ppxscal/embedding_network huggingface dataset:
A Learning Method of Detecting Anomalous Pedestrian
Authors: Yue Liu, Jun Zhang, Zhijing Liu
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

Abnormal behavior detecting is one of the hottest but most difficult subjects in Monitoring System. It is hard to define "abnormal" in different scenarios. In this paper firstly the classification of motion is conducted, and then conclusions are made under specific circumstances. In order to indicate a pedestrian's movements, a complex number notation based on centroid is proposed. And according to the different sorts of movements, a set of standard image contours are made. Different behavior matrices based on spatio-temporal are acquired through Hidden Markov Models (HMM). A Procrustes shape analysis method is presented in order to get the similarity degree of two contours. Finally Fuzzy Associative Memory (FAM) is proposed to infer behavior classification of a walker. Thus anomalous pedestrians can be detected in the given condition. FAM can detect irregularities and implement initiative analysis of body behavior.
CoCoME Jury Evaluation and Conclusion
Authors: Manfred Broy, Johannes Siedersleben, Clemens Szyperski
Venue: The Common Component Modeling Example: Comparing Software Component Models (2007)

The CoCoME Jury attended the two-day seminar with presentations from all participating teams. The jury provided individual feedback to each of the teams. This chapter is an attempt at both organizing the contributions into groups of related themes and summarizing some of the more salient feedback. The jury concludes with a few observations about the CoCoME contest as such and its overall outcome.
Prototype Proliferation in the Growing Neural Gas Algorithm
Authors: Héctor F. Satizábal, Andres Pérez-Uribe, Marco Tomassini
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

Growing Neural Gas is an incremental vector quantization algorithm with the capabilities of topology-preserving and distribution-matching. Distribution matching can produce overpopulation of prototypes in zones with high density of data. In order to tackle this drawback, we introduce some modifications to the original Growing Neural Gas algorithm by adding three new parameters, one of them controlling the distribution of the codebook and the other two controlling the quantization error and the amount of units in the network. The resulting learning algorithm is capable of efficiently quantizing datasets presenting high and low density regions while solving the prototype proliferation problem.
The Research on the Influence Factors for Fitness between Technology Strategy and Corporate Strategy
Authors: Chen Jin, Yao Wei, He Yubing, JinXin
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

Technology itself doesn’t guarantee a success in financial performance. The fitness between technology strategy and corporate strategy ensures the successful deployment of a company’s technological capability and enhances the company’s financial performance. Based on an investigation on 121 Chinese technology-based firms through questionnaires and further data analysis, it reveals that corporate environment, top management team, technology resources, internal convergence ability of firms have a positive relation with the fitness between technology strategy and corporate strategy. Moreover, technology background, technology preference and the diversity of top management team are also proven to be the key factors.
Multi-objective Feature Selection with NSGA II
Authors: Tarek M. Hamdani, Jin-Myung Won, Adel M. Alimi, Fakhri Karray
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

This paper deals with the multi-objective definition of the feature selection problem for different pattern recognition domains. We use NSGA II the latest multi-objective algorithm developed for resolving problems of multi-objective aspects with more accuracy and a high convergence speed. We define the feature selection as a problem including two competing objectives and we try to find a set of optimal solutions so called Pareto-optimal solutions instead of a single optimal solution. The two competing objectives are the minimization of both the number of used features and the classification error using 1-NN classifier. We apply our method to five databases selected from the UCI repository and we report the results on these databases. We present the convergence of the NSGA II on different problems and discuss the behavior of NSGA II on these different contexts.
Analyzing Software Component Graphs of Grid Middleware: Hint to Performance Improvement
Authors: Pingpeng Yuan, Hai Jin, Kang Deng, Qingcha Chen
Venue: Proceedings of the 8th international conference on Algorithms and Architectures for Parallel Processing (2008)

