ppxscal/embedding_network huggingface dataset:
The Application of Macro-Economic Prediction Based on Improved Gene Expression Programming
Authors: Yan Jingfeng, Li Guoqing
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

An Improved Gene Expression Programming (IGEP)is proposed in this paper. It has some new features: 1) introducing a newindividual coding;2) introducing a new way of creating constants; 3) introducing a hybrid self-adaptive crossover-mutation operator, which can enhance the search ability and exploit the optimum offspring. To validate the performance of IGEP, this paper applies IGEP into the solution of the macro-economic predictions. The experimental results demonstrate thatImproved GEP can automatically find better Optimization Model, based on which prediction will be generated much more exactly.
Toward Cognitive Modeling for Predicting Usability
Authors: Bonnie E. John, Shunsuke Suzuki
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends (2009)

Historically, predictive human performance modeling has been successful at predicting the task execution time of skilled users on a desktop computer. More recent work has predicted novice behavior in web searches. This paper reports on a collaborative effort between industry and academia to expand the scope of predictive modeling to the mobile phone domain, both skilled and novice behavior, and how human performance relates to the perception of usability. Since, at this writing, only preliminary results to validate models of mobile phone use are in, we describe the process we will use to progress towards our modeling goals.
Stepping into the operating theater: ARAV — Augmented Reality Aided Vertebroplasty
Authors: Christoph Bichlmeier, Ben Ockert, Sandro Michael Heining, Ahmad Ahmadi, Nassir Navab
Venue: Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality (2008)

Augmented Reality (AR) for preoperative diagnostics and planning, intra operative navigation and postoperative follow-up examination has been a topic of intensive research over the last two decades. However, clinical studies showing AR technology integrated into the real clinical environment and workflow are still rare. The incorporation of an AR system as a standard tool into the real clinical workflow has not been presented so far. This paper reports on the strategies and intermediate results of the ARAV — Augmented Reality Aided Vertebroplasty project that has been initiated to make an AR system based on a stereo video see-through head mounted display that is permanently available in the operating room (OR).
An Evaluation of Scale and Noise Sensitivity of Fibre Orientation Estimation in Volume Images
Authors: Maria Axelsson
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

Fibre orientation influences many important properties of fibre-based materials, for example, strength and stiffness. Fibre orientation and the orientation anisotropy in paper and other wood fibre-based materials have previously been estimated using two-dimensional images. Recently, we presented a method for estimating the three-dimensional fibre orientation in volume images based on local orientation estimates. Here, we present an evaluation of the method with respect to scale and noise sensitivity. The evaluation is performed for both tubular and solid fibres. We also present a new method for automatic scale selection for solid fibres. The method is based on a segmentation of the fibres that also provides an estimate of the fibre dimension distribution in an image. The results show that the fibre orientation estimation performs well both in noisy images and at different scales. The presented results can be used as a guide to select appropriate parameters for the method when it is applied to real data. The applicability of the fibre orientation estimation to fibre-based materials with solid fibres is demonstrated for a volume image of a press felt acquired with X-ray microtomography. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Estimating the Cumulative Effects of Different Roads Using Roadless Volume Index - A Case Study in Yunnan Province
Authors: Liu Shiliang, Dong Yuhong
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

Roads encroaching into undeveloped areas generally degrade ecological and watershed conditions. The road networks bring forth many ecological effects. The span of documented effects ranges from a few meters to many kilometers and different grade road have distinct impact. We used a metric, roadless volume (RV), which is derived from the calculated distance to the nearest road to estimate the effect of different roads on various ecosystems and took Xishuangbanna Autonomous Region as a case. The results showed that roads had a close positive relationship with ecosystem patch number, village and negative relationship with elevation. The calculated RV index clearly reveal road effect on different land uses. The grassland, shrub, forest land have more roadless volume while constructive lands have less. Scenario analysis showed RV decreased with with the road network completeness. This suggests that full road network data should be considered to avoid the underestimate of the comprehensive effects.
Measuring the Board Governance Capability in China by Means of Neural Networks and Genetic Algorithms
Authors: Jian Deng
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 04 (2009)

