Journal articles on the topic 'Node importance estimation'
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1
Fatemi, Zahra, and Elena Zheleva. "Minimizing Interference and Selection Bias in Network Experiment Design." Proceedings of the International AAAI Conference on Web and Social Media 14 (May 26, 2020): 176–86. http://dx.doi.org/10.1609/icwsm.v14i1.7289.
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Current approaches to A/B testing in networks focus on limiting interference, the concern that treatment effects can "spill over" from treatment nodes to control nodes and lead to biased causal effect estimation. Prominent methods for network experiment design rely on two-stage randomization, in which sparsely-connected clusters are identified and cluster randomization dictates the node assignment to treatment and control. Here, we show that cluster randomization does not ensure sufficient node randomization and it can lead to selection bias in which treatment and control nodes represent different populations of users. To address this problem, we propose a principled framework for network experiment design which jointly minimizes interference and selection bias. We introduce the concepts of edge spillover probability and cluster matching and demonstrate their importance for designing network A/B testing. Our experiments on a number of real-world datasets show that our proposed framework leads to significantly lower error in causal effect estimation than existing solutions.
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Jia, Shijie, Tianyin Wang, Xiaoyan Su, and Liuke Liang. "A Novel Video Propagation Strategy Fusing User Interests and Social Influences Based on Assistance of Key Nodes in Social Networks." Electronics 12, no. 3 (January 19, 2023): 532. http://dx.doi.org/10.3390/electronics12030532.
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Accurate video launching and propagation is significant for promotion and distribution of videos. In this paper, we propose a novel video propagation strategy that fuses user interests and social influences based on the assistance of key nodes in social networks (VPII). VPII constructs an estimation model for video distribution capacities in the process of video propagation by investigating interest preference and influence of social users: (1) An estimation method of user preferences for video content is designed by integrating a comparative analysis between current popular videos and historical popular videos. (2) An estimation method to determine the distribution capacities of videos is designed according to scale and importance of neighbor nodes covered. VPII further designs a multi-round video propagation strategy with the assistance of the selected key nodes, which enables these nodes to implement accurate video launching by estimating weighted levels based on available bandwidth and node degree centrality. The video propagation can effectively promote the scale and speed of video sharing and efficiently utilize network resources. Simulations-based testing shows how VPII outperforms other state-of-the-art solutions in terms of startup delay, caching hit ratio, caching cost and higher control overhead.
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Geier, Christian, and Klaus Lehnertz. "Which Brain Regions are Important for Seizure Dynamics in Epileptic Networks? Influence of Link Identification and EEG Recording Montage on Node Centralities." International Journal of Neural Systems 27, no. 01 (November 8, 2016): 1650033. http://dx.doi.org/10.1142/s0129065716500337.
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Nodes in large-scale epileptic networks that are crucial for seizure facilitation and termination can be regarded as potential targets for individualized focal therapies. Graph-theoretical approaches based on centrality concepts can help to identify such important nodes, however, they may be influenced by the way networks are derived from empirical data. Here we investigate evolving functional epileptic brain networks during 82 focal seizures with different anatomical onset locations that we derive from multichannel intracranial electroencephalographic recordings from 51 patients. We demonstrate how the various methodological steps (from the recording montage via node and link inference to the assessment of node centralities) affect importance estimation and discuss their impact on the interpretability of findings in the context of pathophysiological aspects of seizure dynamics.
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Murayama, Toru. "Articulation Node Importance Estimation and Its Correctness for Robustness of Multi-robot Network." IFAC-PapersOnLine 51, no. 22 (2018): 166–71. http://dx.doi.org/10.1016/j.ifacol.2018.11.536.
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Liu, Chao, and Zhongshan Zhang. "Towards a robust FANET: Distributed node importance estimation-based connectivity maintenance for UAV swarms." Ad Hoc Networks 125 (February 2022): 102734. http://dx.doi.org/10.1016/j.adhoc.2021.102734.
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Islam, Tariq, and Yong Kyu Lee. "A Two-Stage Localization Scheme with Partition Handling for Data Tagging in Underwater Acoustic Sensor Networks." Sensors 19, no. 9 (May 8, 2019): 2135. http://dx.doi.org/10.3390/s19092135.
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Knowledge about the geographic coordinates of underwater sensor nodes is of primary importance for many applications and protocols of under water sensor networks (UWSNs) thus making localization of sensor nodes a crucial part of underwater network design. In case of mobile underwater sensor network, location estimation becomes challenging not only due to the need for periodic tracking of nodes, but also due to network partitioning caused by the pseudo-random mobility of nodes. Our proposed technique accomplishes the task of localization in two stages: (1) relative localization of sensor nodes with respect to a reference node at regular intervals during sensing operation. (2) Offline absolute localization of sensor nodes using absolute coordinates of the reference node and relative locations estimated during stage 1. As our protocol deals with mobile underwater sensor networks that may introduce network partitioning, we also propose a partition handling routine to deal with network partitions to achieve high localization coverage. The major design goal of our work is to maximize localization coverage while keeping communication overhead minimum, thus achieving better energy efficiency. Major contributions of this paper are: (1) Two energy efficient relative localization techniques, and (2) A partition handling strategy that ensures localization of partitioned nodes.
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Wang, Zheng Jun, Xiao Ou Jin, Guo Qiang Fu, and Dian Min Sun. "Experimental Method and Research Evolution of Strength Prediction of Cement Concrete." Advanced Materials Research 250-253 (May 2011): 1071–76. http://dx.doi.org/10.4028/www.scientific.net/amr.250-253.1071.
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That griping and predicting concrete strength is crucial importance for shorten design cycle of cement concrete proportion and control efficiently key construction node in time. The paper exposited systematically experimental method of strength estimation of cement concrete and corresponding research progress at present, and the prospect was also analyzed. It is very necessary to promote research work of experiment and analysis method because strength estimation of cement concrete is paramount. It has important meaning for delving into the aspect through above discussion in the future.
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Jokic, Aleksandar, Jovana Grahovac, Jelena Dodic, Zoltan Zavargo, Sinisa Dodic, Stevan Popov, and Damjan Vucurovic. "Interpreting the neural networkfor prediction of fermentation of thick juice from sugar beet processing." Acta Periodica Technologica, no. 42 (2011): 241–49. http://dx.doi.org/10.2298/apt1142241j.
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Methods that can provide adequate accuracy in the estimation of variables from incomplete information are desirable for the prediction of fermentation processes. A feed-forward back-propagation artificial neural network was used for modelling of thick juice fermentation. Fermentation time and starting sugar content were usedas input variables, i.e. nodes. Neural network had one output node (ethanol content, yeast cell number or sugar content). The hidden layer had nine neurons. Garson's algorithm and connection weights were used for interpreting neural network. The inadequacy of Garson's algorithm can be seen by comparing with the results of regression analysis, which indicates that the influence of the fermentation time is higher. A better agreement of the results was obtained using network connection weights, a method that can be used to determine the relative importance of input variables.
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Liu, Li, A. Sankarasubramanian, and S. Ranji Ranjithan. "Logistic regression analysis to estimate contaminant sources in water distribution systems." Journal of Hydroinformatics 13, no. 3 (October 28, 2010): 545–57. http://dx.doi.org/10.2166/hydro.2010.106.
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Accidental or intentional contamination in a water distribution system (WDS) has recently attracted attention due to the potential hazard to public health and the complexity of the contaminant characteristics. The accurate and rapid characterization of contaminant sources is necessary to successfully mitigate the threat in the event of contamination. The uncertainty surrounding the contaminants, sensor measurements and water consumption underscores the importance of a probabilistic description of possible contaminant sources. This paper proposes a rapid estimation methodology based on logistic regression (LR) analysis to estimate the likelihood of any given node as a potential source of contamination. Not only does this algorithm yield location-specific probability information, but it can also serve as a prescreening step for simulation–optimization methods by reducing the decision space and thus alleviating the computational burden. The applications of this approach to two example water networks show that it can efficiently rule out numerous nodes that do not yield contaminant concentrations to match the observations. This elimination process narrows down the search space of the potential contamination locations. The results also indicate that the proposed method efficiently yields a good estimation even when some noise is incorporated into the measurements and demand values at the consumption nodes.
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Stroeven, Piet, Nghi L. B. Le, Lambertus J. Sluys, and Huan He. "POROSIMETRY BY RANDOM NODE STRUCTURING IN VIRTUAL CONCRETE." Image Analysis & Stereology 31, no. 2 (May 17, 2012): 79. http://dx.doi.org/10.5566/ias.v31.p79-87.
