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Physical Model to Achieve Virtual Mezzotint 实现虚拟凹版的物理模型
Pub Date : 2007-05-15 DOI: 10.2197/IPSJDC.3.244
Daisuke Tasaki, M. Katou, S. Mizuno, M. Okada
The authors propose a method of producing virtual mezzotint using a physics-based rendering approach. Mezzotint is a traditional copperplate printing technique. An important characteristic is its gradations from black to white. This is acquired in three phases during the plate-making process, i.e., by roughening, scraping, and burnishing. Numerous dots and burrs are created with a rocker in the roughening phase over the entire surface of the copper plate to obtain black areas in the print. The burrs are removed in the second phase with a scraper to yield halftones. The plate surface is finally polished with a burnisher in the last phase to produce the white areas. A method of simulating these phases and physical phenomena is discussed in this paper to make mezzotint enjoyable even for beginners and children. Zigzag-stroke patterns and paraboloidal-dot models are applied to the rocker to simulate the roughening phase. Reducing and smoothing models are applied to the scraper and burnisher to simulate the scraping and burnishing phases. The feasibility of the proposed method is demonstrated by observing and comparing actual and virtual plate surfaces with determined patterns and actual pieces of handcrafted work.
作者提出了一种使用基于物理的渲染方法生成虚拟中色的方法。凹版印刷是一种传统的铜版印刷技术。一个重要的特征是它从黑到白的渐变。这是在制版过程中的三个阶段获得的,即粗糙,刮擦和抛光。在铜板的整个表面上,在粗化阶段用摇杆产生许多点和毛刺,以获得印刷中的黑色区域。在第二阶段用刮刀去除毛刺以产生半色调。在最后一阶段,用抛光机抛光钢板表面,产生白色区域。本文讨论了一种模拟这些阶段和物理现象的方法,使初学者和儿童也能欣赏到版画。采用之字形冲程模式和抛物面点模型对摇杆进行粗化过程模拟。对刮刀和抛光机应用了还原和平滑模型来模拟刮刀和抛光阶段。通过观察和比较确定图案的实际和虚拟板表面和实际手工制品,证明了该方法的可行性。
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引用次数: 1
Retrieving functionally similar bioinformatics workflows using TF-IDF filtering 使用TF-IDF过滤检索功能相似的生物信息学工作流程
Pub Date : 2007-04-15 DOI: 10.2197/IPSJDC.3.164
Junya Seo, S. Seno, Y. Takenaka, H. Matsuda
In bioinformatics, dealing with tools to analyze biological data becomes important. Those tools are provided by various institutions and the number of the tools is rapidly increasing. Recently many institutions have been offering those tools and access to databases with Web service technologies. The workflow technology is one of the ways to manage those tools and it is becoming available in bioinformatics. In order to compose workflows, several research groups develop and provide workflow composing tools. And consequently, the concept “Workflow Reuse” is also arisen in order to help workflow composition. Nevertheless it is still difficult to search for the reusable workflows from the repository of workflows in the current situation. In this paper, we propose a method to extract reusable workflows from the repository by using currently available information. We could extract some functionally similar workflows as reusable ones. By extracting reusable workflows efficiently, researchers can compose their workflow more easily.
在生物信息学中,处理分析生物数据的工具变得很重要。这些工具由各机构提供,工具的数量正在迅速增加。最近,许多机构都在提供这些工具,并使用Web服务技术访问数据库。工作流技术是管理这些工具的一种方法,它在生物信息学中越来越可用。为了组合工作流,一些研究小组开发并提供了工作流组合工具。因此,为了帮助工作流的组合,“工作流重用”的概念也随之产生。然而,在目前的情况下,从工作流存储库中搜索可重用工作流仍然很困难。在本文中,我们提出了一种利用当前可用信息从存储库中提取可重用工作流的方法。我们可以提取一些功能相似的工作流作为可重用的工作流。通过有效地提取可重用工作流,研究人员可以更轻松地构建工作流。
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引用次数: 0
GroupAdaBoost: Accurate Prediction and Selection of Important Genes GroupAdaBoost:准确预测和选择重要基因
Pub Date : 2007-04-15 DOI: 10.2197/IPSJDC.3.145
Takashi Takenouchi, M. Ushijima, S. Eguchi
In this paper, we propose GroupAdaBoost which is a variant of AdaBoost for statistical pattern recognition. The objective of the proposed algorithm is to solve the “ p » n ”problem arisen in bioinformatics. In a microarray experiment, gene expressions are observed to extract any specific pattern of gene expressions related to a disease status. Typically, p is the number of investigated genes and n is number of individuals. The ordinary method for predicting the genetic causes of diseases is apt to over-learn from any particular training dataset because of the“ p » n ” problem. We observed that GroupAdaBoost gave a robust performance for cases of the excess number p of genes. In several real datasets which are publicly available from web-pages, we compared the analysis of results among the proposed method and others, and a small scale of simulation study to confirm the validity of the proposed method. Additionally the proposed method effectively worked for the identification of important genes.