Grid middleware is a kind of important service management tool and is composed of different interaction units. The units of a grid middleware do not interact in random ways and are very well connected. As shown in this paper, irrespective of the specific features of each grid middleware analyzed, the final outcome of grid middleware is a small world, hierarchical component diagram with well-defined statistical properties. These measurements of network are largely independent of the particular the application and indicated key execution path or key elements. Therefore, analyzing grid middleware structure can show a roadmap to tune performance of grid middleware. Based on analysis of those diagrams, the key components of grid middleware are outlined.
Combinatorial bounds via measure and conquer: Bounding minimal dominating sets and applications
Authors: Fedor V. Fomin, Fabrizio Grandoni, Artem V. Pyatkin, Alexey A. Stepanov
Venue: ACM Transactions on Algorithms (TALG) (2008)

We provide an algorithm listing all minimal dominating sets of a graph on n vertices in time O(1.7159n). This result can be seen as an algorithmic proof of the fact that the number of minimal dominating sets in a graph on n vertices is at most 1.7159n, thus improving on the trivial O(2n/&sqrt;n) bound. Our result makes use of the measure-and-conquer technique which was recently developed in the area of exact algorithms. Based on this result, we derive an O(2.8718n) algorithm for the domatic number problem.
Empirical Analysis of a Distributed Software Development Project
Authors: Przemyslaw Cichocki, Alessandro Maccari
Venue: Balancing Agility and Formalism in Software Engineering: Second IFIP TC 2 Central and East European Conference on Software Engineering Techniques, CEE-SET 2007, Poznan, Poland, October 10-12, 2007, Revised Selected Papers (2008)

In spite of the abundant research that promotes different methods for software development, and the current method war amidst agile and disciplined methods, little research is done to actually figure out whether real projects, carried out in industrial environments, benefit more from either approach. This paper analyses a real project team's opinions and feelings about project management techniques, software development methods and cultural difference in a multi-site project where traveling and communication are made difficult by restrictions and low-quality infrastructure. The different sites also worked in different time zones and with different working week patterns. The project team members almost unanimously indicated that the presence of a local team leader with authority and flexibility to cover a role that is not exactly as assigned in the beginning, is key factor for the success of this sort of projects. While there was no consensus on whether the project was agile or disciplined, evidence seems to hint towards a more disciplined approach, probably as a compensation for the higher degree of uncertainty that derives from the distributed setup. While the findings of the case study cannot be extended to other organizations without caution, we do infer a number of conclusions on cultural differences, project management tools and techniques.
A Neural Network Based Cascaded Classifier for Face Detection in Color Images with Complex Background
Authors: Kamal Nasrollahi, Mohammad Rahmati, Thomas B. Moeslund
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

When utilizing neural networks as a classifier in face detection systems there are two important problems which should be solved: 1. High computations between the network layers and 2. Adjusting the topology of the network. The proposed system in this paper uses a genetic algorithm to directly solve the second problem and a fuzzy inference engine as a pre-classifier to indirectly deal with the first problem. After computing a small number of reliable and easy to extract features from skin like regions, in the pre-classification step, a set of flexible rules are applied by a fuzzy inference engine. The accepted regions are fed into a neural network for final decision making. Using this combination of classifiers has established an acceptable tradeoff between the computation and the missed faces while the rate of correct detection is acceptably high.
Particle Filter with Multiple Motion Models for Object Tracking in Diving Video Sequences
Authors: Beiji Zou, Xiaoning Peng, Liqin Han
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

This paper addresses the problem of object tracking in diving video sequences by particle filter. Because the diversity of motions in diving video sequences such as bouncing on the springboard, somersaulting in the air increases the difficulty to construct particle motion model, this paper presents an object tracking method in diving video sequences by particle filter with multiple motion models. In this method, video paragraphing based on Hough transform technique and the knowledge of critical frame is proposed to divide a whole diving video sequences into several sub-sequences, and construct a particle motion model for each sub-sequences. The particles are predicted by multiple motion models to adjust to athlete motions in diving video sequences. Experiments demonstrate that the object tracking method is efficient in diving video sequences.
Implementing the LZ-index: Theory versus practice
Authors: Gonzalo Navarro
Venue: Journal of Experimental Algorithmics (JEA) (2009)