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Two different porosimetry methods are presented in two successive papers. Inspiration for the development came from the rapidly-exploring random tree (RRT) approach used in robotics. The novel methods are applied to virtual cementitious materials produced by a modern concurrent algorithm-based discrete element modeling system, HADES. This would render possible realistically simulating all aspects of particulate matter that influence structure-sensitive features of the pore network structure in maturing concrete, namely size, shape and dispersion of the aggregate and cement particles. Pore space is a complex tortuous entity. Practical methods conventionally applied for assessment of pore size distribution may fail or present biased information. Among them, mercury intrusion porosimetry and 2D quantitative image analysis are popular. The mathematical morphology operator “opening” can be applied to sections and even provide 3D information on pore size distribution, provided isotropy is guaranteed. However, aggregate grain surfaces lead to anisotropy in porosity. The presented methods allow exploration of pore space in the virtual material, after which pore size distribution is derived from star volume measurements. In addition to size of pores their continuity is of crucial importance for durability estimation. Double-random multiple tree structuring (DRaMuTS), introduced earlier in IA&S (Stroeven et al., 2011b) and random node structuring (RaNoS) provide such information.
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Jia, Feng, and Yang Song. "UAV Automation Control System Based on an Intelligent Sensor Network." Journal of Sensors 2022 (August 21, 2022): 1–12. http://dx.doi.org/10.1155/2022/7143194.
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With the widespread use of UAVs, it is gradually difficult for single UAV to meet the needs of increasingly complex scenarios. At the same time, the problems of low autonomy and high dependence on control stations in central UAV cluster networks are gradually highlighted. In this paper, we analyze the theoretical conditions of network topology establishment and network connectivity, design a series of UAV distributed cluster automation control algorithm frameworks, and achieve certain research results, taking the distributed clusters of flight self-organizing networks as the background and using mathematical tools such as algebraic graph theory and random geometry to build a vibration sensor array model based on multiple intelligent sensor management. Based on this, a distributed connectivity maintenance algorithm based on the importance of nodes is designed to realize the “self-healing” of the flight’s self-organizing network. This study also improves the Mavlink flight control communication protocol customization and Zigbee wireless networking mode design to solve the UAV swarm communication link collision problem. Compared with the existing distributed spectrum estimation-based node importance algorithm, the proposed algorithm further analyzes the topological changes caused by the removal of associated edges by failed nodes and the reconstruction of new associated edges between neighboring nodes, so that the theoretical results are closer to the actual topological dynamics of the flight self-organizing network.
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Dawson, Leelavathi, Ketan Garg, and Sakshi Choudhary. "Estimation of tumor volume and its prognostic significance to study the biological behavior of carcinoma of cervix." Asian Journal of Oncology 02, no. 01 (January 2016): 035–42. http://dx.doi.org/10.4103/2454-6798.180592.
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Abstract Objective: The objective of this study was to assess a correlation between tumor volume, the spread and metastatic potential of the tumor. Materials and Methods: A prospective study was done on 40 cases of carcinoma of cervix with stage IIb or less. The hysterectomy specimens alongwith the lymph nodes were sent to the histopathology department. Clinical details were taken from gynecology department. Hematoxylin and eosin slides were prepared and seen. Tumor volume was calculated by using the formula TV = π/6×Length×Width×Depth. Immunohistochemistry for Fibronectin and LN5 was also done. Results: The median age of the patients in this group was 47.5 years, with a range of 30–80 years. The major histological type of carcinoma among 40 cases is squamous cell carcinoma (SCC) (in 90% of cases), and 10% had adenocarcinoma. Pathological staging of the carcinoma cervix showed stage Ib, IIa, IIb, and IVa (35%, 20%, 40%, and 5%). Tumor volume estimated on pathological specimens of 40 cases ranged from 230 cumm to 49,760 cumm with a mean of 14,844 cumm. 12 (30%) cases had tumor volume more than 15,000 cumm, 12 (30%) cases had tumor volume <5000 cumm and 16 (40%) cases had tumor volume between 5000 and 15,000 cumm. 17% of the tumors with tumor volume <5000 cumm showed lymph node metastases, whereas 67% (out of 12cases) of cases with tumor volume more than 15,000 cumm showed lymph node metastases. 67% of the tumors with tumor volume <5000 cumm showed 0/4 organs involvement, whereas all cases with tumor volume more than 15,000 cumm showed more than one organ involvement among vagina, uterus, parametrium or bladder/rectum. Fibronectin positivity was seen in 22 out of 44 cases (55%). Macrophages were seen surrounding the group of tumor cells by LN5 immunostaining. Conclusion: Tumor volume can be considered as an independent prognostic factor to assess the spread of the tumor. Cases with tumor volume <5000 cumm show low risk in terms of parametrial involvement and lymph node metastasis and those with tumor volume more than 15,000 cumm showed more organ spread. Fibronectin positivity carries some importance in low-risk cases. For macrophages, further detailed study needs to be carried out.
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Tsikitis, Vassiliki Liana, David Larson, Christina Preece, Spyros Tsavaridis, and Patricia Thompson. "Copy number differences in EGFR and other amplicons between primary colon tumors and paired lymph node metastasis." Journal of Clinical Oncology 30, no. 4_suppl (February 1, 2012): 498. http://dx.doi.org/10.1200/jco.2012.30.4_suppl.498.
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498 Background: Prior study, demonstrating differential immunohistochemical EGFR expression between the primary colon cancer and the liver metastasis, suggested possible molecular differences between the two tumor sites. This questions the relevance of obtaining genomic information from the primary tumor to guide adjuvant treatment. In this study we examine whether there are genomic differences specific to metastatic nodes versus the paired colon primary samples. Methods: Using 30 primary and lymph node metastasis pairs (dissected for >80% tumor from paraffin embedded tissue), we obtained a dataset of copy number derived from the Affymetrix Oncoscan Molecular Inversion Probe platform. Using the Nexus Copy Number software for processing, we used the default automatic segmentation of the copy number data with a threshold for calling copy number gains/losses of 2.3/1.7. Subsequently we applied the Wilcoxon signed-rank test in order to find regions showing copy number imbalance that differ between the paired nodes and tumors correcting for multiple comparisons by performing permutation-based estimation of the false discovery rate permuting the samples 100 times. Results: Using 40 ng of total DNA from paraffin embedded tumor from primary and tumor in positive nodes, we obtained high quality, genome wide copy number data. Using FDR < 0.1, we identified four chromosomal segments that showed statistically significant increased likelihood of copy number gains in the primary tumor compared to the tumor-containing node. Thirty five percent of tumor-bearing lymph nodes were copy number normal at the EGFR locus whereas the corresponding primary tumor showed amplification at 7p11.2 (includes the EGFR gene). A similar pattern was observed for 8q24, 14q11.2, and 20q12-q13; regions associated with aggressive tumor behavior. Conclusions: Our results demonstrate four significant differences between the primary tumor and lymph node metastasis and in all cases the metastasis were copy number normal compared to the copy number gain observed in the primary tumor. These results support the importance to examine differences at the genome level between the metastatic tumor site and the primary.
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CANCÈS, ERIC, BENJAMIN JOURDAIN, and TONY LELIÈVRE. "QUANTUM MONTE CARLO SIMULATIONS OF FERMIONS: A MATHEMATICAL ANALYSIS OF THE FIXED-NODE APPROXIMATION." Mathematical Models and Methods in Applied Sciences 16, no. 09 (September 2006): 1403–40. http://dx.doi.org/10.1142/s0218202506001583.
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The Diffusion Monte Carlo (DMC) method is a powerful strategy to estimate the ground state energy E0 of an N-body Schrödinger Hamiltonian H = -½Δ + V with high accuracy. It consists of writing E0 as the long-time limit of an expectation value of a drift-diffusion process with a source term, and numerically simulating this process by means of a collection of random walkers. As for a number of stochastic methods, a DMC calculation makes use of an importance sampling function ψI which hopefully approximates some ground state ψ0 of H. In the fermionic case, it has been observed that the DMC method is biased, except in the special case when the nodal surfaces of ψI coincide with those of a ground state of H. The approximation due to the fact that, in practice, the nodal surfaces of ψI differ from those of the ground states of H, is referred to as the Fixed Node Approximation (FNA). Our purpose in this paper is to provide a mathematical analysis of the FNA. We prove that, under convenient hypotheses, a DMC calculation performed with the importance sampling function ψI, provides an estimation of the infimum of the energy 〈ψ, Hψ〉 on the set of the fermionic test functions ψ that exactly vanish on the nodal surfaces of ψI.
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O’Reilly, Joseph E., and Philip C. J. Donoghue. "The Effect of Fossil Sampling on the Estimation of Divergence Times with the Fossilized Birth–Death Process." Systematic Biology 69, no. 1 (May 25, 2019): 124–38. http://dx.doi.org/10.1093/sysbio/syz037.