This paper took a research on the Board of governance capacity measurement using the neural networks and genetic algorithms method. After constructing a measurement indicator system about Board of governance capacity, the paper took a empirical rearch on Chinese company’s board governance capacity using the listed companies as the data sample. The results show that NNGA model improved the networks' performance comparing with traditional NN model. This paper took a research on the Board of governance capacity measurement using the neural networks and genetic algorithms method. After constructing a measurement indicator system about Board of governance capacity, the paper took a empirical rearch on Chinese company’s board governance capacity using the listed companies as the data sample. The results show that NNGA model improved the networks' performance comparing with traditional NN model. The stochastic nature of NNGA networks' structures develop more heterogeneous structures than NN model which were chosen through a fixed procedure. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Networked Control System Based on Embedded Dynamic Web Intelligence
Authors: Liu Yubin, Liu Yucheng
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

Web intelligence has been widely used in industrial automation system, this paper presented a sort of integrated control scheme based on embedded Web intelligence that aimed at the existent problems such as distributing of gas stations being wide in China, communication protocol of dispenser being disunion, being difficult to realize integrated control and so on. The intelligent computer MOXA7420/7410 based on Intel Xscale IXP-422 266Mhz RISC CPU used as its hardware was chosen as the forecourt controller of gas stations. The field control device could be connected into Internet by means of multi-manner such as Ethernet pork and wireless pork and so on. The realization of networked control system is based on Web intelligence. The Web server applied the architecture of browser / server, the control unit of Web dynamic browsing by means of the scheme of Apache＋Html＋PHP. The practical test shows that it is high in security level, and it is able to be applied to industrial control field that has very strict demand such as being high in real time performance, being strong against field disturbance, and being adaptable in complex work environment.
Shadow Awareness: Bodily Expression Supporting System with Use of Artificial Shadow
Authors: Yoshiyuki Miwa, Shiorh Itai, Takabumi Watanabe, Koji Iida, Hiroko Nishi
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part II: Novel Interaction Methods and Techniques (2009)

As a supporting means for self-creating bodily expression, shadow media system was developed with which shadow is artificially deformed into diverse forms and such deformed shadow can be displayed on a screen without separating it from the own body. With the system, it was found that the awareness was established inside the body via deformed shadows; therefore it can support an improvised creation of the images. Furthermore, by the subject-object inseparable interaction through shadows, co-creation of images with others was encouraged. Accordingly, it was indicated that this media system is promising and effective to support co-creative expression and shows its potential applicability as a creative archive technology to connect to past people.
Unsupervised recognition of literal and non-literal use of idiomatic expressions
Authors: Caroline Sporleder, Linlin Li
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (2009)

We propose an unsupervised method for distinguishing literal and non-literal usages of idiomatic expressions. Our method determines how well a literal interpretation is linked to the overall cohesive structure of the discourse. If strong links can be found, the expression is classified as literal, otherwise as idiomatic. We show that this method can help to tell apart literal and non-literal usages, even for idioms which occur in canonical form.
An Integrative Approach to Geospatial Data Fusion
Authors: Silvija Stankutė, Hartmut Asche
Venue: Proceedings of the International Conference on Computational Science and Its Applications: Part I (2009)

Geodata are used in different branches of industry or academic fields, e.g. landscape planning, environmental protection, traffic, urbanism, economy, tourism et cetera. Depending on the objectives and applications, geodata will have to meet certain requirements in order to be utilised, e.g. concerning geometry and/or semantics. A frequent problem of geo information processing is to identify suitable datasets. The geometric requirements are often met, while this is not the case with semantic requirements. Sometimes geo datasets have similar geometric properties but different semantics. Generally, the acquisition of fresh geodata meeting the requirements defined is not an option. Instead, data mining concepts, as such as data fusion, provide an effective solution to this problem. The fundamental concept of data fusion is the extraction of the best-fit geometry data as well as the most suitable semantic data from existing datasets. The extracted data features are subsequently amalgamated into a newly created dataset. Data fusion can be applied to linear and polygonal data. This work introduces algorithms allowing for the joining of linear structures. The method discussed is based on the comparison of coordinates. The fusion process has been automated and implemented in the DataMerge software tool using the PERL scripting language and thus is not bound to any specific GIS software.
On Negations in Boolean Networks
Authors: Norbert Blum
Venue: Efficient Algorithms: Essays Dedicated to Kurt Mehlhorn on the Occasion of His 60th Birthday (2009)