在本文中,我们提出了GroupAdaBoost,它是AdaBoost的一个变体,用于统计模式识别。该算法的目标是解决生物信息学中出现的“p»n”问题。在微阵列实验中,观察基因表达以提取与疾病状态相关的任何特定基因表达模式。通常,p是研究基因的数量,n是个体的数量。由于“p»n”问题,预测疾病遗传原因的普通方法容易从任何特定的训练数据集中过度学习。我们观察到,GroupAdaBoost在基因数量超过p的情况下表现良好。在几个公开的网页上的真实数据集上,我们比较了所提出方法和其他方法的分析结果,并进行了小规模的模拟研究,以证实所提出方法的有效性。此外,该方法还能有效地识别重要基因。
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引用次数: 4
Duality between Call-by-value Reductions and Call-by-name Reductions 按值调用约简和按名称调用约简之间的对偶性
Pub Date : 2007-04-15 DOI: 10.2197/IPSJDC.3.207
D. Kimura
Wadler proposed the dual calculus, which corresponds to classical sequent calculus LK, and studied the relationship between the λμ-calculus and the dual calculus as equational systems to explain the duality between call-by-value and call-by-name in a purely syntactical way. Wadler left an open question whether one can obtain similar results by replacing the equations with reductions. This paper gives one answer to his question. We first refine the λμ-calculus as reduction systems by reformulating sum types and omitting problematic reduction rules that are not simulated by reductions of the dual calculus. Secondly, we give translations between the call-by-name λμ-calculus and the call-by-name dual calculus, and show that they preserve the call-by-name reductions. We also show that the compositions of these translations become identity maps up to the call-by-name reductions. We also give translations for the call-by-value systems, and show that they satisfy properties similar to the call-by-name translations. Thirdly, we introduce translations between the call-by-value λμ-calculus and the call-by-name one by composing the above translations with duality on the dual calculus. We finally obtain results corresponding to Wadler's, but our results are based on reductions.
Wadler提出了对偶演算,对应于经典序演算LK,并将λμ演算与对偶演算作为方程组进行研究,从纯语法的角度解释了按值调用与按名调用之间的对偶性。瓦德勒留下了一个悬而未决的问题,即是否可以用约简代替方程来得到类似的结果。本文对他的问题给出了一个答案。我们首先将λμ微积分细化为约简系统,通过重新表述和类型,并省略了对偶微积分的约简不能模拟的问题约简规则。其次,给出了命名λμ演算与命名对偶演算之间的翻译,并证明它们保持了命名约简。我们还表明,这些翻译的组成成为身份映射,直到call-by-name还原。我们还给出了按值调用系统的转换,并证明它们满足与按名称调用转换类似的属性。第三,通过对偶演算上的对偶性,引入了按值调用λμ-演算与按名调用λμ-演算之间的转换。我们最终得到了与Wadler的结果相对应的结果,但我们的结果是基于约简的。
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引用次数: 3
A Multi-Resolution Grid Snapping Technique Based on Fuzzy Theory 基于模糊理论的多分辨率网格捕获技术
Pub Date : 2007-04-15 DOI: 10.2197/IPSJDC.3.198
Qamar Uddin Khand, Sumudu Dematapitiya, S. Saga, J. Maeda
This paper presents a grid snapping technique, called multi-resolution fuzzy grid snapping (MFGS), that enables automatic mouse cursor snapping for a multi-resolution grid system. Quick and frequent switching between high- and low-resolution grid snapping is essential to make geometrical drawings that include both fine and coarse structures when using CAD systems with ordinary single-resolution grid systems. MFGS is intended to relieve users of this tedious manual switching. MFGS dynamically selects an appropriate snapping resolution level from a multi-resolution grid system according to the pointing behavior of the user. MFGS even supports an extremely fine grid resolution level, which is referred to as the no-snapping level. We show experimental results which demonstrate that MFGS is an effective grid snapping technique that speeds up low-resolution grid snapping while retaining the ability to snap to high-resolution grids. Furthermore, we examine the role of fuzziness in MFGS and its effect on snapping performance.