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Abstract Timescales are of fundamental importance to evolutionary biology as they facilitate hypothesis tests of historical evolutionary processes. Through the incorporation of fossil occurrence data, the fossilized birth–death (FBD) process provides a framework for estimating divergence times using more paleontological data than traditional node calibration approaches have allowed. The inclusion of more data can refine evolutionary timescale estimates, but for many taxonomic groups it is computationally infeasible to include all available fossil occurrence data. Here, we utilize both empirical data and a simulation framework to identify approaches to subsampling fossil occurrence data that result in the most accurate estimates of divergence times. To achieve this we assess the performance of the FBD-Skyline model when implementing multiple approaches to incorporating subsampled fossil occurrence data. Our results demonstrate that it is necessary to account for all available fossil occurrence data to achieve the most accurate estimates of clade age. We show that this can be achieved if an empirical Bayes approach, accounting for fossil sampling through time, is applied to the FBD process. Random subsampling of occurrence data can lead to estimates of clade age that are incompatible with fossil evidence if no control over the affinities of fossil occurrences is enforced. Our results call into question the accuracy of previous divergence time studies incorporating the FBD process that have used only a subsample of all available fossil occurrence data.
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Kaushik, Shivkant, Ramesh Chandra Poonia, Sunil Kumar Khatri, Debabrata Samanta, and Partha Chakraborty. "Transmit Range Adjustment Using Artificial Intelligence for Enhancement of Location Privacy and Data Security in Service Location Protocol of VANET." Wireless Communications and Mobile Computing 2022 (September 16, 2022): 1–13. http://dx.doi.org/10.1155/2022/9642774.
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IoT or the internet of things is the talk of the town topic being researched in the field of information technology for more than decade. It is being in deployment stage in various developing economics, to enable driverless automobiles in the field of VANET. It helps in preventing crashes and provides urgent medical assistance in emergency case. Data security and location privacy are becoming of most importance in present IT scenario. Unauthorized access to location information of vehicles may pose a significant security threat. So, it is necessary to secure the location information of the vehicle. The proposed work aims at enhancement of location privacy data security in service location protocol of VANET’S. The primary techniques to be employed include artificial intelligence-based RF range approximation for transmission range adjustment and receive RF strength based distance estimation for trusted node location perimeters approximation, dynamic adjustment of silence period of OBU (on based unit) in conjunction with radio/RF interrupt. The unauthorized access to location information of vehicles and need of its privacy is the motivation for this work.
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Li, Jinlin, Tianjun Jing, Jiangbo Wang, Kun Wang, and Lei Wang. "Study on the Limit Penetration Level Evaluation Method of Distributed Photovoltaics Based on Large Sample Generation-Load Data." Energies 12, no. 18 (September 16, 2019): 3544. http://dx.doi.org/10.3390/en12183544.
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The three-step rule of distributed photovoltaic (DPVs) connecting to a distribution network in the planning of practical photovoltaic projects is modeled in this paper. On this basis, a method based on large sample historical generation-load data is proposed to comprehensively evaluate the DPV limit penetration level of the low voltage–medium voltage (LV-MV) distribution network, which is the premise of DPV connection planning. Considering the fluctuations of generation-load data in time and space, the DPV limit penetration level of the LV network is evaluated based on kernel density estimation. On this basis, considering the uncertainties of DPVs connecting node schemes and connection capacity, the limit penetration level of DPVs continuously connecting to the MV network is evaluated based on the dichotomy method and stochastic simulation. Finally, the feasibility of evaluating the DPV limit penetration level by the proposed method is verified based on an example of a real distribution network, which is of great importance for the planning of a distribution network with high DPV permeability to continuously connect to DPVs.
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Liu, Ming, Yan Zhou, and Lin Sun. "Risk Prediction of Gasifier System Based on Dynamic Cloud Bayesian Network." Journal of Physics: Conference Series 2381, no. 1 (December 1, 2022): 012103. http://dx.doi.org/10.1088/1742-6596/2381/1/012103.
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Abstract To address the current problem of insufficient risk level analysis of gasifier systems, an evaluation method combining the cloud model and dynamic Bayesian network is proposed, taking the gasifier system as the evaluation target, using the cloud model to discretize continuous data, and setting each risk factor in the evaluation system as a node in the dynamic Bayesian network to build a dynamic Bayesian network. The entropy weight method is used to calculate the weight of each risk indicator, the maximum likelihood estimation method is used to process the affiliation degree obtained from the cloud model, and the probability obtained by the affiliation-probability conversion method is input into the dynamic Bayesian network as evidence. Finally, the risk prediction assessment for the gasifier system is completed by using the features of forwarding and backward inference of the dynamic Bayesian network, combined with the comprehensive analysis of importance. The study shows that human maintenance efficiency, equipment integrity, gasifier pressure, and oxygen-coal ratio are the weak points that need to be focused on in the operation of the system.
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Bueti, Domenica, Vincent Walsh, Chris Frith, and Geraint Rees. "Different Brain Circuits Underlie Motor and Perceptual Representations of Temporal Intervals." Journal of Cognitive Neuroscience 20, no. 2 (February 2008): 204–14. http://dx.doi.org/10.1162/jocn.2008.20017.
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In everyday life, temporal information is used for both perception and action, but whether these two functions reflect the operation of similar or different neural circuits is unclear. We used functional magnetic resonance imaging to investigate the neural correlates of processing temporal information when either a motor or a perceptual representation is used. Participants viewed two identical sequences of visual stimuli and used the information differently to perform either a temporal reproduction or a temporal estimation task. By comparing brain activity evoked by these tasks and control conditions, we explored commonalities and differences in brain areas involved in reproduction and estimation of temporal intervals. The basal ganglia and the cerebellum were commonly active in both temporal tasks, consistent with suggestions that perception and production of time are subserved by the same mechanisms. However, only in the reproduction task was activity observed in a wider cortical network including the right pre-SMA, left middle frontal gyrus, left premotor cortex, with a more reliable activity in the right inferior parietal cortex, left fusiform gyrus, and the right extrastriate visual area V5/MT. Our findings point to a role for the parietal cortex as an interface between sensory and motor processes and suggest that it may be a key node in translation of temporal information into action. Furthermore, we discuss the potential importance of the extrastriate cortex in processing visual time in the context of recent findings.
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Xiong, Zhengqiang, Tao Sun, Zhengxing Wang, Yuhao Wu, Jie Yin, and Chaoqun Duan. "A Novel Efficient Passive Spatial Orientation Detection Method of UMT Enabled by ISB." Shock and Vibration 2020 (September 28, 2020): 1–9. http://dx.doi.org/10.1155/2020/8837071.
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The passive detection and direction-of-arrival (DOA) estimation problem is of great importance in many underwater applications such as target reconnaissance and data collection. In this paper, an Efficient Correlation-based Orientation Detection (ECOD) method is proposed to achieve high efficiency. Without high computational complexity in any Transform Domain, the time consumption of ECOD is largely reduced, which is especially critical for underwater intrusion detection, territorial waters protection, and many other real-time underwater applications. To achieve good invisibility, we design an intelligent submerged buoy (ISB) structure, which consists of six embedded hydrophones and an in situ electronic control unit (IECU). As a supplement to solutions against complex underwater environments, a hybrid ECOD method is also developed by involving the cooperation from underwater distributed sensor networks. To be specific, when high SNR signals are not recorded by a single ISB node, other distributed sensors are scheduled to assist in cooperative sensing. Simulation experiments demonstrate the efficiency of the ECOD method in passive 3D spatial orientation of underwater acoustic target and show that the ECOD method has a better performance in time consumption compared with general DOA algorithms.
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Zhou, Chenyan, Jianing Zhang, Yahong Zhang, and Jie Chen. "Research on fatigue crack propagation life prediction method for subsea pipelines." Journal of Physics: Conference Series 2390, no. 1 (December 1, 2022): 012045. http://dx.doi.org/10.1088/1742-6596/2390/1/012045.
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Abstract Subsea pipelines are subject to complex loading environments, and fatigue damage is one of the main failure modes. Due to manufacturing or environmental factors, crack defects are inevitable in submarine pipelines. For subsea pipelines in service, it is of practical importance to predict the residual fatigue life. On the premise of the conservative estimation method, the MTS criterion is used to analyze the crack propagation mode of subsea pipelines. In the numerical prediction method, the crack stress intensity factor is solved by the finite element method combined with the 1/4 node displacement method, and then the fatigue life of the subsea pipeline is predicted by the da/dN method based on the Paris formula. The results show that when the crack size increment Δa is set reasonably, the predicted results of crack propagation life of subsea pipeline are close to the experiment results, which verifies the accuracy of the numerical prediction method. The choice of the crack size increment has a large impact on the life prediction and needs to be considered in terms of both calculation accuracy and time consumption. The results obtained provide a reference for the safety assessment of pipelines in service.
