Proposed Method Matches Research Articles

Tensor completion with noisy side information

We develop a new model for tensor completion which incorporates noisy side information available on the rows and columns of a 3-dimensional tensor. This method learns a low rank representation of the data along with regression coefficients for the observed noisy features. Given this model, we propose an efficient alternating minimization algorithm to find high-quality solutions that scales to large data sets. Through extensive computational experiments, we demonstrate that this method leads to significant gains in out-of-sample accuracy filling in missing values in both simulated and real-world data. We consider the problem of imputing drug response in three large-scale anti-cancer drug screening data sets: the Genomics of Drug Sensitivity in Cancer (GDSC), the Cancer Cell Line Encyclopedia (CCLE), and the Genentech Cell Line Screening Initiative (GCSI). On imputation tasks with 20% to 80% missing data, we show that the proposed method TensorGenomic matches or outperforms state-of-the-art methods including the original tensor model and a multilevel mixed effects model. With 80% missing data, TensorGenomic improves the R^2 from 0.404 to 0.552 in the GDSC data set, 0.407 to 0.524 in the CCLE data set, and 0.331 to 0.453 in the GCSI data set compared to the tensor model which does not take into account genomic side information.

EESD special issue: AI and data‐driven methods in earthquake engineering – (Part 1)

EESD special issue: AI and data‐driven methods in earthquake engineering – (Part 1)

Gender tagging of named entities using retrieval‐assisted multi‐context aggregation: An unsupervised approach

AbstractInferring the gender of named entities present in a text has several practical applications in information sciences. Existing approaches toward name gender identification rely exclusively on using the gender distributions from labeled data. In the absence of such labeled data, these methods fail. In this article, we propose a two‐stage model that is able to infer the gender of names present in text without requiring explicit name‐gender labels. We use coreference resolution as the backbone for our proposed model. To aid coreference resolution where the existing contextual information does not suffice, we use a retrieval‐assisted context aggregation framework. We demonstrate that state‐of‐the‐art name gender inference is possible without supervision. Our proposed method matches or outperforms several supervised approaches and commercially used methods on five English language datasets from different domains.

Behavior-Driven Development of Microservice Applications

As the number of microservice applications rises, different development methodologies for them are under consideration. In this manuscript, we propose a behavior-driven development method for microservice applications. The proposed method starts with writing end-to-end tests at the system or application level and then moves down to the microservice level, where component and unit tests are written. Next, code that passes these tests is developed one by one for each level. Once user stories are covered, our method loops again to integrate negative tests to achieve holistic testing for the microservices and the application. Finally, the proposed method is validated with an application with five microservices. Results confirm that the proposed method matches with the generally accepted test pyramid.

Three-dimensional reconstruction of porous media using super-dimension-based adjacent block-matching algorithm.

As porous media play an essential role in a variety of industrial applications, it is essential to understand their physical properties. Nowadays, the super-dimensional (SD) reconstruction algorithm is used to stochastically reconstruct a three-dimensional (3D) structure of porous media from a given two-dimensional image. This algorithm exhibits superiority in accuracy compared with classical algorithms because it learns information from the real 3D structure. However, owing to the short development time of the SD algorithm, it also has some limitations, such as inexact porosity characterization, long run time, blocking artifacts, and suboptimal accuracy that may be improved. To mitigate these limitations, this study presents the design of a special template that contains two parts of data (i.e., adjacent blocks and a central block); the proposed method matches adjacent blocks during reconstruction and assigns the matched central block to the area to be reconstructed. Furthermore, we design two important mechanisms during reconstruction: one for block matching and the other for porosity control. To verify the effectiveness of the proposed method compared with an existing SD method, both methods were tested on silica particle material and three homogeneous sandstones with different porosities; meanwhile, we compared the proposed method with a multipoint statistics method and a simulated annealing method. The reconstructed results were then compared with the target both visually and quantitatively. The experimental results indicate that the proposed method can overcome the aforementioned limitations and further improve the accuracy of existing methods. This method achieved 4-6 speedup factor compared with the traditional SD method.

