ppxscal/embedding_network huggingface dataset:
Applied Software Architecture, 1st edition
Authors: Christine Hofmeister, Robert Nord, Dilip Soni
Venue:  (2009)

"Designing a large software system is an extremely complicated undertaking that requires juggling differing perspectives and differing goals, and evaluating differing options. Applied Software Architecture is the best book yet that gives guidance as to how to sort out and organize the conflicting pressures and produce a successful design." -- Len Bass, author of Software Architecture in Practice. Quality software architecture design has always been important, but in today's fast-paced, rapidly changing, and complex development environment, it is essential. A solid, well-thought-out design helps to manage complexity, to resolve trade-offs among conflicting requirements, and, in general, to bring quality software to market in a more timely fashion. Applied Software Architecture provides practical guidelines and techniques for producing quality software designs. It gives an overview of software architecture basics and a detailed guide to architecture design tasks, focusing on four fundamental views of architecture--conceptual, module, execution, and code. Through four real-life case studies, this book reveals the insights and best practices of the most skilled software architects in designing software architecture. These case studies, written with the masters who created them, demonstrate how the book's concepts and techniques are embodied in state-of-the-art architecture design. You will learn how to: * create designs flexible enough to incorporate tomorrow's technology; * use architecture as the basis for meeting performance, modifiability, reliability, and safety requirements; * determine priorities among conflicting requirements and arrive at a successful solution; and * use software architecture to help integrate system components. Anyone involved in software architecture will find this book a valuable compendium of best practices and an insightful look at the critical role of architecture in software development.
Gait Representation and Recognition Using Haar Wavelet and Radon Transform
Authors: Hao Zhang, Zhijing Liu
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

This paper presented a new gait identification and authentication method based on Haar wavelet and Radon transform. This method consists of two stages, gait modeling and recognition. In the first stage, images extracted from video sequences are pre-processed into binary silhouette. In terms of gait cycle, they are divided into 4 states, in each of which the distinct images are selected. The horizontal and vertical features are acquired by Haar wavelet, and then feature vectors are obtained respectively by Radon transform. In the second stage, probe sequences are fed. After feature transform of image sequence, the value of similarity can be obtained by comparing probe vectors with gallery ones and optimized to give gait recognition. Consequently, we can improve the rate of recognition by further optimization.
A tale of two parsers: investigating and combining graph-based and transition-based dependency parsing using beam-search
Authors: Yue Zhang, Stephen Clark
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

Graph-based and transition-based approaches to dependency parsing adopt very different views of the problem, each view having its own strengths and limitations. We study both approaches under the framework of beam-search. By developing a graph-based and a transition-based dependency parser, we show that a beam-search decoder is a competitive choice for both methods. More importantly, we propose a beam-search-based parser that combines both graph-based and transition-based parsing into a single system for training and decoding, showing that it outperforms both the pure graph-based and the pure transition-based parsers. Testing on the English and Chinese Penn Treebank data, the combined system gave state-of-the-art accuracies of 92.1% and 86.2%, respectively.
GoDiS: an accommodating dialogue system
Authors: Staffan Larsson, Peter Ljunglöf, Robin Cooper, Elisabet Engdahl, Stina Ericsson
Venue: Proceedings of the ANLP-NAACL 2000 Workshop on Conversational Systems (2000)

This paper accompanies a demo of the GoDiS system. Work on this system was reported at IJCAI-99 (Bohlin et al., 1999). GoDiS is a prototype dialogue system for information-seeking dialogue, capable of accommodating questions and tasks to enable the user to present information in any desired order, without explicitly naming the dialogue task. GoDiS is implemented using the TRINDIKIT software package, which enables implementation of these behaviours in a compact and natural way.
Knowledge Base Design for Fault Diagnosis Expert System Based on Production Rule
Authors: Chen WenBin, Liu XiaoLing, He ChangJiu, Liu YiJun
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

Based on production rule, the establishment of knowledge base was discussed in this paper. The reticular fault tree in blackboard model was designed. The presentation form of rule conflict was discussed and the arithmetic for conflict detecting and resolution was given. Based on the knowledge base, an aircraft fault diagnosis expert system was realized.
A Novel SeND Based Source Address Validation Mechanism (SAVM-SeND)
Authors: Pingping Lin, Jun Bi
Venue: Proceedings of the 2009 Ninth Annual International Symposium on Applications and the Internet (2009)