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Cai, Hui, Junli Zhang, Jingqiu Yu, and Zheren Zhang. "Fault Current and Voltage Estimation for Pole-to-Pole Faults in Modular Multilevel Converter Based DC Grids Considering AC Active Power." Applied Sciences 11, no. 6 (March 23, 2021): 2882. http://dx.doi.org/10.3390/app11062882.
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DC short-circuit faults are one of the challenges for modular multilevel converter (MMC) based DC grid. It is vital for proper design of protection system to estimate the fault currents and voltages. The existing calculation methods based on RLC equivalent model of MMC have enough accuracy in estimating the branch currents but suffer from poor accuracy in estimating the node voltages. To better reflect the dynamics of MMC control during the fault, MMC is equivalent to a RLC series circuit in parallel with a variable controlled current source. This model not only considers the discharge of sub-module capacitors but also the AC active power and MMC control. Then, based on the discrete adjoint model of the equivalent MMC model and the RL series equivalent model of DC lines, the fault voltages and currents for the pre-fault and faulted DC grids could be easily obtained. From the aspect of power balance, the importance of AC active power on estimating the fault currents and voltages is discussed then. At last, based on the Zhangbei bipolar DC grid, comparisons are conducted between the simulations on PSCAD, the numerical calculation under the proposed method and the existing methods. The results show that the proposed method and the existing methods are both able to accurately estimate the fault currents within a relative error of 1%. However, compared with the error of the existing methods in calculating the fault voltages, the relative error for the proposed method is limited to less than 5% for the whole DC gird.
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Milica Lekic, Gordana Gardasevic, and Milan Mladen. "Experimental evaluation of multi-PHY 6TiSCH networks." ITU Journal on Future and Evolving Technologies 3, no. 2 (September 30, 2022): 470–82. http://dx.doi.org/10.52953/cghe6909.
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The architectural design of Wireless Sensor Networks (WSNs) for the Industrial Internet of Things (IIoT) applications requires the careful planning and selection of an appropriate operational strategy. Harmonization of standards is crucial to ensure easier certification and commercialization of IIoT solutions. The ongoing research activities are directed toward designing agile, reliable, and secure transmission technologies and protocols. Recently, Time Slotted Channel Hopping (TSCH) standardization bodies have started to consider support for multiple physical layers thus accommodating a wide range of applications. This paper presents the results of the extensive experimental measurement campaign to study the performance of the 6TiSCH (IPv6 over the TSCH mode of IEEE 802.15.4e) network while supporting multiple physical layers (PHYs). For measurement purposes, all experiments were performed on OpenMote-B hardware. These devices are equipped with an Atmel AT86RF215 dual radio transceiver implementing IEEE 802.15.4g. The performance evaluation is provided for the following metrics: network formation time, Packet Delivery Ratio (PDR), latency, and duty cycle. Results are encouraging, particularly in terms of high PDR for all tested PHYs. Performance evaluation indicates the importance of proper node positioning, link quality estimation and careful selection of network parameters. Moreover, collected experimental results create a dataset that provides insights into the tested PHYs' performance and their potential for indoor 6TiSCH networking.
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Stroeven, Piet, Nghi L. B. Le, Lambertus J. Sluys, and Huan He. "POROSIMETRY BY DOUBLE-RANDOM MULTIPLE TREE STRUCTURING IN VIRTUAL CONCRETE." Image Analysis & Stereology 31, no. 1 (March 15, 2012): 55. http://dx.doi.org/10.5566/ias.v31.p55-63.
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Two different porosimetry methods are presented in two successive papers. Inspiration for the development came from the rapidly-exploring random tree (RRT) approach used in robotics. The novel methods are applied to virtual cementitious materials produced by a modern concurrent algorithm-based discrete element modeling system, HADES. This would render possible realistically simulating all aspects of particulate matter that influence structure-sensitive features of the pore network structure in maturing concrete, namely size, shape and dispersion of aggregate and cement particles. Pore space is a complex tortuous entity. Practical methods conventionally applied for assessment of pore size distribution may fail or present biased information. Among them, mercury intrusion porosimetry and 2D quantitative image analysis are popular. The mathematical morphology operator “opening” can be applied to sections and even provide 3D information on pore size distribution, provided isotropy is guaranteed. Unfortunately, aggregate grain surfaces lead to pore anisotropy. The presented methods allow exploration of pore space in the virtual material, after which pore size distribution is derived from star volume measurements. In addition to size of pores their continuity is of crucial importance for durability estimation. Double-random multiple tree structuring (DRaMuTS), presented herein, and random node structuring (RaNoS) provide such information. The latter method will be introduced in a next issue of IA&S.
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Ding, Rui. "The Complex Network Theory-Based Urban Land-Use and Transport Interaction Studies." Complexity 2019 (June 17, 2019): 1–14. http://dx.doi.org/10.1155/2019/4180890.
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The research on complex networks offers novel insight into the analysis of complex urban systems. The objective of this article is to provide a review of complex network theory in urban land-use and transport studies to date. Some traditional integrated studies of urban land-use and traffic networks are summarized and analysed; related research gaps were proposed. Then, this paper reviewed the application of complex network theory in urban land-use and transport research and practice. It shows that the node importance identification method is critical for network protection or attack studies; the multiple centrality assessment and kernel density estimation approaches can be used to represent the intuitionistic connections of urban traffic networks and surrounding land-uses; it can be used to verify the changing trend and variation of landscape connectivity; also it can be applied to the identification of key changed land-use types in land-use cover change; the coevolution process can be treated as an integrated way to discuss the relationships between urban traffic network growth and land-use change, and the multilayer networks based analysis is a novel method to measure their interactions. This paper is essential in establishing apparent research interests and points out the further potential application of complex network theory in urban traffic network and land-use related studies.
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Ford, Shannon, Jacqueline Vaughn, Arvind Subramaniam, Abhinav Gundala, and Nirmish Shah. "Symptom Correlates Using Network Analysis in Pediatric Patients Undergoing Blood and Marrow Transplant." Blood 138, Supplement 1 (November 5, 2021): 4978. http://dx.doi.org/10.1182/blood-2021-152069.
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Abstract Introduction: Youth undergoing blood and marrow transplantation (BMT) experience significant distress. The widespread and mainstream use of mHealth technologies such as smartphone applications offer a unique opportunity to collect patient-generated health data that can enhance patients' and clinicians' understanding of symptom onset, trajectories, and inter-relationships. Network analysis (NA) is a useful tool that can illuminate inter-relationships between symptoms, leading to better collective understanding of the symptom experiences of these youths. This knowledge can lead to enhanced patient-caregiver interactions/collaborations, treatment management, and potentially support improved inference around adverse clinical outcomes. Objective: To determine the feasibility of using network analysis to evaluate mHealth symptom data in patients undergoing BMT. Aim 1. Estimate the network by creating a graphic model that depicts symptom inter-relationships. Aim 2. Identify influential symptoms in the network by evaluating centrality indices and assessing the stability of edges and centrality results. Methods : Study participants undergoing BMT recorded daily symptoms via a smartphone app from preconditioning through 120 days. Patients report their symptom experience (intensity and distress on a scale of 0-10). NA was conducted on the initial patients (n=3) to evaluate inter-relationships between reported symptoms. Each symptom is represented by a circle (node), while associations (regularized partial correlations coefficients) between symptoms are depicted as lines (edges). Stronger associations among symptoms present as thicker lines in the network and a higher value in the weighted matrix table. Centrality indices identify and quantify symptoms that exert more influence in the network. These symptoms are influential in the network due to their strength (sum of absolute values of its connections with other nodes), betweenness (number of times a node lies on the shortest path between two other nodes), or closeness (the summed average distance of a node to all other nodes). Other centrality measures also exist. Centrality tests aimed to evaluate symptoms for their reported importance to the youth and association of those symptoms with other reported symptoms. The more "central" a symptom, the higher the potential to transmit effects to and from other symptoms in the network. This can make them important foci for intervention. Stability testing was used to assess the network's accuracy. Results/Discussion: Descriptive statistics are summarized in Table 1. The estimated network (Fig. 1) provided details on the eight most often reported symptoms; nausea, tired (intensity and distress), vomiting, pain, mouth pain, and sore throat (intensity). The network shows strong mutual associations (regularized partial correlations) between the intensity and distress of nausea (.596) and being tired (.722). There was also a strong relationship between mouth pain and sore throat (.791). A less strong relationship was noted between nausea intensity and tired intensity (.145), and tired intensity and pain intensity (.187). A slight negative relationship was noted between vomiting intensity and pain intensity (-.086). The centrality indices (Fig. 2) revealed vomiting intensity (-1.917) as the strongest symptom with the highest closeness (-1.715). The symptom with the highest betweenness centrality was equal for both nausea intensity and tired intensity at 1.286. To assess confidence in the network estimation we replicated this test 1000 times (non-parametric bootstrapping, n=1000) on the edge stability and centrality results (Fig. 3). Results indicate areas with wide confidence intervals (instability) especially in the edge between vomiting intensity and mouth pain. Conclusion: It is feasible to use mHealth data from youth who experience symptom distress during BMT. However, efforts to obtain more data is necessary if we hope to make accurate inferences from the data. Future work will focus on enriching data collection, examining clinically important sign and symptom patterns and interrelationships, and to explore feasibility of using mHealth data for individualized/precision care and possible predictive uses. Figure 1 Figure 1. Disclosures Shah: Novartis: Research Funding, Speakers Bureau; GBT: Consultancy, Research Funding, Speakers Bureau; CSL Behring: Consultancy; Guidepoint Global: Consultancy; Alexion: Speakers Bureau; Bluebird Bio: Consultancy; Emmaus: Consultancy; GLG: Consultancy.