Mass documentation of archaeological ship timbers: introducing a novel, time-efficient approach

This article introduces the annotated scans method as a new approach to ship timber recording. The proposed method consists of several phases: timbers are first scanned in 3D, these scans are then annotated in Rhino, and finally the timber catalogue is generated using a semi-automated workflow. We compare this approach to the current best practice method for timber recording, namely contact digitising. Based on our experience recording the timbers of the Wismar “Big Ship”, we conclude that the proposed method matches, and in some regards surpasses the current best practice method, most notably in terms of cost and time efficiency.

Automatic Identification of Mixed Retinal Cells in Time-Lapse Fluorescent Microscopy Images using High-Dimensional DBSCAN.

Despite providing high spatial resolution, functional imaging remains largely unsuitable for high-throughput experiments because current practices require cells to be manually identified in a time-consuming procedure. Against this backdrop, we seek to integrate such high-resolution technique in high-throughput workflow by automating the process of cell identification. As a step forward, we attempt to identify mixed retinal cells in time-lapse fluorescent microscopy images. Unfortunately, usual 2D image segmentation as well as other existing methods do not adequately distinguish between time courses of different spatial locations. Here, the task gets further complicated due to the inherent heterogeneity of cell morphology. To overcome such challenge, we propose to use a high-dimensional (HiD) version of DBSCAN (density based spatial clustering of applications with noise) algorithm, where difference in such time courses are appropriately accounted. Significantly, outcome of the proposed method matches manually identified cells with over 80% accuracy, marking more than 50% improvement compared to a reference 2D method.

Discrete ordinates characteristics solution for phonon transport in an anisotropic plant canopy

Radiation-vegetation canopy interaction is analyzed using a semi-analytic discrete ordinates characteristics solution. The plant canopy is considered as a single layer containing a set of leave ensembles of bi-Lambertian surfaces and the radiation-plant canopy interaction is described by a radiative transfer equation in which the plant canopy radiative properties depend on the incident radiation direction. An analytical expression for anisotropic plant canopy radiance is derived. Radiance and hemispherical reflectance/transmittance for different boundary conditions and the plant canopy in the visible and near infrared are predicted. Results show that the discrete ordinates characteristics solution using the moderate number of double-Gauss ordinates direction compete well with the FN or “facile” and analytical discrete ordinates methods, which are two other literature quasi-analytical methods for phonon transport in the anisotropic plant canopy. Results also reveal that the proposed method matches exact Chandrasekhar benchmark, except for view cosine direction µ≥0.9, where the accuracy on transmitted radiance is less than 0.3% for low angular discretization. Comparisons between numerical predictions and soybean reflectance experiments indicate that the leaf area index and soil reflectance effects are significant in the near infrared plateau.

A New, Score-Based Multi-Stage Matching Approach for Road Network Conflation in Different Road Patterns

Road-matching processes establish links between multi-sourced road lines representing the same entities in the real world. Several road-matching methods have been developed in the last three decades. The main issue related to this process is selecting the most appropriate method. This selection depends on the data and requires a pre-process (i.e., accuracy assessment). This paper presents a new matching method for roads composed of different patterns. The proposed method matches road lines incrementally (i.e., from the most similar matching to the least similar). In the experimental testing, three road networks in Istanbul, Turkey, which are composed of tree, cellular, and hybrid patterns, provided by the municipality (authority), OpenStreetMap (volunteered), TomTom (private), and Basarsoft (private) were used. The similarity scores were determined using Hausdorff distance, orientation, sinuosity, mean perpendicular distance, mean length of triangle edges, and modified degree of connectivity. While the first four stages determined certain matches with regards to the scores, the last stage determined them with a criterion for overlapping areas among the buffers of the candidates. The results were evaluated with manual matching. According to the precision, recall, and F-value, the proposed method gives satisfactory results on different types of road patterns.