Although it is well known by a counting argument that relative to the full basis most Boolean functions need exponentially many operations, for explicit Boolean functions only linear lower bounds with small constant factors are known. For monotone networks (i.e., networks without negations) exponential lower bounds for explicit monotone Boolean functions have been proved. We describe the state of the art and give some arguments why techniques developed for the proof of lower bounds for monotone networks cannot easily be extended to Boolean networks with negations.
Mining abnormal patterns from heterogeneous time-series with irrelevant features for fault event detection
Authors: Ryohei Fujimaki, Takayuki Nakata, Hidenori Tsukahara, Akinori Sato, Kenji Yamanishi
Venue: Statistical Analysis and Data Mining (2009)

We address the issue of detecting fault events in multivariate time series. We suppose the following realistic and challenging situations: (A) the features to which multivariate time series correspond are heterogeneous; (B) only a small number of examples of fault events are available in advance relative to a large number of normal examples; and (C) many features irrelevant to fault events are included. To resolve these situations, detecting faults specifically in machine systems such as automobile, train, etc. is usually required. We propose an algorithm to resolve the issue. Key ideas in it include: (1) transforming the time-series for each feature into a sequence of anomaly scores, in order to map heterogeneous features to homogeneous ones (an anomaly score indicates the degree of anomalousness relative to an ordinal sequence) and then representing the pattern of a fault event in terms of fault anomaly score vectors; (2) selecting features specifying a fault event by means of iterative optimization using both normal and fault anomaly score vectors. We then monitor the degree of anomalousness with respect to target anomaly score vectors by comparing them with the abnormal patterns. We demonstrate the effectiveness of our proposed algorithm through an application to an actual automobile fault diagnosis data set as well as an artificial dataset. &copy; 2009 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 2: 1-17, 2009
A general method for reducing the complexity of relational inference and its application to MCMC
Authors: Hoifung Poon, Pedro Domingos, Marc Sumner
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 2 (2008)

Many real-world problems are characterized by complex relational structure, which can be succinctly represented in first-order logic. However, many relational inference algorithms proceed by first fully instantiating the first-order theory and then working at the propositional level. The applicability of such approaches is severely limited by the exponential time and memory cost of propositionalization. Singla and Domingos (2006) addressed this by developing a "lazy" version of the WalkSAT algorithm, which grounds atoms and clauses only as needed. In this paper we generalize their ideas to a much broader class of algorithms, including other types of SAT solvers and probabilistic inference methods like MCMC. Lazy inference is potentially applicable whenever variables and functions have default values (i.e., a value that is much more frequent than the others). In relational domains, the default is false for atoms and true for clauses. We illustrate our framework by applying it to MC-SAT, a state-of-the-art MCMC algorithm. Experiments on a number of real-world domains show that lazy inference reduces both space and time by several orders of magnitude, making probabilistic relational inference applicable in previously infeasible domains.
A framework for evaluating the usability of mobile phones based on multi-level, hierarchical model of usability factors
Authors: Jeongyun Heo, Dong-Han Ham, Sanghyun Park, Chiwon Song, Wan Chul Yoon
Venue: Interacting with Computers (2009)

As a mobile phone has various advanced functionalities or features, usability issues are increasingly challenging. Due to the particular characteristics of a mobile phone, typical usability evaluation methods and heuristics, most of which are relevant to a software system, might not effectively be applied to a mobile phone. Another point to consider is that usability evaluation activities should help designers find usability problems easily and produce better design solutions. To support usability practitioners of the mobile phone industry, we propose a framework for evaluating the usability of a mobile phone, based on a multi-level, hierarchical model of usability factors, in an analytic way. The model was developed on the basis of a set of collected usability problems and our previous study on a conceptual framework for identifying usability impact factors. It has multi-abstraction levels, each of which considers the usability of a mobile phone from a particular perspective. As there are goal-means relationships between adjacent levels, a range of usability issues can be interpreted in a holistic as well as diagnostic way. Another advantage is that it supports two different types of evaluation approaches: task-based and interface-based. To support both evaluation approaches, we developed four sets of checklists, each of which is concerned, respectively, with task-based evaluation and three different interface types: Logical User Interface (LUI), Physical User Interface (PUI) and Graphical User Interface (GUI). The proposed framework specifies an approach to quantifying usability so that several usability aspects are collectively measured to give a single score with the use of the checklists. A small case study was conducted in order to examine the applicability of the framework and to identify the aspects of the framework to be improved. It showed that it could be a useful tool for evaluating the usability of a mobile phone. Based on the case study, we improved the framework in order that usability practitioners can use it more easily and consistently.
Language and translation model adaptation using comparable corpora
Authors: Matthew Snover, Bonnie Dorr, Richard Schwartz
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