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Šarler, Božidar, Tadej Dobravec, Gašper Glavan, Vanja Hatić, Boštjan Mavrič, Robert Vertnik, Peter Cvahte, Filip Gregor, Marina Jelen, and Marko Petrovič. "Multi-Physics and Multi-Scale Meshless Simulation System for Direct-Chill Casting of Aluminium Alloys." Strojniški vestnik – Journal of Mechanical Engineering 65, no. 11-12 (November 18, 2019): 658–70. http://dx.doi.org/10.5545/sv-jme.2019.6350.
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This paper represents an overview of the elements of the user-friendly simulation system, developed for computational analysis and optimization of the quality and productivity of the electromagnetically direct-chill cast semi-products from aluminium alloys. The system also allows the computational estimation of the design changes of the casting equipment. To achieve this goal, the electromagnetic and the thermofluid process parameters are coupled to the evolution of Lorentz force, temperature, velocity, concentration, strain and stress fields as well as microstructure evolution. This forms a multi-physics and multi-scale problem of great complexity, which has not been demonstrated before. The macroscopic fluid mechanics, solid mechanics, and electromagnetic solution framework is based on local strong-form meshless formulation, involving the radial basis functions and monomials as trial functions, and local collocation or weighted least squares approximation. It is coupled to the micro-scale by incorporating the point automata solution concept. The entire macro-micro solution concept does not require meshing and space integration. The solution procedure can be easily and efficiently automatically adapted in node redistribution and/or refinement sense, which is of utmost importance when coping with fields exhibiting sharp gradients, which occur in the phase-change problems. The simulation system is coded from scratch in modern Fortran. The elements of the experimental validation of the system and the demonstration of its use for round billet casting in IMPOL Aluminium Industry are shown.
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Liu, Kai Chun, Chung Tse Liu, Chao Wei Chen, Chih Ching Lin, and Chia Tai Chan. "Accelerometry-Based Motion Pattern Analysis for Physical Activity Recognition and Activity Level Assessment." Applied Mechanics and Materials 479-480 (December 2013): 818–22. http://dx.doi.org/10.4028/www.scientific.net/amm.479-480.818.
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Physical inactivity is becoming a major public health concern and lead to a variety of chronic diseases. Since adequate moderate or vigorous activity can reduce the incidence of chronic diseases, noncommunicable disease and obesity. The evidence is supporting the importance of physical activity on health and well-being. However, many people nowadays live without adequate physical activity, and do not aware whether their daily activity is enough or not. The activity recognition and activity level can be used to survey the effectiveness and achievement of goals aimed at increasing physical activity. Physical activity monitoring has become a more proactive healthcare service that should build on the real-time reminding offered by healthcare solutions. Therefore, physical activity monitoring and activity level assessment are critical to maintain adequate physical activity and improve health. In this work, we present a motion patterns analysis for physical activity recognition and activity level assessment by using a wearable sensor. The proposed mechanism uses triaxial accelerometer as a sensing device. The sensor node is mounted in the right front waist, sensing and transmitting sensing data to server. The time series of raw data will be preprocessed through the aggregation technique of jumping window. The raw data will be divided into small segments and separated to gravity signal and body acceleration by filter. Through feature extraction and proposed classifier, motion pattern analysis is achieved. The classifier consists of activity recognition and activity level assessment algorithms. The results have demonstrated that the proposed methods can achieve 94.7%, 87.0% accuracy of activity recognition and activity level estimation respectively.
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Hossain, Ferdous Al, Md Rokonuzzaman, Nowshad Amin, Jianmin Zhang, Mahmuda Khatun Mishu, Wen-Shan Tan, Md Rabiul Islam, and Rajib Baran Roy. "Probabilistic Load Flow–Based Optimal Placement and Sizing of Distributed Generators." Energies 14, no. 23 (November 23, 2021): 7857. http://dx.doi.org/10.3390/en14237857.
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Distributed generation (DG) is gaining importance as electrical energy demand increases. DG is used to decrease power losses, operating costs, and improve voltage stability. Most DG resources have less environmental impact. In a particular region, the sizing and location of DG resources significantly affect the planned DG integrated distribution network (DN). The voltage profiles of the DN will change or even become excessively increased. An enormous DG active power, inserted into an improper node of the distribution network, may bring a larger current greater than the conductor’s maximum value, resulting in an overcurrent distribution network. Therefore, DG sizing and DG location optimization is required for a systematic DG operation to fully exploit distributed energy and achieve mutual energy harmony across existing distribution networks, which creates an economically viable, secure, stable, and dependable power distribution system. DG needs to access the location and capacity for rational planning. The objective function of this paper is to minimize the sum of investment cost, operation cost, and line loss cost utilizing DG access. The probabilistic power flow calculation technique based on the two-point estimation method is chosen for this paper’s load flow computation. The location and size of the DG distribution network are determined using a genetic algorithm in a MATLAB environment. For the optimum solution, the actual power load is estimated using historical data. The proposed system is based on the China distribution system, and the currency is used in Yuan. After DG access, active and reactive power losses are reduced by 53% and 26%, respectively. The line operating cost and the total annual cost are decreased by 53.7% and 12%, respectively.
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Wang, Heyong, Carl K. Chang, Hen-I. Yang, and Yanping Chen. "Estimating the Relative Importance of Nodes in Social Networks." Journal of Information Processing 21, no. 3 (2013): 414–22. http://dx.doi.org/10.2197/ipsjjip.21.414.
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Bhat, Soumya J., and K. V. Santhosh. "Is Localization of Wireless Sensor Networks in Irregular Fields a Challenge?" Wireless Personal Communications 114, no. 3 (May 23, 2020): 2017–42. http://dx.doi.org/10.1007/s11277-020-07460-6.
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Abstract Wireless sensor networks have been considered as an emerging technology for numerous applications of cyber-physical systems. These applications often require the deployment of sensor nodes in various anisotropic fields. Localization in anisotropic fields is a challenge because of the factors such as non-line of sight communications, irregularities of terrains, and network holes. Traditional localization techniques, when applied to anisotropic or irregular fields, result in colossal location estimation errors. To improve location estimations, this paper presents a comparative analysis of available localization techniques based on taxonomy framework. A detailed discussion on the importance of localization of sensor nodes in irregular fields from the reported real-life applications is presented along with challenges faced by existing localization techniques. Further, taxonomy based on techniques adopted by localization methods to address the effects of irregular fields on location estimations is reported. Finally, using the designed taxonomy framework, a comparative analysis of different localization techniques addressing irregularities and the directions towards the development of an optimal localization technique is addressed.
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Rossi, R. A., L. K. McDowell, D. W. Aha, and J. Neville. "Transforming Graph Data for Statistical Relational Learning." Journal of Artificial Intelligence Research 45 (October 30, 2012): 363–441. http://dx.doi.org/10.1613/jair.3659.
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Relational data representations have become an increasingly important topic due to the recent proliferation of network datasets (e.g., social, biological, information networks) and a corresponding increase in the application of Statistical Relational Learning (SRL) algorithms to these domains. In this article, we examine and categorize techniques for transforming graph-based relational data to improve SRL algorithms. In particular, appropriate transformations of the nodes, links, and/or features of the data can dramatically affect the capabilities and results of SRL algorithms. We introduce an intuitive taxonomy for data representation transformations in relational domains that incorporates link transformation and node transformation as symmetric representation tasks. More specifically, the transformation tasks for both nodes and links include (i) predicting their existence, (ii) predicting their label or type, (iii) estimating their weight or importance, and (iv) system- atically constructing their relevant features. We motivate our taxonomy through detailed examples and use it to survey competing approaches for each of these tasks. We also dis- cuss general conditions for transforming links, nodes, and features. Finally, we highlight challenges that remain to be addressed.
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Buijsrogge, Anne, Pieter-Tjerk de Boer, and Werner R. W. Scheinhardt. "ON STATE-INDEPENDENT IMPORTANCE SAMPLING FOR THE GI|GI|1 TANDEM QUEUE1." Probability in the Engineering and Informational Sciences 34, no. 1 (November 5, 2018): 131–56. http://dx.doi.org/10.1017/s0269964818000426.