Power Transmission Analysis in Wireless Sensor Networks Using Data Aggregation Techniques

The process model matching is a critical step in many business process management activities. Process model matching consists of finding correspondences between activities of process models. This article presents a method for matching process model. The proposed method matches (i.e., aligns) two process models in three sequential steps. First, activities in the two process models are extracted. Second, the extracted activities are expanded using synonyms, hypernyms, and hyponyms of its composing words. These synonyms, hypernyms, and hyponyms are extracted from the WordNet thesaurus. Third, the expanded activities are compared using the Monge-Elkan similarity metric to detect matches. An empirical study was conducted on three well known datasets to evaluate the proposed method. The results of the experiment showed that the proposed method has the potential to match business process models in an effective manner when step two of the method is based on synonyms and hypernyms.

Water Absorption Properties of Cement Pastes: Experimental and Modelling Inspections

An intermingled fractal units’ model is shown in order to simulate pore microstructures as pore fraction and pore size distribution. This model is aimed at predicting capillary water absorption coefficient and sorptivity values in cement pastes. The results obtained are in good agreement with the experimental ones. For validating this model, a comparison with other procedures has been shown. It is possible to establish that the newly proposed method matches better with the experimental results. That is probably due to the fact that pore size distribution has been considered as a whole. Moreover, even though the proposed model is based on fractal base units, it is able to simulate and predict different properties as well as nonfractal porous microstructure.

A novel, simple model of cascaded fiber Raman lasers

We present a simple numerical method for modeling an nth-order cascaded continuous wave fiber Raman laser. The novelty of this model is the method by which power is transferred between waves, which provides simplicity without the need for any approximations of the equations related to laser dynamics, or simplification of the experimental arrangement. It was found that the results based on the proposed method matches exactly with the results based on established techniques available in the literature.

Hough Voting for 3D Object Recognition under Occlusion and Clutter

This work proposes a novel approach for the detection of free-form shapes in a 3D space. The proposed method matches 3D features through their descriptions to attain correspondences, then accumulates evidence of the presence of the object(s) being sought by verifying the consensus of correspondences within a 3D Hough space. Our approach is capable of recognizing 3D shapes under significant degree of occlusion and clutter and can deal with multiple instances of the shape to be recognized. We validate our proposal by means of a quantitative experimental comparison to the state of the art over two datasets acquired with different sensors (a laser scanner and a stereo camera) and characterized by high degrees of clutter and occlusion. In addition, we propose an extension of the approach to RGB-D (i.e., color and depth) data together with results concerning 3D object recognition from RGB-D data acquired by a Microsoft Kinect sensor.

Product Development Task Planning Using Worth Flow Analysis

The acceleration of the product development cycle continues to be a significant challenge for manufacturing enterprises around the world. This paper describes a task planning method that minimizes the number of trial and error to reduce the development time for large-scale and complex products at the early stage of product development. The proposed method matches groups of product components and determines the development sequence for each component to minimize the amount of feedback information required across task groups. The method provides, as evaluation indices for task prioritization, the product-sum of engineering interaction among components and worth of each component, which the authors define as the “worth flow.” A generic hair dryer with simple mechanical structure serves as an example, illustrating that the proposed method contributes to the reduction in the amount of information required for setting the interface links by 65% compared with the conventional planning methods.

