1, no. 1 (1997): 14–22. http://dx.doi.org/10.20965/jaciii.1997.p0014.

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A connection admission control (CAC) method is proposed for asynchronous transfer mode (ATM) networks by applying the fuzzy inference and learning algorithm of neural networks. In order to guarantee the allowed cell loss ratio (CLR) in CAC, the upper bound of CLR must be used as the criterion for judging whether an incoming call can be accepted or not. For estimating the upper bound of CLR from observed CLR data, fuzzy inference, based on a weighted mean of fuzzy sets, is adopted. This inference method can effectively estimate the possibility distribution of CLR by applying the error back-propagation algorithm with the proposed energy functions in learning and provide the upper bound of CLR efficiently from the distribution. A self-compensation mechanism for estimation errors is also provided, which is simple enough to work in real time by taking advantage of the fuzzy inference method adopted. Fuzzy rules in the area with no observed data are generated by extrapolation from adjacent fuzzy rules in the area with observed data. This increases the multiplex gain, thereby guaranteeing the allowed CLR as much as possible. The simulation results show the feasibility of the proposed CAC method.

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Kim, Woo-Hyun, Ye-Chan Kim, and Seung-Ho Song. "Estimation and Application for Line Impedance Between IBR and POM." Energies 18, no. 12 (2025): 3135. https://doi.org/10.3390/en18123135.

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With the increasing integration of Inverter-Based Resources (IBRs) into power grids, accurate estimation of line impedance between the Point of Connection (POC) and the Point of Measurement (POM) has become critical to ensure stable and efficient reactive power control. However, conventional impedance estimation methods often face challenges such as power quality degradation and sensitivity to voltage unbalance. This paper presents a method to improve the reactive power control performance of Inverter-Based Resources (IBRs) by estimating the line impedance between the Point of Connection (POC) and the Point of Measurement (POM) and utilize the estimated impedance into control. The impact of voltage drop caused by line impedance on reactive power delivery is analyzed, and a compensation method is designed to mitigate the resulting control errors. The line impedance is estimated through a negative-sequence current injection technique, under the condition that the voltage phases at the two measurement points are synchronized. To address potential voltage unbalance issues that may arise during the injection process, a dedicated compensation algorithm is also proposed. The proposed algorithm is validated through both simulations and lab-scale experiments, demonstrating that the line impedance can be estimated with an error of less than 2%, while effectively compensating for reactive power distortion at the POM.

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Chen, Jenn Yih, and Bean Yin Lee. "Adaptive Parameter Estimation and Position Control of Induction Motors Based on Passivity Theorem." Materials Science Forum 626-627 (August 2009): 489–94. http://dx.doi.org/10.4028/www.scientific.net/msf.626-627.489.

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This paper presents the passivity-based rotor resistance and mechanical paramters estimation, and the position control for induction motors. Firstly, the input-output linearization theory is employed to decouple the rotor flux amplitude and the rotor position at the transient state. An open-loop current model flux observer then estimates the rotor flux. Furthermore, we adopted the gradient algorithm to design adaptive laws to estimate the rotor resistance, moment of inertia, viscous coefficient, and load torque. The passive properties of the feedback connection of the rotor flux observer to the rotor resistance estimator, and the position controller are analyzed by the passivity theorem. According to the properties, the overall control system is proved to be globally stable without using Lyapunov-type arguments. Finally, experimental results are provided to show that the proposed method is robust to variations of the mechanical parameters and load torque disturbances. Moreover, good position tracking response and parameters estimating characteristic can be obtained.

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Mohammed, Douaa Raheem, and Murtada A. Ismael. "Effect of Semi-Rigid Connection on Post-Buckling Behaviour of Frames Using Finite Element Method." Civil Engineering Journal 5, no. 7 (2019): 1619–30. http://dx.doi.org/10.28991/cej-2019-03091358.