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In this paper, we consider a d-node GI|GI|1 tandem queue with i.i.d. inter-arrival process and service processes that are independent of each other. Our main interest is to estimate the probability to reach a high level N in a busy cycle of the system using simulation. As crude simulation does not give a sufficient precision in reasonable time, we use importance sampling. We introduce a method to find a state-independent change of measure and we show that this is equivalent to a change of measure that was earlier, but implicitly, described by Parekh and Walrand [8]. We also show that this change of measure is the only exponential state-independent change of measure that may result in an asymptotically efficient estimator. Lastly, we provide necessary conditions for this state-independent change of measure to give an asymptotically efficient estimator.
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Khalaf-Allah, Mohamed. "Particle Filtering for Three-Dimensional TDoA-Based Positioning Using Four Anchor Nodes." Sensors 20, no. 16 (August 12, 2020): 4516. http://dx.doi.org/10.3390/s20164516.
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In this article, the four-anchor time difference of arrival (TDoA)-based three-dimensional (3D) positioning by particle filtering is addressed. The implemented particle filter uses 1000 particles to represent the probability density function (pdf) of interest, i.e., the posterior pdf of the target node’s state (position). A resampling procedure is used to generate particles in the prediction step, and TDoA measurements are used to determine the importance, i.e., weight, of each particle to enable updating the posterior pdf and estimating the position of the target node. The simulation results show the feasibility of this approach and the possibility to employ it in indoor positioning applications under the assumed working conditions using, e.g., the ultra-wideband (UWB) wireless technology. Therefore, it is possible to enable unmanned air vehicle (UAV) positioning applications, e.g., inventory management in large warehouses, without the need for an excessive number of anchor nodes.
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Barbagallo, F., M. Bosco, A. Ghersi, E. M. Marino, and P. P. Rossi. "Seismic Assessment of Steel MRFs by Cyclic Pushover Analysis." Open Construction and Building Technology Journal 13, no. 1 (January 31, 2019): 12–26. http://dx.doi.org/10.2174/18748368019130012.
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Background:Structural members subjected to strong earthquakes undergo stiffness and strength degradation. To predict accurately the seismic behaviour of structures, nonlinear static methods of analysis have been developed in scientific literature. Generally, nonlinear static methods perform the pushover analysis by applying a monotonic lateral load. However, every earthquake input is characterized by several repeated loads with reverse in signs and the strength and deformation capacities of structures are generally related to the cumulative damage. This aspect is neglected by the conventional monotonic approaches, which tend to overestimate the strength and stiffness of structural members.Objective:This paper aims to investigate the possibility that the Cyclic Pushover Analysis (CPA) may be used as a tool to assess the seismic behaviour of structures. During the CPA, the structure is subjected to a distribution of horizontal forces that is reversed in sign when predefined peak displacements of the reference node are attained. This process repeats in cycles previously determined in a loading protocol.Methods:To investigate the effectiveness of the CPA in predicting the structural response, a steel moment resisting frame is designed as a case study building. A numerical model of this frame is developed in OpenSees. To examine the influence of the loading protocols on the seismic response, the CPA is run following the ATC-24 and the SAC protocols. Additionally, the seismic demand of the case study frame is determined by a Monotonic Pushover Analysis (MPA) and by Incremental nonlinear Dynamic Analysis (IDA).Results and Conclusions:The following results are obtained:• Despite the differences between the SAC and the ATC-24 loading protocols, the CPA applied according to those two protocols led to almost the same structural response of the case study frame.• The CPA showed the capability of catching the stiffness and strength degradation, which is otherwise neglected by the MPA. In fact, given a base shear or peak ground acceleration, the CPA leads to the estimation of larger displacement demands compared to the MPA.• During long (or medium) duration earthquakes, the CPA was necessary to estimate accurately the response of the structure. In fact, at a PGA equal to 1 g, the CPA estimated the top displacement demand with an error lower than 10%, while the MPA underestimated it by 18%.• The importance of considering the cyclic deterioration is shown at local level by the damage indexes of the frame. In the case of long earthquakes, given a top displacement of 600 mm (corresponding to a PGA equal to 1 g), the CPA estimated the damage indexes with an error equal to 12%.
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Yang, Xiong, Wang, and Zhang. "Analysis of Byzantine Attacks for Target Tracking in Wireless Sensor Networks." Sensors 19, no. 15 (August 5, 2019): 3436. http://dx.doi.org/10.3390/s19153436.
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Herein, the problem of target tracking in wireless sensor networks (WSNs) is investigated in the presence of Byzantine attacks. More specifically, we analyze the impact of Byzantine attacks on the performance of a tracking system. First, under the condition of jointly estimating the target state and the attack parameters, the posterior Cramer–Rao lower bound (PCRLB) is calculated. Then, from the perspective of attackers, we define the optimal Byzantine attack and theoretically find a way to achieve such an attack with minimal cost. When the attacked nodes are correctly identified by the fusion center (FC), we further define the suboptimal Byzantine attack and also find a way to realize such an attack. Finally, in order to alleviate the negative impact of attackers on the system performance, a modified sampling importance resampling (SIR) filter is proposed. Simulation results show that the tracking results of the modified SIR filter can be close to the true trajectory of the moving target. In addition, when the quantization level increases, both the security performance and the estimation performance of the tracking system are improved.
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Ibusuki, M., Y. Yamamoto, T. Kawasoe, K. Kai, S. Shiraishi, S. Tomiguchi, and H. Iwase. "Potential advantage of studying preoperative sentinel node mapping with three-dimensional images by a hybrid single photon emission CT (SPECT)/CT system for breast cancer." Journal of Clinical Oncology 25, no. 18_suppl (June 20, 2007): 601. http://dx.doi.org/10.1200/jco.2007.25.18_suppl.601.
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601 Background: Lymph node status is one of the key factors in determining the stage, appropriate therapy and outcome in patients with breast cancer. Accurate identification of sentinel nodes (SNs) has clinical importance for each patients before surgery. The purpose of this study was to assess the role of Single-photon emission computed tomography (SPECT)/CT lymphoscintigraphy in SN identification for patients with breast cancer, and to analyze the impact of such information on estimating metastases to SNs. Methods: Two hundred and twenty-three clinically node-negative patients were underwent SN biopsy between July 2002 and November 2006. CT and SPECT images were obtained after injection of subcutaneal 1mCi (99m)Tc-nanocolloid, allowing identification of SN. Target and non-target structures, including lymph nodes identified by SPECT, were drawn by SPECT/CT combined system, which was comprised of a two-detector SPECT system and a multiple-detector CT at the same platform. We compared the anatomical location of SNs demonstrated on the 3D SPECT/CT images and correlation to SN positivity. Results: SPECT/CT uptake was detected in 221 cases (99.1%). 3D SPECT/CT images visualized accurate localization of SNs in each cases. Total number of biopsied SNs were 315 , and the most frequent locations of SN were trapezoid area in the upper side of axilla. We defined this area as ‘Pectoral area (PA)’. In SN negative (SN-) patients, 228 (98.3%) SNs were found in PA, and 4 (1.7%) SNs were out of this area such as parasternal area. In SN positive (SN+) patients, 65(78.3%) SNs were in the PA, and 18(21.7%)SNs were out of PA ,respectively. Significant differences (p<0.01 ,chi-square test) were found in SNs distribution whether in or out of PA between SN+ and SN- patients. Conclusions: SN biopsy navigated by 3D-SPECT/CT can clarify the preoperative anatomical localization of SNs in patients with breast cancer. Atypical distribution of SNs out of PA may suggest SN positivity as a reflection of the failure of lymphatic drainage systems. No significant financial relationships to disclose.
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Kamola, Mariusz. "Sensitivity of Importance Metrics for Critical Digital Services Graph to Service Operators’ Self-Assessment Errors." Security and Communication Networks 2019 (September 23, 2019): 1–8. http://dx.doi.org/10.1155/2019/7510809.
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Interdependency of critical digital services can be modeled in the form of a graph with exactly known structure but with edge weights subject to estimation errors. We use standard and custom centrality indexes to measure each service vulnerability. Vulnerability of all nodes in the graph gets aggregated in a number of ways into a single network vulnerability index for services whose operation is critical for the state. This study compares sensitivity of various centralities combined with various aggregation methods to errors in edge weights reported by service operators. We find that many of those combinations are quite robust and can be used interchangeably to reflect various perceptions of network vulnerability. We use graphs of source files’ dependencies for a number of open-source projects, as a good analogy for real critical services graph, which will remain confidential.