SAVM-SeND, a solution to provide source address validation using the SeND protocol, is proposed in this paper. It assumes all the hosts are configured with SeND protocol in IPv6 networks and aims to provide a mechanism for the control of the source addresses spoofing in all of the address assigning circumstances. Besides, it supports each host with multiple interfaces, each interface with multiple MAC addresses, port mobility, and can achieve a host level granularity filtering in the access network. In the end, the evaluation is discussed.
Efficient Heuristic Algorithm for Rapid Custom-Instruction Selection
Authors: Tao Li, Wu Jigang, Siew-Kei Lam, Thambipillai Srikanthan, Xicheng Lu
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

Custom-instruction selection is an essential phase in custom-instruction generation. It determines the most profitable custom instruction candidates for hardware implementation. In this paper, a practical computing model is proposed for the problem of custom-instruction selection that takes into account the hardware area constraint. Based on the new computing model, a novel heuristic algorithm is presented to rapidly generate high quality approximate solutions. The overlapping information of custom-instruction instances is utilized in the algorithm to instruct the selection process. Simulation results show that the proposed heuristic algorithm runs fast even for the large-sized problems. The proposed heuristic algorithm produces high-quality approximate solutions.Experimental results show that the difference between the approximate solutions and the optimal ones is only about 3%.
The Enhancement for Foggy Traffic Image Based on EM Algorithm
Authors: Chen Xianqiao, Wu Qing, Yan Xinping, Chu Xiuming
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

In bad weather, such as foggy, the vision become poor, and this often induce many problems for traffic safety. So it is a hot research subject how to improve the vision ability for bad weather in traffic, and there are many achievements have been made. Among these the single scale Retinex algorithm is a common used method, which was proposed by Land. According this theory, any obtained image can be divided into two images: illumination image and object reflected image. If the illumination can be estimated accurately, the high quality enhanced image (reflected image) will be obtained easily. In this paper, one efficient method (EFTI-EM) for illumination was proposed, which is used to estimate the illumination by using sky area in a foggy traffic image and to get sky area is based on EM algorithm. By setting a considerable number of tests, satisfactory results have been achieved.
The Effect of Multimodal Feedback Presented via a Touch Screen on the Performance of Older Adults
Authors: Ju-Hwan Lee, Ellen Poliakoff, Charles Spence
Venue: Proceedings of the 4th International Conference on Haptic and Audio Interaction Design (2009)

Many IT devices --- such as mobile phones and PDAs --- have recently started to incorporate easy-to-use touch screens. There is an associated need for more effective user interfaces for touch screen devices that have a small screen area. One attempt to make such devices more effective and/or easy to use has come through the introduction of multimodal feedback from two or more sensory modalities. Multimodal feedback might provide even larger benefits to older adults who are often unfamiliar with recent developments in electronic devices, and may be suffering from the age-related degeneration of both cognitive and motor processes. Therefore, the beneficial effects associated with the use of multimodal feedback might be expected to be larger for older adults in perceptually and/or cognitively demanding situations. In the present study, we examined the potential benefits associated with the provision of multimodal feedback via a touch screen on older adults' performance in a demanding dual-task situation. We compared unimodal (visual) feedback with various combinations of multimodal (bimodal and trimodal) feedback. We also investigated the subjective difficulty of the task as a function of the type of feedback provided in order to evaluate qualitative usability issues. Overall, the results demonstrate that the presentation of multimodal feedback with auditory signals via a touch screen device results in enhanced performance and subjective benefits for older adults.
Supporting Uncertainty in Indexing and Querying of Moving Objects in Networks Databases
Authors: Song Guangjun, Hao Zhong-xiao, Wang Lijie
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

In order to get more accurate movement information of moving objects, and to capture the temporal trajectory of the spatial uncertainty, This article describes the uncertain trajectory model of the moving objects in the road networks databases, and extends the structure of the MON-tree index based on the road network. The uncertain geometry between two sampling points is divided into pieces, which are stored into the uncertain area list according to time sorting. To enable them to effectively support the uncertainty of moving objects in the road network, and the probabilistic query of the uncertain region of the moving objects trajectory is carried out on this basis of them. The experiment shows that the index structure as well as the probabilistic query with a better performance and higher accuracy inquiries
Being bored? Recognising natural interest by extensive audiovisual integration for real-life application
Authors: Björn Schuller, Ronald Müller, Florian Eyben, Jürgen Gast, Benedikt Hörnler, Martin Wöllmer, Gerhard Rigoll, Anja Höthker, Hitoshi Konosu
Venue: Image and Vision Computing (2009)