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It is very important task to estimate the post buckling for structures that have slender elements, since post-buckling state means loss the structures stability related with large displacement and that lead to demolition the structures. On the other hand, in the design and analysis of steel frame, the beam-columns connection is assumed perfect pin or fully rigid, this assumption leads to incorrect estimation of the structural behaviour. Practically, beam-column connection is between these two assumptions and this type of connection is called semi-rigid. This study presents a numerical analysis using finite element method to investigate the effect of semi-rigid connections on post-buckling behaviour of two-dimensional frames with different supporting types and different lateral loading cases. The semi-rigid connections are modelled as rotational spring in linear elastic stage, using COMBIN14 element which has rotational stiffness value. The numerical results showed that; the effect of changing the beam-column connections from rigid to semi rigid for toggle frame with rotational joint stiffness 25EI/L to 15EI/L and 10EI/L led to decrease the initial peak load of the frames of fixed-fixed supports with percentages 3.36 %, 5.6% and 8.95% respectively as compared with that of the rigid connection frame, While, the frames with fixed-pin and pin-pin supports cases did not affected by this changing. The fixed-fixed support case is more affected by changing the joint stiffness from other cases and the effect of changing the joint stiffness in pin-pin support model is less significant from others. This can be attributed to that, the fixed-fixed supports is restrained in all degree of freedom and will be affected by any rotation and presence the pin in other cases makes the frame less affected by the rotation of semi-rigid connection. The effect of changing the beam-column connection from rigid to semi rigid decreases with presence the lateral load. Thus, the semi-rigid connection should be considered in analysis and design of steel frames to obtain more realistic results.

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Jäntschi, Lorentz. "A Test Detecting the Outliers for Continuous Distributions Based on the Cumulative Distribution Function of the Data Being Tested." Symmetry 11, no. 6 (2019): 835. http://dx.doi.org/10.3390/sym11060835.

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One of the pillars of experimental science is sampling. Based on the analysis of samples, estimations for populations are made. There is an entire science based on sampling. Distribution of the population, of the sample, and the connection among those two (including sampling distribution) provides rich information for any estimation to be made. Distributions are split into two main groups: continuous and discrete. The present study applies to continuous distributions. One of the challenges of sampling is its accuracy, or, in other words, how representative the sample is of the population from which it was drawn. To answer this question, a series of statistics have been developed to measure the agreement between the theoretical (the population) and observed (the sample) distributions. Another challenge, connected to this, is the presence of outliers - regarded here as observations wrongly collected, that is, not belonging to the population subjected to study. To detect outliers, a series of tests have been proposed, but mainly for normal (Gauss) distributions—the most frequently encountered distribution. The present study proposes a statistic (and a test) intended to be used for any continuous distribution to detect outliers by constructing the confidence interval for the extreme value in the sample, at a certain (preselected) risk of being in error, and depending on the sample size. The proposed statistic is operational for known distributions (with a known probability density function) and is also dependent on the statistical parameters of the population—here it is discussed in connection with estimating those parameters by the maximum likelihood estimation method operating on a uniform U(0,1) continuous symmetrical distribution.

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Molodtsov, Vladimir Vladimirovich, and Andrey Yurevich Barbin. "Reasonable Choice of Motorized Spindles with HSK Tool Connection." Applied Mechanics and Materials 607 (July 2014): 229–34. http://dx.doi.org/10.4028/www.scientific.net/amm.607.229.

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The article describes the problem of reasonable choice of parameters of main motion drive of modern multi-purpose machine tools. Authors propose a multi-purpose methodological model for reasonable estimation of operational capabilities of motorized spindles and efficiency of equipment usage for performing of required technological operations. Dependencies are provided considering influence of HSK connection on operational parameters of drives.

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Wang, Pan. "Modeling and Estimation of Production Rate in Ornamental Stones Sawing Based on Brittleness Indexes." Mathematical Problems in Engineering 2019 (February 13, 2019): 1–12. http://dx.doi.org/10.1155/2019/3232517.

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As for estimating the cost and planning the process of the rock sawing plants, it is significant to predict the production rate of ornamental stones sawing. To promote the efficiency in planning these rock sawing projects, scholars have been trying to find a high-accuracy method of production rate estimation. Moreover, targeting at the 28 granite and carbonates stone in the nature, this study examined the connection between two various brittleness indexes in statistics, including the ratio of compressive strength to tensile strength (B1) and places below the line of compressive strength and the line of tensile strength (B2) in rocks and production rate had been studied. Through the results of cross plots analysis, it was indicated that there existed a strong connection between production rate and the brittleness B1 and B2. Finally, in this thesis, through adding B1 factor, it has improved the estimation model for production rate which Mikaeil et al. (2013) have established. What’s more, by virtue of brittleness about B1 and B2, this production rate estimation model has been established successfully for natural stone sawing. Actually, the way of estimating the production rate of 28 rock samples is to utilize the two kinds of models described before. Through the result, it is showed that the production rate estimated by the improved model corresponds to the value of production rate of rock testing. Meanwhile, the precision has been greatly improved with comparison to the model of estimating the production rate designed by Mikaeil et al. (2013). Thus, on the basis of the new model, a dependable prediction for ornamental stones production is put forward in this paper. And it is required to do a further study involving different rock types since limited rock types were used in this study.