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Khan, Inam Ullah, Ryan Alturki, Hasan J. Alyamani, Mohammed Abdulaziz Ikram, Muhammad Adnan Aziz, Vinh Truong Hoang, and Tanweer Ahmad Cheema. "RSSI-Controlled Long-Range Communication in Secured IoT-Enabled Unmanned Aerial Vehicles." Mobile Information Systems 2021 (March 1, 2021): 1–11. http://dx.doi.org/10.1155/2021/5523553.
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Unmanned aerial vehicle (UAV) has recently gained significant attention due to their efficient structures, cost-effectiveness, easy availability, and tendency to form an ad hoc wireless mobile network. IoT-enabled UAV is a new research domain that uses location tracking with the advancement of aerial technology. In this context, the importance of 3D aerial networks is attracting a lot of attention recently. It has various applications related to information processing, communication, and location-based services. Location identification of wireless nodes is a challenging job and of extreme importance. In this study, we introduced a novel technique for finding indoor and open-air three-dimensional (3D) areas of nodes by measuring the signal strength. The mathematical formulation is based on a path loss model and decision tree machine learning classifier. We constructed 2D and 3D models to gather more accurate information on the nodes. Simulation findings demonstrate that the proposed machine learning-based model excels in nodes location estimation, the actual and estimated distance of different nodes, and calculation of received signal strength in aerial ad hoc networks. In addition, the decision tree constructs an offline phase control in the flying vehicle’s location to enhance the time complexity along with experimental accuracy.
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Hijazi, Hussein, Nahi Kandil, Nour Zaarour, and Nadir Hakem. "Impact of Initialization on Gradient Descent Method in Localization Using Received Signal Strength." ITM Web of Conferences 27 (2019): 01003. http://dx.doi.org/10.1051/itmconf/20192701003.
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In this article we present a localization technique based on received signal strength (RSS) combined with the gradient descent optimization method. The goal of this article is to show the importance of gradient descent in localization domain over the trilateration technique, and that by reducing the number of needed anchor nodes. Furthermore, we demonstrate the effect of the initialization technique on the localization accuracy. Results have shown that the selection of the initialization type (4 types of initialization were tested) has an efficient impact on the accuracy of the target sensors location estimation.
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Wolf, Benjamin, Lars-Christian Horn, Michael Höckel, and Bahriye Aktas. "Tumor-stroma interaction in cervical cancer: The prognostic importance of desmoplasia." Journal of Clinical Oncology 40, no. 16_suppl (June 1, 2022): e17519-e17519. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.e17519.
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e17519 Background: During tumor growth, cancer cells can induce the formation of new extracellular matrix, mainly by activating peritumoral fibroblasts. This stromal reconfiguration has been termed desmoplasia. In pancreatic and ovarian cancer models, targeting desmoplasia therapeutically to normalize the microenvironment has recently shown promising results. We investigated the frequency and prognostic relevance of peritumoral desmoplasia, as well as its association with other prognostic factors such as lymph node involvement and parametrial tumor extension in cervical cancer patients. Methods: A retrospective cohort study based on data from the prospective monocentric observational Leipzig School Mesometrial Resection study was conducted. Cervical cancer patients staged IB1 to IVA according to the Fédération Internationale de Gynécologie et d’Obstétrique (FIGO) who underwent primary surgery between 1999 and 2017 were included. Information regarding desmoplastic tumor reaction was retrospectively retrieved from the pathology reports. All other data had been collected prospectively during the trial period. Using non-parametric tests, we calculated the association of peritumoral desmoplasia with other common risk factors. To determine the prognostic significance of desmoplasia, we used the Kaplan-Meier estimator and performed multivariable Cox-regression modelling. Results: Overall, 355 patients were included. Desmoplasia was present in 298 cases and was associated with a significantly higher likelihood of lymphovascular space involvement (odds ratio [OR] 2.7, 95% confidence interval [CI] 1.4 – 5.1, p = 0.001) and venous infiltration (OR 5.1, 95%-CI 1.3 – 44.9, p = 0.01). Lymph node metastasis was more common in patients with desmoplasia (OR 2.4, 95%-CI 1.2 – 5.0, p = 0.01), as was parametrial involvement (OR 3.5, 95%-CI 1.7 – 7.9, p = 0.0002). Interestingly, the presence of desmoplasia was not associated with larger tumor size. Patients with desmoplastic tissue reaction were significantly older than those without desmoplasia (median 41 years [inter quartile range 34 – 51] vs. 47 years [IQR 39-56], p = 0.009). These prognostically negative parameters in patients with desmoplastic disease translated into inferior overall (94.5% vs 80.5%, OR 3.9 [95%-CI 1.2 – 12.5], p = 0.02) and recurrence-free survival (86.8% vs. 74.2%, OR 2.3 [95%-CI 1.0 – 4.9], p = 0.04). A multivariable Cox-regression model including tumor size, patient age, and nodal status indicated that desmoplasia was an independent risk factor for overall death (OR 4.2, 95%-CI 1.03 – 17.5, p = 0.04). Conclusions: Desmoplastic stromal remodeling is associated with a more aggressive phenotype of cervical cancer and inferior survival. Targeting desmoplasia, especially in advanced disease when surgical treatment is not feasible, might be a promising treatment approach in the future.
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Khalaf-Allah, Mohamed. "Novel Solutions to the Three-Anchor ToA-Based Three-Dimensional Positioning Problem." Sensors 21, no. 21 (November 3, 2021): 7325. http://dx.doi.org/10.3390/s21217325.
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At least four non-coplanar anchor nodes (ANs) are required for the time-of-arrival (ToA)-based three-dimensional (3D) positioning to enable unique position estimation. Direct method (DM) and particle filter (PF) algorithms were developed to address the three-anchor ToA-based 3D positioning problem. The proposed DM reduces this problem to the solution of a quadratic equation, exploiting the knowledge about the workspace, to first estimate the x- or z-coordinate, and then the remaining two coordinates. The implemented PF uses 1000 particles to represent the posterior probability density function (PDF) of the AN’s 3D position. The prediction step generates new particles by a resampling procedure. The ToA measurements determine the importance of these particles to enable updating the posterior PDF and estimating the 3D position of the AN. Simulation results corroborate the viability of the developed DM and PF algorithms, in terms of accuracy and computational cost, in the pursuit and circumnavigation scenarios, and even with a horizontally coplanar arrangement of the three ANs. Therefore, it is possible to enable applications requiring real-time positioning, such as unmanned aerial vehicle (UAV) autonomous docking and circling a stationary (or moving) position, without the need for an excessive number of ANs.
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Clarke, Noel, Adnan Ali, Hitesh Mistry, and Alex Hoyle. "The importance of non-regional lymph nodes in assigning risk in primary metastatic prostate cancer." Journal of Clinical Oncology 36, no. 6_suppl (February 20, 2018): 227. http://dx.doi.org/10.1200/jco.2018.36.6_suppl.227.
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227 Background: Patients diagnosed with non-regional lymph nodes (NRLN) in isolation exhibit a more prolonged clinical course than those with bone or visceral metastases in trial data, but evaluation of survival data in general populations is sparse and their presence doesn’t feature in risk estimations based on tumour volume. Methods: The evaluation and prognostic relevance of NRLN metastasis presenting synchronously with osseous or non-ossesous metastasis in hormone-naive prostate cancer was evaluated using the Surveillance, Epidemiology and End-results (SEER) database. Patients with stage M1a-c PCa diagnosed between 2004 and 2009 were identified and included within the analysis. Kaplan Meier was used to estimate overall (OS) and cancer specific survival (CSS) rates in relation to metastatic distribution. Multivariate cox-regression models were used to identify predictors of OS and CSS. Results: Of 4869 metastatic PCa patients identified, osseous metastasis was the most common finding (65.1%); followed by non-osseous (17.5%), osseous + NRLN (7.8%), NRLN (4.9%), non-osseous + osseous (±NRLN) (2.9%) and non-osseous + NRLN (1.8%). Median follow-up was 93 mo. Median OS and CSS were 28 and 34 mo respectively. Patients with osseous + NRLN metastasis had a significantly worse median OS (30 mo vs 25 mo, p = 0.001) and CSS (37 mo vs 29 mo, p < 0.001) compared to osseous only metastasis. On multivariate cox regression, osseous + NRLN metastasis was an independent predictor of OS and CSS when compared to osseous only metastasis (both p-values < 0.01). Conclusions: NRLN metastasis in the presence of osseous metastasis represents a poor prognostic feature when compared to osseous metastasis alone. The current therapeutic stratification of “low vs high volume” disease does not account for this phenomenon and patients requiring aggressive therapy may not receive maximal therapeutic benefit as a consequence.
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Roycroft, Emily J., Adnan Moussalli, and Kevin C. Rowe. "Phylogenomics Uncovers Confidence and Conflict in the Rapid Radiation of Australo-Papuan Rodents." Systematic Biology 69, no. 3 (September 12, 2019): 431–44. http://dx.doi.org/10.1093/sysbio/syz044.
