ppxscal/embedding_network huggingface dataset:
Block Mechanism of Left-turned Flow at Signal-Controlled Roundabout
Authors: Yu Bai, Kun Xue, Xiaoguang Yang
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 03 (2009)

The “Left-turn with two stops” control method, being an organically combined method between signal control and roundabouts has been greatly applied in some of the Chinese cities, resulting in certain traffic and social efficiency. In the meanwhile, because of the short time in putting forward the theory, it appears, to some extent, immature up till now, especially that the essential problem concerning the block mechanism of signal-controlled roundabout influences the left-turned flow still needs further discussion from the point of theory.It is from the above background that this text gives it good study to the block types and emission regularities resulted from the left-turned vehicles at signal-controlled roundabouts, trying to make a quantizing calculation about such retardation in which delay is taken as objective function and to obtain the calculative formula for average delay of individual left-turned vehicle at signal-controlled roundabouts.
SemEval-2007 task 08: metonymy resolution at SemEval-2007
Authors: Katja Markert, Malvina Nissim
Venue: Proceedings of the 4th International Workshop on Semantic Evaluations (2007)

We provide an overview of the metonymy resolution shared task organised within SemEval-2007. We describe the problem, the data provided to participants, and the evaluation measures we used to assess performance. We also give an overview of the systems that have taken part in the task, and discuss possible directions for future work.
Company-oriented extractive summarization of financial news
Authors: Katja Filippova, Mihai Surdeanu, Massimiliano Ciaramita, Hugo Zaragoza
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (2009)

The paper presents a multi-document summarization system which builds company-specific summaries from a collection of financial news such that the extracted sentences contain novel and relevant information about the corresponding organization. The user's familiarity with the company's profile is assumed. The goal of such summaries is to provide information useful for the short-term trading of the corresponding company, i.e., to facilitate the inference from news to stock price movement in the next day. We introduce a novel query (i.e., company name) expansion method and a simple unsupervized algorithm for sentence ranking. The system shows promising results in comparison with a competitive baseline.
Polynomial Size Asymmetric Linear Model for SAT
Authors: Sergey Gubin
Venue: Proceedings of the Advances in Electrical and Electronics Engineering - IAENG Special Edition of the World Congress on Engineering and Computer Science 2008 (2008)

Article describes a polynomial time many-one reduction of SAT to a polynomial size asymmetric linear system, where asymmetry means that shape and location of the system's polytope depend on order of clauses in CNF and on order of literals in the clauses.
HMM-Based Defect Localization in Wire Ropes --- A New Approach to Unusual Subsequence Recognition
Authors: Esther-Sabrina Platzer, Josef Nägele, Karl-Heinz Wehking, Joachim Denzler
Venue: Proceedings of the 31st DAGM Symposium on Pattern Recognition (2009)

Automatic visual inspection has become an important application of pattern recognition, as it supports the human in this demanding and often dangerous work. Nevertheless, often missing abnormal or defective samples prohibit a supervised learning of defect models. For this reason, techniques known as one-class classification and novelty- or unusual event detection have arisen in the past years. This paper presents a new strategy to employ Hidden Markov models for defect localization in wire ropes. It is shown, that the Viterbi scores can be used as indicator for unusual subsequences. This prevents a partition of the signal into sufficient small signal windows at cost of the temporal context. Our results outperform recent time-invariant one-class classification approaches and depict a great advance for an automatic visual inspection of wire ropes.
Parallel structured duplicate detection
Authors: Rong Zhou, Eric A. Hansen
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

We describe a novel approach to parallelizing graph search using structured duplicate detection. Structured duplicate detection was originally developed as an approach to external-memory graph search that reduces the number of expensive disk I/O operations needed to check stored nodes for duplicates, by using an abstraction of the search graph to localize memory references. In this paper, we show that this approach can also be used to reduce the number of slow synchronization operations needed in parallel graph search. In addition, we describe several techniques for integrating parallel and external-memory graph search in an efficient way. We demonstrate the effectiveness of these techniques in a graph-search algorithm for domain-independent STRIPS planning.
Ad-Hoc Communication and Localization System for Mobile Robots
Authors: Bernd Neuwinger, Ulf Witkowski, Ulrich Rückert
Venue: Proceedings of the FIRA RoboWorld Congress 2009 on Advances in Robotics (2009)