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Kowalczuk, Zdzisław, and Mariusz Domżalski. "Asynchronous distributed state estimation for continuous-time stochastic processes." International Journal of Applied Mathematics and Computer Science 23, no. 2 (2013): 327–39. http://dx.doi.org/10.2478/amcs-2013-0025.

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The problem of state estimation of a continuous-time stochastic process using an Asynchronous Distributed multi-sensor Estimation (ADE) system is considered. The state of a process of interest is estimated by a group of local estimators constituting the proposed ADE system. Each estimator is based, e.g., on a Kalman filter and performs single sensor filtration and fusion of its local results with the results from other/remote processors to compute possibly the best state estimates. In performing data fusion, however, two important issues need to be addressed namely, the problem of asynchronism of local processors and the issue of unknown correlation between asynchronous data in local processors. Both the problems, along with their solutions, are investigated in this paper. Possible applications and effectiveness of the proposed ADE approach are illustrated by simulated experiments, including a non-complete connection graph of such a distributed estimation system.

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Rahman, Imran Ur, Mohsin Shafi, Liu Junrong, Enitilina Tatiani M. K. Fetuu, Shah Fahad, and Buddhi Prasad Sharma. "Infrastructure and Trade: An Empirical Study Based on China and Selected Asian Economies." SAGE Open 11, no. 3 (2021): 215824402110360. http://dx.doi.org/10.1177/21582440211036082.

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We empirically determine the role of different forms of infrastructure on a country’s trade. We use an augmented gravity model that incorporates infrastructure in the estimation of merchandise trade flows. We take panel data, including China and 21 selected Asian economies, from 1999 to 2018. We find that the panel ordinary least squares (OLS) and poisson pseudo maximum likelihood (PPML) model estimations prove to be significant. Proxies for Transport Infrastructure including roads, railways, and sea transport, and Proxies for information and communication technology (ICT) infrastructure consisting of mobile, electricity, and internet connections show a strong and positive impact on trade while air transport and landline phone connection have an unexpected negative effect on trade. The positive estimates for quality of infrastructure signify that high standards of Transport and ICT infrastructures lead to increased trade flows of the exporting and importing countries. Results also show that cultural similarity leads to increased trade flows between China and its trading partners in Asia.

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Jang, Yeong Min Jang. "Estimation and Prediction-Based Connection Admission Control in Broadband Satellite Systems." ETRI Journal 22, no. 4 (2000): 40–50. http://dx.doi.org/10.4218/etrij.00.0100.0405.

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Isomura, Takuya, Akimasa Takeuchi, Kenta Shimba, Kiyoshi Kotani, and Yasuhiko Jimbo. "Connection-strength Estimation of Neuronal Networks by Fitting for Izhikevich Model." IEEJ Transactions on Electronics, Information and Systems 132, no. 10 (2012): 1581–88. http://dx.doi.org/10.1541/ieejeiss.132.1581.

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Kwon, Soo-Ahn, Jae-Jun Lee, Hak-Yong Moon, and Seung-Ki Ryu. "An Estimation of Piezoelectric Power as Connection Methods of Piezoelectric Ceramic." Journal of the Korean Society of Road Engineers 14, no. 2 (2012): 37–44. http://dx.doi.org/10.7855/ijhe.2012.14.2.037.

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Hoomod, Haider K., and Mohammed Radi. "Fuzzy-Estimation Control for Improvement Microwave Connection for Iraq Electrical Grid." Journal of Physics: Conference Series 1003 (May 2018): 012034. http://dx.doi.org/10.1088/1742-6596/1003/1/012034.

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Babu, Prabhu, and Petre Stoica. "Connection between SPICE and Square-Root LASSO for sparse parameter estimation." Signal Processing 95 (February 2014): 10–14. http://dx.doi.org/10.1016/j.sigpro.2013.08.011.

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Journal articles on the topic 'Estimation of connection'

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