Automatic detection of the level of human interest is of high relevance for many technical applications, such as automatic customer care or tutoring systems. However, the recognition of spontaneous interest in natural conversations independently of the subject remains a challenge. Identification of human affective states relying on single modalities only is often impossible, even for humans, since different modalities contain partially disjunctive cues. Multimodal approaches to human affect recognition generally are shown to boost recognition performance, yet are evaluated in restrictive laboratory settings only. Herein we introduce a fully automatic processing combination of Active-Appearance-Model-based facial expression, vision-based eye-activity estimation, acoustic features, linguistic analysis, non-linguistic vocalisations, and temporal context information in an early feature fusion process. We provide detailed subject-independent results for classification and regression of the Level of Interest using Support-Vector Machines on an audiovisual interest corpus (AVIC) consisting of spontaneous, conversational speech demonstrating ''theoretical'' effectiveness of the approach. Further, to evaluate the approach with regards to real-life usability a user-study is conducted for proof of ''practical'' effectiveness.
The Art of Management and the Technology of Knowledge-Based Systems
Authors: Jozef Kelemen, Ivan Polášek
Venue: Proceedings of the 18th International Symposium on Foundations of Intelligent Systems (2009)

Explicit knowledge is successfully transferrable into computers. As the consequence of this, we have today at hand various knowledge and expert systems. The talk provides a short overview of some basic steps towards the actual situation. Then it focuses to the role of management for effective dealing with knowledge, and to the role of special kind of knowledge --- the knowledge of management. A new type of knowledge storing and processing technology, resulting in specific type of knowledge-based systems --- the Knowledge Managing Systems --- is proposed as a computer-based support for activities which form at least some part of the Art of Management.
Optimal Online Learning Procedures for Model-Free Policy Evaluation
Authors: Tsuyoshi Ueno, Shin-Ichi Maeda, Motoaki Kawanabe, Shin Ishii
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II (2009)

In this study, we extend the framework of semiparametric statistical inference introduced recently to reinforcement learning [1] to online learning procedures for policy evaluation. This generalization enables us to investigate statistical properties of value function estimators both by batch and online procedures in a unified way in terms of estimating functions. Furthermore, we propose a novel online learning algorithm with optimal estimating functions which achieve the minimum estimation error. Our theoretical developments are confirmed using a simple chain walk problem.
Autonomous color learning on a mobile robot
Authors: Mohan Sridharan, Peter Stone
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

Color segmentation is a challenging subtask in computer vision. Most popular approaches are computationally expensive, involve an extensive off-line training phase and/or rely on a stationary camera. This paper presents an approach for color learning on-board a legged robot with limited computational and memory resources. A key defining feature of the approach is that it works without any labeled training data. Rather, it trains autonomously from a color-coded model of its environment. The process is fully implemented, completely autonomous, and provides high degree of segmentation accuracy.
What Is Spatio-Temporal Data Warehousing?
Authors: Alejandro Vaisman, Esteban Zimányi
Venue: Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery (2009)

In the last years, extending OLAP (On-Line Analytical Processing) systems with spatial and temporal features has attracted the attention of the GIS (Geographic Information Systems) and database communities. However, there is no a commonly agreed definition of what is a spatio-temporal data warehouse and what functionality such a data warehouse should support. Further, the solutions proposed in the literature vary considerably in the kind of data that can be represented as well as the kind of queries that can be expressed. In this paper we present a conceptual framework for defining spatio-temporal data warehouses using an extensible data type system. We also define a taxonomy of different classes of queries of increasing expressive power, and show how to express such queries using an extension of the tuple relational calculus with aggregated functions.
Semi Supervised Image Spam Hunter: A Regularized Discriminant EM Approach
Authors: Yan Gao, Ming Yang, Alok Choudhary
Venue: Proceedings of the 5th International Conference on Advanced Data Mining and Applications (2009)

Image spam is a new trend in the family of email spams. The new image spams employ a variety of image processing technologies to create random noises. In this paper, we propose a semi-supervised approach, regularized discriminant EM algorithm (RDEM), to detect image spam emails, which leverages small amount of labeled data and large amount of unlabeled data for identifying spams and training a classification model simultaneously. Compared with fully supervised learning algorithms, the semi-supervised learning algorithm is more suitedin adversary classification problems, because the spammers are actively protecting their work by constantly making changes to circumvent the spam detection. It makes the cost too high for fully supervised learning to frequently collect sufficient labeled data for training. Experimental results demonstrate that our approach achieves 91.66% high detection rate with less than 2.96% false positive rate, meanwhile it significantly reduces the labeling cost.
Instant Action Recognition
Authors: Thomas Mauthner, Peter M. Roth, Horst Bischof
Venue: Proceedings of the 16th Scandinavian Conference on Image Analysis (2009)