Robots exploring unknown territory cannot rely on fixed infrastructure for communication and localization purposes. Therefore an ad-hoc communication and localization system is required to provide such facilities. In this paper a solution for a radio based localization system is presented using a 2.4 GHz wireless radio transceiver based on Chirp Spread Spectrum (CSS) modulation, which allows distance measurements by evaluating the signal propagation delay. Using odometry data as additional information source a communication and positioning system is developed fulfilling ad-hoc demands.
Description Population Migration Algorithm Based on Framework of Swarm Intelligence
Authors: Weiwei Zhang, Yongquan Zhou
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 02 (2009)

Population migration algorithm is proposed in recent years, it’s a new search algorithm for global optimization that mainly simulates population transition mechanism, so far, and there was no unified framework to describe this algorithm. This paper describes the population migration algorithm based on a given framework of swarm intelligence, it helps to understand the principles of the population migration algorithm, as well as combination with chaos theory, a chaos population migration algorithm is proposed. Finally, a numerical experiment example indicates that the new algorithm is effective and accuracy.
Tendon Based Full Size Biped Humanoid Robot Walking Platform Design
Authors: Chung-Hsien Kuo, Kuo-Wei Chiou
Venue: Proceedings of the FIRA RoboWorld Congress 2009 on Advances in Robotics (2009)

Actuators and gear trains of most biped humanoid robots are divergently allocated on the links of two legs. Disadvantages of such a mechanical design are complicated wiring of power cord and sensing/ control signal bundles and imprecise kinetics models of mixed link-and-actuator structures. Based on these drawbacks, this paper proposes a tendon-driven mechanism to develop a lower body structure of a full-size biped humanoid robot. The actuators are compacted as an actuator module, and they are placed at a distal site. A 12 degree-of-freedom mechanical structure is proposed with 100 cm in height and 45 kg in weight. The gait planning module is simulated and evaluated using the Matlab software. At the same time, an ARM7 based controller is developed to automatically generate walking patterns as well as to control the motors. Finally, a tendon-driven biped humanoid robot prototype is realized for practical waling control in the future.
A Algorithm for the Nonlinear Complementarity Problem in Contact Mechanics Modeling
Authors: Hongchun Sun
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

In this paper, we consider nonlinear complementarity problem in contact mechanics modeling (NCP). To solve the problem, we first establish a global error bound for NCP, and then propose a new type of solution method to solve the NCP based on the error bound estimation. The global convergence is also established, and the given numerical experiments shows the efficiency of the method.
Interactive knowledge validation and query refinement in CBR
Authors: Monica H. Ou, Geoff A. W. West, Mihai Lazarescu, Chris Clay
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 1 (2005)

In most case-based reasoning (CBR) systems there has been little research done on validating new knowledge, specifically on how previous knowledge differs from current knowledge as a result of conceptual change. This paper proposes two methods that enable the domain expert, who is nonexpert in artificial intelligence (AI), to interactively supervise the knowledge validation process in a CBR system, and to enable dynamic updating of the system, to provide the best diagnostic questions. The first method is based on formal concept analysis which involves a graphical representation and comparison of the concepts, and a summary description highlighting the conceptual differences. We propose a dissimilarity metric for measuring the degree of variation between the previous and current concepts when a new case is added to the knowledge base. The second method involves determining unexpected classification-based association rules to form critical questions as the knowledge base gets updated.
Constructing Interpretable Genetic Fuzzy Rule-Based System for Breast Cancer Diagnostic
Authors: Kavan Sedighiani, SeyedSasan HashemiKhabir
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

This paper shows how a subset of features can be selected for designing interpretable fuzzy rule-based system. This method consists of two phases: feature subset selection based on Michigan Learning approach and Training fuzzy rule-based system using the selected subset from the first phase. First, a number of independent fuzzy rule-based systems are trained using genetic operations, and then the dominated rules of each trained system with the highest fitness values are selected. From the selected rules, a pre-specified number of features are chosen with the highest frequency. In the second phase, a fuzzy rule-based system is trained based on the selected features from the previous phase. Experiments shows the two-phase method feature reduction based on the “collective thought” can achieve promising classification accuracy and performance in Breast Cancer Diagnostic Wisconsin data set.
Decision tree grafting
Authors: Geoffrey I. Webb
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

This paper extends recent work on decision tree grafting. Grafting is an inductive process that adds nodes to inferred decision trees. This process is demonstrated to frequently improve predictive accuracy. Superficial analysis might suggest that decision tree grafting is the direct reverse of pruning. To the contrary, it is argued that the two processes are complementary. This is because, like standard tree growing techniques, pruning uses only local information, whereas grafting uses non-local information. The use of both pruning and grafting in conjunction is demonstrated to provide the best general predictive accuracy over a representative selection of learning tasks.
Towards Coordination Preparedness of Soft-Target Organisation
Authors: Mohammed Shahadat Uddin, Liaquat Hossain
Venue: Proceedings of the 8th International Conference on Electronic Government (2009)