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Abstract The estimation of robust and accurate measures of branch support has proven challenging in the era of phylogenomics. In data sets of potentially millions of sites, bootstrap support for bifurcating relationships around very short internal branches can be inappropriately inflated. Such overestimation of branch support may be particularly problematic in rapid radiations, where phylogenetic signal is low and incomplete lineage sorting severe. Here, we explore this issue by comparing various branch support estimates under both concatenated and coalescent frameworks, in the recent radiation Australo-Papuan murine rodents (Muridae: Hydromyini). Using nucleotide sequence data from 1245 independent loci and several phylogenomic inference methods, we unequivocally resolve the majority of genus-level relationships within Hydromyini. However, at four nodes we recover inconsistency in branch support estimates both within and among concatenated and coalescent approaches. In most cases, concatenated likelihood approaches using standard fast bootstrap algorithms did not detect any uncertainty at these four nodes, regardless of partitioning strategy. However, we found this could be overcome with two-stage resampling, that is, across genes and sites within genes (using -bsam GENESITE in IQ-TREE). In addition, low confidence at recalcitrant nodes was recovered using UFBoot2, a recent revision to the bootstrap protocol in IQ-TREE, but this depended on partitioning strategy. Summary coalescent approaches also failed to detect uncertainty under some circumstances. For each of four recalcitrant nodes, an equivalent (or close to equivalent) number of genes were in strong support ($>$ 75% bootstrap) of both the primary and at least one alternative topological hypothesis, suggesting notable phylogenetic conflict among loci not detected using some standard branch support metrics. Recent debate has focused on the appropriateness of concatenated versus multigenealogical approaches to resolving species relationships, but less so on accurately estimating uncertainty in large data sets. Our results demonstrate the importance of employing multiple approaches when assessing confidence and highlight the need for greater attention to the development of robust measures of uncertainty in the era of phylogenomics.
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Puttick, Mark N. "Partially incorrect fossil data augment analyses of discrete trait evolution in living species." Biology Letters 12, no. 8 (August 2016): 20160392. http://dx.doi.org/10.1098/rsbl.2016.0392.
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Ancestral state reconstruction of discrete character traits is often vital when attempting to understand the origins and homology of traits in living species. The addition of fossils has been shown to alter our understanding of trait evolution in extant taxa, but researchers may avoid using fossils alongside extant species if only few are known, or if the designation of the trait of interest is uncertain. Here, I investigate the impacts of fossils and incorrectly coded fossils in the ancestral state reconstruction of discrete morphological characters under a likelihood model. Under simulated phylogenies and data, likelihood-based models are generally accurate when estimating ancestral node values. Analyses with combined fossil and extant data always outperform analyses with extant species alone, even when around one quarter of the fossil information is incorrect. These results are especially pronounced when model assumptions are violated, such as when there is a trend away from the root value. Fossil data are of particular importance when attempting to estimate the root node character state. Attempts should be made to include fossils in analysis of discrete traits under likelihood, even if there is uncertainty in the fossil trait data.
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Wu, Yunkai, Bin Jiang, Ningyun Lu, and Yang Zhou. "Bayesian Network Based Fault Prognosis via Bond Graph Modeling of High-Speed Railway Traction Device." Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/321872.
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Reliability of the traction system is of critical importance to the safety of CRH (China Railway High-speed) high-speed train. To investigate fault propagation mechanism and predict the probabilities of component-level faults accurately for a high-speed railway traction system, a fault prognosis approach via Bayesian network and bond graph modeling techniques is proposed. The inherent structure of a railway traction system is represented by bond graph model, based on which a multilayer Bayesian network is developed for fault propagation analysis and fault prediction. For complete and incomplete data sets, two different parameter learning algorithms such as Bayesian estimation and expectation maximization (EM) algorithm are adopted to determine the conditional probability table of the Bayesian network. The proposed prognosis approach using Pearl’s polytree propagation algorithm for joint probability reasoning can predict the failure probabilities of leaf nodes based on the current status of root nodes. Verification results in a high-speed railway traction simulation system can demonstrate the effectiveness of the proposed approach.
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Ma, Ping Hua, Hong Fu Fan, and Ke Li. "A Model with Back-Propagation Algorithm for the Estimation of Irreducible Water Saturation." Advanced Materials Research 361-363 (October 2011): 445–50. http://dx.doi.org/10.4028/www.scientific.net/amr.361-363.445.
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As one of the most important reservoir parameters, irreducible water saturation, Swir, is a key parameter in evaluating multi-phase flow, as well as its importance in defining oil in-place. Residual oil saturation, the target of tertiary recovery, is also a function of Swir. In traditionally, Swir is determined by conducting capillary pressure experiments, requiring considerable resources and long time periods, with the consequence of a limited number of core plug evaluations for a particular reservoir. Thus, the estimation of Swir with mathematical models is developed in recent years. The study reported in this paper uses artificial neural network to determine Swir. The optimal model is chosen among 25 simulations, subtilizing different combinations of hidden layer nodes and activation functions for the hidden and output layers. Its performance is compared with other conventional models, demonstrating the superior performance of the proposed Swir prediction models.
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Durán, Mayra, Reyes Juárez-Ramírez, Samantha Jiménez, and Claudia Tona. "User Story Estimation based on the Complexity Decomposition using Bayesian Networks." Proceedings of the Institute for System Programming of the RAS 33, no. 2 (2021): 77–92. http://dx.doi.org/10.15514/ispras-2021-33(2)-4.
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Currently, in Scrum, there are different methods to estimate user stories in terms of effort or complexity. Most of the existing techniques consider factors in a fine grain level; these techniques are not always accurate. Although Planning Poker is the most used method in Scrum to estimate user stories, it is primarily effective in experienced teams since the estimation mostly depends on the observation of experts, but it is difficult when is used by inexperienced teams. In this paper, we present a proposal for complexity decomposition in a coarse grain level, in order to consider important factors for complexity estimation. We use a Bayesian network to represent those factors and their relations. The edges of the network are weighted with the judge of professional practitioners about the importance of the factors. The nodes of the network represent the factors. During the user estimation phase, the Scrum team members introduce the values for each factor; in this way, the network generates a value for the complexity of a User story, which is transformed in a Planning Poker card number, which represents the story points. The purpose of this research is to provide to development teams without experience or without historical data, a method to estimate the complexity of user stories through a model focused on the human aspects of developers.
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Liu, Kailong, Kang Li, Qiao Peng, Yuanjun Guo, and Li Zhang. "Data-Driven Hybrid Internal Temperature Estimation Approach for Battery Thermal Management." Complexity 2018 (July 5, 2018): 1–15. http://dx.doi.org/10.1155/2018/9642892.
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Temperature is a crucial state to guarantee the reliability and safety of a battery during operation. The ability to estimate battery temperature, especially the internal temperature, is of paramount importance to the battery management system for monitoring and thermal control purposes. In this paper, a data-driven approach combining the RBF neural network (NN) and the extended Kalman filter (EKF) is proposed to estimate the internal temperature for lithium-ion battery thermal management. To be specific, the suitable input terms and the number of hidden nodes for the RBF NN are first optimized by a two-stage stepwise identification algorithm (TSIA). Then, the teaching-learning-based optimization (TLBO) algorithm is developed to optimize the centres and widths in every neuron of basis function. After optimizing the RBF NN model, a battery lumped thermal model is adopted as the state function with the EKF to filter out the outliers of the RBF model and reduce the estimation error. This data-driven approach is validated under four different conditions in comparison with the linear NN models. The experimental results demonstrate that the proposed RBF data-driven approach outperforms the other approaches and can be extended to other types of batteries for thermal monitoring and management.
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Rakai, Logan, Laleh Behjat, Shawki Areibi, and Tamas Terlaky. "A Multilevel Congestion-Based Global Router." VLSI Design 2009 (November 17, 2009): 1–13. http://dx.doi.org/10.1155/2009/537341.
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Routing in nanometer nodes creates an elevated level of importance for low-congestion routing. At the same time, advances in mathematical programming have increased the power to solve complex problems, such as the routing problem. Hence, new routing methods need to be developed that can combine advanced mathematical programming and modeling techniques to provide low-congestion solutions. In this paper, a hierarchical mathematical programming-based global routing technique that considers congestion is proposed. The main contributions presented in this paper include (i) implementation of congestion estimation based on actual routing solutions versus purely probabilistic techniques, (ii) development of a congestion-based hierarchy for solving the global routing problem, and (iii) generation of a robust framework for solving the routing problem using mathematical programming techniques. Experimental results illustrate that the proposed global router is capable of reducing congestion and overflow by as much as 36% compared to the state-of-the-art mathematical programming models.