本文提出了一种网格捕捉技术,称为多分辨率模糊网格捕捉(MFGS),它可以实现多分辨率网格系统中鼠标光标的自动捕捉。在使用具有普通单分辨率网格系统的CAD系统时,快速和频繁地在高分辨率和低分辨率网格捕获之间切换对于绘制包括精细和粗糙结构的几何图形至关重要。MFGS旨在将用户从这种繁琐的手动切换中解脱出来。MFGS根据用户的指向行为,从多分辨率网格系统中动态选择合适的捕捉分辨率。MFGS甚至支持一个非常精细的网格分辨率水平,这被称为无捕捉水平。实验结果表明,MFGS是一种有效的网格捕获技术,可以在保持捕获高分辨率网格的能力的同时加速低分辨率网格捕获。此外,我们还研究了模糊性在MFGS中的作用及其对捕获性能的影响。
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引用次数: 3
Hardness Results on Local Multiple Alignment of Biological Sequences 生物序列局部多重比对的硬度结果
Pub Date : 2007-04-15 DOI: 10.2197/IPSJDC.3.174
T. Akutsu, Hiroki Arimura, S. Shimozono
This paper studies the local multiple alignment problem, which is, given protein or DNA sequences, to locate a region (i.e., a substring) of fixed length from each sequence so that the score determined from the set of regions is optimized. We consider the following scoring schemes: the relative entropy score (i.e., average information content), the sum-of-pairs score and a relative entropy-like score introduced by Li, et al. We prove that multiple local alignment is NP-hard under each of these scoring schemes. In particular, we prove that multiple local alignment is APX-hard under relative entropy scoring. It implies that unless P =NP there is no polynomial time algorithm whose worst case approximation error can be arbitrarily specified(precisely, a polynomial time approximation scheme). Several related theoretical results are also provided.
本文研究了局部多重比对问题,即给定蛋白质或DNA序列,从每个序列中定位一个固定长度的区域(即子串),从而优化从区域集确定的分数。我们考虑了以下评分方案:相对熵评分(即平均信息含量)、对和评分和由Li等人引入的类相对熵评分。我们证明了在每一种计分方案下,多局部对齐都是np困难的。特别是在相对熵评分下,我们证明了多局部对齐是APX-hard的。这意味着除非P =NP,否则不存在最坏情况近似误差可以任意指定的多项式时间算法(准确地说,是多项式时间近似方案)。并给出了几个相关的理论结果。
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引用次数: 4
Function Approximation Approach to the Inference of Neural Network Models of Genetic Networks 遗传网络神经网络模型推理的函数逼近方法
Pub Date : 2007-04-15 DOI: 10.2197/IPSJDC.3.153
Shuhei Kimura, Katsuki Sonoda, S. Yamane, Koki Matsumura, M. Hatakeyama
A model based on a set of differential equations can effectively capture various dynamics. This type of model is therefore ideal for describing genetic networks. Several genetic network inference algorithms based on models of this type have been proposed. Most of these inference methods use models based on a set of differential equations of the fixed form to describe genetic networks. In this study, we propose a new method for the inference of genetic networks. To describe genetic networks, the proposed method does not use models of the fixed form, but uses neural network models. In order to interpret obtained neural network models, we also propose a method based on sensitivity analysis. The effectiveness of the proposed methods is verified through a series of artificial genetic network inference problems.
基于一组微分方程的模型可以有效地捕捉各种动态。因此,这种类型的模型是描述遗传网络的理想模型。已经提出了几种基于这类模型的遗传网络推理算法。这些推理方法大多使用基于一组固定形式的微分方程的模型来描述遗传网络。在这项研究中,我们提出了一种新的遗传网络推断方法。为了描述遗传网络,该方法不使用固定形式的模型,而是使用神经网络模型。为了解释得到的神经网络模型,我们还提出了一种基于灵敏度分析的方法。通过一系列人工遗传网络推理问题验证了所提方法的有效性。
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引用次数: 6
A biclustering method for gene expression module discovery using a closed itemset enumeration algorithm 基于封闭项集枚举算法的基因表达模块发现的双聚类方法
Pub Date : 2007-04-15 DOI: 10.2197/IPSJDC.3.183
Yoshifumi Okada, W. Fujibuchi, P. Horton
A gene expression module (module for short) is a set of genes with shared expression behavior under certain experimental conditions. Discovering of modules enables us to uncover the function of uncharacterized genes or genetic networks. In recent years, several biclustering methods have been suggested to discover modules from gene expression data matrices, where a bicluster is defined as a subset of genes that exhibit a highly correlated expression pattern over a subset of conditions. Biclustering however involves combinatorial optimization in selecting the rows and columns composing modules. Hence most existing algorithms are based on heuristic or stochastic approaches and produce possibly sub-optimal solutions. In this paper, we propose a novel biclustering method, BiModule, based on a closed itemset enumeration algorithm. By exhaustive enumeration of such biclusters, it is possible to select only biclusters satisfying certain criteria such as a user-specified bicluster size, an enrichment of functional annotation terms, etc. We performed comparative experiments to existing salient biclustering methods to test the validity of biclusters extracted by BiModule using synthetic data and real expression data. We show that BiModule provides high performance compared to the other methods in extracting artificially-embedded modules as well as modules strongly related to GO annotations, protein-protein interactions and metabolic pathways.