In this paper, we introduce a network enabled coordination model to examine the coordination preparedness of soft-target organisations such as common public access areas including transit hubs, schools, parks, and sports areas. It is apparent that little attention is given in recent research focusing on the use of network analysis as a way to explore coordination preparedness for this type of organisation. In this study, we emphasise this type of soft-target organisation and propose a model to examine the coordination preparedness to any disasters by testing hypothesis related to network relationship and coordination preparedness. We analyse the dataset entitled Preparedness of Large Retail Malls to Prevent and Respond to Terrorist Attack, 2004, which contains a total of 120 completed surveys of security directors of retail malls. The following questions form the basis of this study: What do soft-target organisations need to be better prepared to respond to disaster? How does network relationship between soft-target organisation and emergency agencies affect the coordination preparedness of soft-target organisation for disaster recovery? Which degree of centrality measure needs to be followed to measure network variables in order to analyse the coordination preparedness? Result shows that soft-target organisation with high level of network relationship with other emergency agencies are better prepared to disaster response. Using this result, the preparedness of a soft-target organisation might be judged for successfully participation in an actual emergency.
Priming effects in combinatory categorial grammar
Authors: David Reitter, Julia Hockenmaier, Frank Keller
Venue: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (2006)

This paper presents a corpus-based account of structural priming in human sentence processing, focusing on the role that syntactic representations play in such an account. We estimate the strength of structural priming effects from a corpus of spontaneous spoken dialogue, annotated syntactically with Combinatory Categorial Grammar (CCG) derivations. This methodology allows us to test a range of predictions that CCG makes about priming. In particular, we present evidence for priming between lexical and syntactic categories encoding partially satisfied sub-categorization frames, and we show that priming effects exist both for incremental and normal-form CCG derivations.
Coastline Detection from SAR Images by Level Set Model
Authors: Maria Mercede Cerimele, Luigi Cinque, Rossella Cossu, Roberta Galiffa
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

In this paper we present an innovative and automatic procedure which is used to extract the coastline from SAR (Synthetic Aperture Radar) images by the level set model. This model consists in a PDE (Partial Differential Equation) equation governing the evolution of a curve corresponding to the zero level of a 3D function, called level set function, until the curve reaches the edge of the region to be segmented. A coastline is the boundary between land and sea masses. Detecting the coastline is of fundamental importance when monitoring various natural phenomena such as tides, coastal erosion and the dynamics of glaciers. In this case SAR images show problems which arise from the presence of the speckle noise and of the strong signal deriving from the rough or slight sea. In fact in the case of heavy sea the signal determines an intensity similar to the one of land, making it difficult to distinguish the coastline.
Automated measurements of finger movements in arthritic patients using a wearable data hand glove
Authors: J. Condell, K. Curran, T. Quigley, P. Gardiner, M. McNeill, E. Xie
Venue: Proceedings of the 2009 IEEE International Workshop on Medical Measurements and Applications (2009)

This paper outlines the initial ideas surrounding the development of an accurate hand movement measurement tool. This tool will assist medical clinicians, specifically rheumatologists and orthopeadic hand surgeons, with the accurate measurement of the loss of movement in the human hand. This has many direct applications within medical practice including diagnosis, prognosis and recovery assessment of patients with conditions specific to the hand e.g. to measure how far a patient can close their fingers (with a flare up in arthritis patients may not be able to make a fist). Current measurement techniques available to clinicians are either invasive (x-rays) or rely heavily on manual evaluation such as vision and touch which are dependent on training and experience and results often vary between observers. Measuring tape is commonly used to measure distances e.g. between palm and fingertip which also leads to issues with accuracy. Also patient self questionnaires are often used which introduce interpretation problems.
Risk Analysis of Construction Projects Based on Markov Chain
Authors: Zhang Sujiao
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

Construction projects are plagued by risks and often suffered poor performance as a result. There are a number of risk analysis techniques available to help alleviate this, but commonly practiced static risk analysis approaches fail to fit with the dynamic nature of construction project process. In this paper, a method based on Markov chain model is proposed to analyze both short-term and long-term risks in construction projects. It provides a quantitative method to implement project risk analysis in a dynamic framework without the necessity of having mass of historical data.
A Harmonics Analysis Method Based on Triangular Neural Network
Authors: Xiao Xiuchun, Jiang Xiaohua, Lu Xiaomin, Chen Botao
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