3D 변형가능 형상 모델 기반 3D 얼굴 모델링

3D 얼굴 모델링은 33공간에서 얼굴을 자유롭게 회전 시켜 다양한 얼굴 자세를 표현하고 조명 효과도 적절하게 모델링 할 수 있으므로, 얼굴 자세, 조명, 표정 등의 표현에 있어서 2D 얼굴 모델링에 비해 보다 정교하며 사실감이 뛰어나 얼굴 인식, 게임, 아바타 등에서 많은 요구가 존재한다. 본 논문에서는 3D 변형 가능 형상 모델에 기반을 둔 3D 얼굴 모델링 방법을 제안한다. 제안된 3D 얼굴 모델링 방법은 먼저 3D 스캐너를 통하여 획득한 3D 얼굴 스캔 데이터를 이용하여 3D 얼굴 변형 가능 형상 모델을 구축한다. 다음, 3D 얼굴 모델링을 하고자 하는 얼굴의 2D 이미지 시퀀스로부터, 해당 얼굴의 특징점들을 검출하고 이들을 매칭하여, 매칭된 특징점들로부터 인수분해 기반 SfM 기법을 이용하여 해당 특징점의 3D 버텍스 좌표 값을 구한다. 이후, 구한 3D 버텍스들을 3D 변형 가능 형상 모델에 정합하여 해당 얼굴의 3D 형상 모델을 얻는다. 또한, 2D 얼굴 이미지 시퀀스들로부터 뷰 독립적인 2D 원통 좌표 텍스쳐 맵을 구하고 이를 이용하여 3D 형상 모델을 렌더링 함으로써, 최종적으로 3B 얼굴 모델을 완성한다. 제안된 3D 얼굴 모델링 방법에 의한 3D 얼굴 모델 생성 과정을 통해서, 본 논문에서 제안한 3D 얼굴 모델링 방법이 기존의 얼굴 모델링 방법들에 비해 상대적으로 빠르고 비교적 정교하게 수행됨을 볼 수 있었다. Since 3D face can be rotated freely in 3D space and illumination effects can be modeled properly, 3D face modeling Is more precise and realistic in face pose, illumination, and expression than 2D face modeling. Thus, 3D modeling is necessitated much in face recognition, game, avatar, and etc. In this paper, we propose a 3D face modeling method based on 3D morphable shape modeling. The proposed 3D modeling method first constructs a 3D morphable shape model out of 3D face scan data obtained using a 3D scanner Next, the proposed method extracts and matches feature points of the face from 2D image sequence containing a face to be modeled, and then estimates 3D vertex coordinates of the feature points using a factorization based SfM technique. Then, the proposed method obtains a 3D shape model of the face to be modeled by fitting the 3D vertices to the constructed 3D morphable shape model. Also, the proposed method makes a cylindrical texture map using 2D face image sequence. Finally, the proposed method builds a 3D face model by rendering the 3D face shape model with the cylindrical texture map. Through building processes of 3D face model by the proposed method, it is shown that the proposed method is relatively easy, fast and precise than the previous 3D face model methods.

Online learning of a simple perceptron learning with margin

AbstractThe authors analyze the dynamics of online learning in a simple perceptron using a Gardner‐style margin. The proposed method matches the perceptron rules for a margin of κ = 0 and the Hebb rules when κ → ∞. The results of analysis show that the generalization error is smaller than that of the perceptron rules and the Hebb rules during initial learning even though the proposed method is in between these two sets of learning rules. In addition, the authors show that the generalization error for the proposed method matches that of the perceptron rules in terms of asymptotic characteristics. © 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 35(7): 98–105, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10473

An adaptive filter based on singular‐value decomposition of input signal correlation matrix

AbstractAlthough various algorithms have been proposed for updating the filter coefficients of adaptive filters, problems still remain concerning their convergence speed and the accuracy of filter coefficients after the convergence. to solve these problems, this paper proposes an adaptive algorithm in which filter coefficients are obtained by solving a normal equation (for the optimized filter coefficients or the Wiener‐Hopf equation using eigenvalues of the input‐signal correlation matrix. If there are small eigenvalues in the input‐signal correlation matrix, they are assumed to be zero so that the filter coefficients are calculated by using a generalized inverse matrix. This prevents the increase of errors which occurs when the input is a correlative smooth signal. the proposed method matches nonsteady‐state signals, since the eigenvalues are successively calculated using the rank‐one‐modification method.The characteristics of the proposed adaptive filter were investigated, and a computer simulation of the filter as a noise canceller was carried out. the results show that the characteristics of the filter are superior to those of filters using conventional algorithms, although the amount of computation increases considerably.