基因表达模块(简称模块)是在一定实验条件下具有共同表达行为的一组基因。发现模块使我们能够揭示未表征的基因或遗传网络的功能。近年来,人们提出了几种双聚类方法来从基因表达数据矩阵中发现模块,其中双聚类被定义为在一组条件下表现出高度相关表达模式的基因子集。然而,双聚类涉及选择组成模块的行和列的组合优化。因此,大多数现有算法都是基于启发式或随机方法,并可能产生次优解。在本文中,我们提出了一种新的基于封闭项集枚举算法的双聚类方法BiModule。通过对此类双聚类的详尽枚举,可以只选择满足某些标准的双聚类,例如用户指定的双聚类大小、功能注释术语的丰富性等。我们使用合成数据和真实表达数据,与现有显著性双聚类方法进行对比实验,检验BiModule提取的双聚类的有效性。我们表明,与其他方法相比,BiModule在提取人工嵌入模块以及与GO注释、蛋白质-蛋白质相互作用和代谢途径密切相关的模块方面提供了高性能。
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引用次数: 28
Estimating Interruptibility in the Home for Remote Communication Based on Audio-Visual Tracking 基于视听跟踪的家庭远程通信可中断性评估
Pub Date : 2007-03-15 DOI: 10.2197/IPSJDC.3.125
Y. Takemae, Takehiko Ohno, I. Yoda, S. Ozawa
This paper presents a method for automatically estimating human interruptibility in the home environment. To make online remote communication smoother, determining if it is appropriate to interrupt the remote partner is critical. As a first step in achieving this goal, several audio-visual features, extracted from data streams captured by a camera and a microphone, are correlated to human assessments of own interruptibility. Based on these features, the level of interruptibility is estimated using the trained Support Vector Regression (SVR) technique. Finally, we discuss the potential of our method based on the results of several experiments.
本文提出了一种自动估计家庭环境中人的可中断性的方法。为了使在线远程通信更顺畅,确定是否适合中断远程合作伙伴是至关重要的。作为实现这一目标的第一步,从摄像机和麦克风捕获的数据流中提取的几个视听特征与人类对自身可中断性的评估相关联。基于这些特征,使用训练支持向量回归(SVR)技术估计可中断性水平。最后,根据几个实验的结果,讨论了该方法的潜力。
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引用次数: 2
Drumix: An Audio Player with Real-time Drum-part Rearrangement Functions for Active Music Listening Drumix:一个音频播放器,具有实时鼓部分重排功能,用于主动音乐收听
Pub Date : 2007-03-15 DOI: 10.2197/IPSJDC.3.134
Kazuyoshi Yoshii, Masataka Goto, Kazunori Komatani, T. Ogata, HIroshi G. Okuno
This paper presents a highly functional audio player, called Drumix, that allows a listener to control the volume, timbre, and rhythmic patterns (drum patterns)of bass and snare drums within existing audio recordings in real time. A demand for active music listening has recently emerged. If the drum parts of popular songs could be manipulated, listeners could have new musical experiences by freely changing their impressions of the pieces (e.g., making the drum performance more energetic)instead of passively listening to them. To achieve this, Drumix provides three functions for rearranging drum parts, i.e., a volume control function that enables users to cut or boost the volume of each drum with a drum-specific volume slider, a timbre change function that allows them to replace the original timbre of each drum with another selected from a drop-down list, and a drum-pattern editing function that enables them to edit repetitive patterns of drum onsets on a graphical representation of their scores. Special musical skills are not required to use these functions. Subjective experiments revealed that Drumix could add a new dimension to the way listeners experience music.
本文介绍了一个功能强大的音频播放器,名为Drumix,它允许听众在现有的音频记录中实时控制低音和军鼓的音量、音色和节奏模式(鼓模式)。最近出现了积极听音乐的需求。如果流行歌曲的鼓部分可以被操纵,听众可以自由地改变他们对作品的印象(例如,使鼓表演更有活力),而不是被动地听,从而获得新的音乐体验。为了实现这一目标,Drumix提供了三个功能来重新安排鼓的部分,即,一个音量控制功能,使用户能够削减或提高每个鼓的音量与鼓特定的音量滑块,一个音色变化功能,允许他们替换每个鼓的原始音色与另一个从下拉列表中选择,和一个鼓模式编辑功能,使他们能够编辑鼓的重复模式,在他们的分数的图形表示。使用这些功能不需要特殊的音乐技能。主观实验表明,Drumix可以为听众体验音乐的方式增加一个新的维度。
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引用次数: 31
期刊
Ipsj Digital Courier
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