Aiming at fast and effectively evaluating harmonics in the power system, a triangular neural network is constructed, of which the hidden neurons are activated with triangular functions. Based on gradient descent method, the learning rules (i.e., weights-iterative-formula) for the constructed neural network are derived. Then global-convergence of the weights-iterative-formula is proved. As the results, a weights-direct-determination method is achieved, which could obtain the optimal weights of such a neural network in one step by using pseudo-inverse. Furthermore, several numerical tests have been conducted to apply this method to some harmonics models. The simulation results substantiate this method can be used to fast and precisely evaluate the harmonic components.
System concept for an FPGA based real-time capable automotive ECU simulation system
Authors: Oliver Sander, Christoph Roth, Vitali Stuckert, Jürgen Becker
Venue: Proceedings of the 22nd Annual Symposium on Integrated Circuits and System Design: Chip on the Dunes (2009)

During the development of automotive electric/electronic architectures testing is usually accomplished by software based approaches on standard PCs. Simulating many ECUs on a single PC highly influences the bus communication thus biasing the results for performance and latency tests. Based on the commonly used software CANoe we propose a system concept for an FPGA based simulator equipped with a real-time data logger. Due to parallelization the system achieves a much higher accuracy for bus communication compared to a single PC approach. Moreover we address reusability of already existing CANoe models in our system. In this paper the system concept is introduced. We present the different modules and show the major benefits. A system prototype has been implemented to proof the system concept concerning functionality.
A Trust Domain-Based Resource Selection Model for Multi-Agent
Authors: Junfeng Tian, Juan Li
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01 (2009)

Along with the development of e-commerce, the problem of credibility for on-line transaction and exact selection of network resources has become more important. That is because of the anonymity and openness of on-line transactions and the richness of network resources. For this reason, A Trust Domain-Based Resource Selection Model for Multi-Agent (DRSM) is presented. The model divides the network into numbers of trust domains. Each domain has one Domain Agent and several Entity Agents. Through the periodically communication between the agents, the model prevents the information’s inconsistency maintained by different agents. Trust values of service providers (SPs) and consumers are evaluated and updated dynamically after the completion of each transaction, which enables the consumer to receive the response from the agent significantly quicker compared to other reputation-based-trust models where the trust values are computed at the request-time. Because of the diversity of Web services, the model takes the similarity between services and the SPs’ recognition to the services into account, which can not only give trusted services to users but also can choose the best matching services to the users’ request. Finally, the model is illustrated the effectiveness and feasibility according to the experiment.
Study on Application of Model Checking Based on Deconstructing
Authors: Qi Jun-qiao, Qi Yan-ming
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

With the development of Internet age, the steganography solution to Internet QoS is defined not only by the improvement of web browsers, but also by the confirmed need for public-private key pairs. In order to confirm 802.11b’sconstruction, which the significant principles of operating systems was embodied. Our focus in our research was not on whether the foremost "fuzzy" algorithm for the exploration of IPv7 was turing complete, but rather on introducing an analysis of DHTs (Forcing). New distributed archetypes were constructed, through our experiences with forcing and symmetric encryption validate.
Corpus-based anaphora resolution towards antecedent preference
Authors: Michael Paul, Kazuhide Yamamoto, Eiichiro Sumita
Venue: Proceedings of the Workshop on Coreference and its Applications (1999)

In this paper we propose a corpus-based approach to anaphora resolution combining a machine learning method and statistical information. First, a decision tree trained on an annotated corpus determines the coreference relation of a given anaphor and antecedent candidates and is utilized as a filter in order to reduce the number of potential candidates. In the second step, preference selection is achieved by taking into account the frequency information of coreferential and non-referential pairs tagged in the training corpus as well as distance features within the current discourse. Preliminary experiments concerning the resolution of Japanese pronouns in spoken-language dialogs result in a success rate of 80.6%.
Driver Measurement: Methods and Applications
Authors: Shane Mclaughlin, Jonathan Hankey, Thomas Dingus
Venue: Proceedings of the 8th International Conference on Engineering Psychology and Cognitive Ergonomics: Held as Part of HCI International 2009 (2009)

This paper presents an overview of methods used when measuring driver behavior and performance. Simulators, test-track, on-road, field-operational-trials, and naturalisitic methods are described. Useful driver measures are described. Three examples are provided of the application of driver measurement in product design and evaluation.