Traditionally, statistical machine translation systems have relied on parallel bi-lingual data to train a translation model. While bi-lingual parallel data are expensive to generate, monolingual data are relatively common. Yet monolingual data have been under-utilized, having been used primarily for training a language model in the target language. This paper describes a novel method for utilizing monolingual target data to improve the performance of a statistical machine translation system on news stories. The method exploits the existence of comparable text---multiple texts in the target language that discuss the same or similar stories as found in the source language document. For every source document that is to be translated, a large monolingual data set in the target language is searched for documents that might be comparable to the source documents. These documents are then used to adapt the MT system to increase the probability of generating texts that resemble the comparable document. Experimental results obtained by adapting both the language and translation models show substantial gains over the baseline system.
On Computing Solutions of Linear Diophantine Equations with One Non-linear Parameter
Authors: Armin Grosslinger, Stefan Schuster
Venue: Proceedings of the 2008 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (2008)

We present an algorithm for solving Diophantine equations which are linear in the variables, but non-linear in one parameter. We are looking for the pointwise solutions, i.e., the solutions for the unknowns in dependence of the value of the parameter. Solving Diophantine equations is central to computing the data dependences of certain codes (loops with certain array accesses) which often occur in scientific computing. Our algorithm enables the computation of data dependences in more general situations than is possible with current algorithms.
Study on Pastures Ecological Footprint of Baotou Region
Authors: Xiaoting Wang, Jixi Gao
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

The ecological footprint, as an excellent tool, has received much attention as an indicator for sustainable development over the 10 years. Pasture is one important natural resource. How can we calculate the pasture footprint dominant by agriculture and animal husbandry in Northern China. We take different approaches calculation the pasture. First we use the conventional ecological footprint method. Second we induct ‘standard sheep unit’ concept calculating the ecological footprint of pasture. Then we contrast the result of different method and China pasture footprint in ASIA-PACIFIC 2005. We think that use standard sheep unit calculating the pasture footprint can give the accurate result that help us can catch hold of the question.
Self-Organizing Maps for Pose Estimation with a Time-of-Flight Camera
Authors: Martin Haker, Martin Böhme, Thomas Martinetz, Erhardt Barth
Venue: Proceedings of the DAGM 2009 Workshop on Dynamic 3D Imaging (2009)

We describe a technique for estimating human pose from an image sequence captured by a time-of-flight camera. The pose estimation is derived from a simple model of the human body that we fit to the data in 3D space. The model is represented by a graph consisting of 44 vertices for the upper torso, head, and arms. The anatomy of these body parts is encoded by the edges, i.e. an arm is represented by a chain of pairwise connected vertices whereas the torso consists of a 2-dimensional grid. The model can easily be extended to the representation of legs by adding further chains of pairwise connected vertices to the lower torso. The model is fit to the data in 3D space by employing an iterative update rule common to self-organizing maps. Despite the simplicity of the model, it captures the human pose robustly and can thus be used for tracking the major body parts, such as arms, hands, and head. The accuracy of the tracking is around 5---6 cm root mean square (RMS) for the head and shoulders and around 2 cm RMS for the head. The implementation of the procedure is straightforward and real-time capable.
The Normalized Compression Distance as a Distance Measure in Entity Identification
Authors: Sebastian Klenk, Dennis Thom, Gunther Heidemann
Venue: Proceedings of the 9th Industrial Conference on Advances in Data Mining. Applications and Theoretical Aspects (2009)

The identification of identical entities accross heterogeneous data sources still involves a large amount of manual processing. This is mainly due to the fact that different sources use different data representations in varying semantic contexts. Up to now entity identification requires either the --- often manual --- unification of different representations, or alternatively the effort of programming tools with specialized interfaces for each representation type. However, for large and sparse databases, which are common e.g. for medical data, the manual approach becomes infeasible.We have developed a widely applicable compression based approach that does not rely on structural or semantical unity. The results we have obtained are promising both in recognition precision and performance.