In this paper, we present an efficient system for action recognition from very short sequences. For action recognition typically appearance and/or motion information of an action is analyzed using a large number of frames. This is a limitation if very fast actions (e.g., in sport analysis) have to be analyzed. To overcome this limitation, we propose a method that uses a single-frame representation for actions based on appearance and motion information. In particular, we estimate Histograms of Oriented Gradients (HOGs) for the current frame as well as for the corresponding dense flow field. The thus obtained descriptors are efficiently represented by the coefficients of a Non-negative Matrix Factorization (NMF). Actions are classified using an one-vs-all Support Vector Machine. Since the flow can be estimated from two frames, in the evaluation stage only two consecutive frames are required for the action analysis. Both, the optical flow as well as the HOGs, can be computed very efficiently. In the experiments, we compare the proposed approach to state-of-the-art methods and show that it yields competitive results. In addition, we demonstrate action recognition for real-world beach-volleyball sequences.
Measuring classifier performance: a coherent alternative to the area under the ROC curve
Authors: David J. Hand
Venue: Machine Learning (2009)

The area under the ROC curve (AUC) is a very widely used measure of performance for classification and diagnostic rules. It has the appealing property of being objective, requiring no subjective input from the user. On the other hand, the AUC has disadvantages, some of which are well known. For example, the AUC can give potentially misleading results if ROC curves cross. However, the AUC also has a much more serious deficiency, and one which appears not to have been previously recognised. This is that it is fundamentally incoherent in terms of misclassification costs: the AUC uses different misclassification cost distributions for different classifiers. This means that using the AUC is equivalent to using different metrics to evaluate different classification rules. It is equivalent to saying that, using one classifier, misclassifying a class 1 point is p times as serious as misclassifying a class 0 point, but, using another classifier, misclassifying a class 1 point is P times as serious, where p¿P. This is nonsensical because the relative severities of different kinds of misclassifications of individual points is a property of the problem, not the classifiers which happen to have been chosen. This property is explored in detail, and a simple valid alternative to the AUC is proposed.
Computing Isophotes on Free-Form Surfaces Based on Support Function Approximation
Authors: M. Aigner, L. Gonzalez-Vega, B. Jüttler, M. L. Sampoli
Venue: Proceedings of the 13th IMA International Conference on Mathematics of Surfaces XIII (2009)

The support function of a free-form-surface is closely related to the implicit equation of the dual surface, and the process of computing both the dual surface and the support function can be seen as dual implicitization. The support function can be used to parameterize a surface by its inverse Gauss map. This map makes it relatively simple to study isophotes (which are simply images of spherical circles) and offset surfaces (which are obtained by adding the offsetting distance to the support function).We present several classes of surfaces which admit a particularly simple computation of the dual surfaces and of the support function. These include quadratic polynomial surfaces, ruled surfaces with direction vectors of low degree and polynomial translational surfaces of bidegree (3,2).In addition, we use a quasi-interpolation scheme for bivariate quadratic splines over criss-cross triangulations in order to formulate a method for approximating the support function. The inverse Gauss maps of the bivariate quadratic spline surfaces are computed and used for approximate isophote computation. The approximation order of the isophote approximation is shown to be 2.
A memory-based approach to the treatment of serial verb construction in combinatory categorial grammar
Authors: Prachya Boonkwan
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop (2009)

CCG, one of the most prominent grammar frameworks, efficiently deals with deletion under coordination in natural languages. However, when we expand our attention to more analytic languages whose degree of pro-dropping is more free, CCG's decomposition rule for dealing with gapping becomes incapable of parsing some patterns of intra-sentential ellipses in serial verb construction. Moreover, the decomposition rule might also lead us to over-generation problem. In this paper the composition rule is replaced by the use of memory mechanism, called CCG-MM. Fillers can be memorized and gaps can be induced from an input sentence in functional application rules, while fillers and gaps are associated in coordination and serialization. Multimodal slashes, which allow or ban memory operations, are utilized for ease of resource management. As a result, CCG-MM is more powerful than canonical CCG, but its generative power can be bounded by partially linear indexed grammar.
Adopting Virtual Characters in Virtual Systems from the Perspective of Communication Studies
Authors: Peiren Shao, Weimin Liao, Zhigeng Pan
Venue: Transactions on Edutainment II (2009)

Virtual characters can play important role in virtual systems because it can enhance mass communication effects via manners of interpersonal communication by well representing the information as well as improving the general publicity. This paper examines the categories of virtual characters by studying the story genres and identifies the potential resources for creating new virtual characters: the traditional and contemporary cultural resources. Creating successful virtual characters not only relates with the cultural identity, which is rooted in the rich cultural heritage resources, but also relies on the advanced technological realization. As a practical example in this project, the discussion about body modeling method shows the technical complexity and feasibility. For future research, better understanding the mechanism of human communication and learning from humanistic disciplines will fundamentally improve the quality of designing virtual characters.