The LZ-index is a theoretical proposal of a lightweight data structure for text indexing, based on the Ziv-Lempel trie. If a text of u characters over an alphabet of size &sigma; is compressible to n symbols using the LZ78 algorithm, then the LZ-index takes 4n log2 n (1+o(1)) bits of space (that is, 4 times the entropy of the text) and reports the R occurrences of a pattern of length m in worst case time O(m3 log &sigma; + (m + R)log n). In this paper we face the challenge of obtaining a practical implementation of the LZ-index, which is not at all straightforward from the theoretical proposal. We end up with a prototype that takes the promised space and has average search time O(&sigma; m log u + &sqrt;uR). This prototype is shown to be faster than other competing approaches when we take into account the time to report the positions or text contexts of the occurrences found. We show in detail the process of implementing the index, which involves interesting lessons of theory versus practice.
Interactive Simulation of Embolization Coils: Modeling and Experimental Validation
Authors: Jérémie Dequidt, Maud Marchal, Christian Duriez, Erwan Kerien, Stéphane Cotin
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

Coil embolization offers a new approach to treat aneurysms. This medical procedure is namely less invasive than an open-surgery as it relies on the deployment of very thin platinum-based wires within the aneurysm through the arteries. When performed intracranially, this procedure must be particularly accurate and therefore carefully planned and performed by experienced radiologists. A simulator of the coil deployment represents an interesting and helpful tool for the physician by providing information on the coil behavior. In this paper, an original modeling is proposed to obtain interactive and accurate simulations of coil deployment. The model takes into account geometric nonlinearities and uses a shape memory formulation to describe its complex geometry. An experimental validation is performed in a contact-free environment to identify the mechanical properties of the coil and to quantitatively compare the simulation with real data. Computational performances are also measured to insure an interactive simulation.
Proactive Authoring for Interactive Drama: An Author's Assistant
Authors: Mei Si, Stacy C. Marsella, David V. Pynadath
Venue: Proceedings of the 7th international conference on Intelligent Virtual Agents (2007)

Interactive drama allows people to participate actively in a dynamically unfolding story, by playing a character or by exerting directorial control. One of the central challenges faced in the design of interactive dramas is how to ensure that the author's goals for the user's narrative experience are achieved in the face of the user's actions in the story. This challenge is especially significant when a variety of users are expected. To address this challenge, we present an extension to Thespian, an authoring and simulating framework for interactive dramas. Each virtual character is controlled by a decision-theoretic goal driven agent. In our previous work on Thespian, we provided a semi-automated authoring approach that allows authors to configure virtual characters' goals through specifying story paths. In this work, we extend Thespian into a more proactive authoring framework to further reduce authoring effort. The approach works by simulating potential users' behaviors, generating corresponding story paths, filtering the generated paths to identify those that seem problematic and prompting the author to verify virtual characters' behaviors in them. The author can correct virtual characters' behaviors by modifying story paths. As new story paths are designed by the author, the system incrementally adjusts virtual characters' configurations to reflect the author's design ideas. Overall, this enables interactive testing and refinement of an interactive drama. The details of this approach will be presented in this paper, followed by preliminary results of applying it in authoring an interactive drama.
Query Dissemination with Predictable Reachability and Energy Usage in Sensor Networks
Authors: Zinaida Benenson, Markus Bestehorn, Erik Buchmann, Felix C. Freiling, Marek Jawurek
Venue: Proceedings of the 7th international conference on Ad-hoc, Mobile and Wireless Networks (2008)

Energy-efficient query dissemination plays an important role for the lifetime of sensor networks. In this work, we consider probabilistic flooding for query dissemination and develop an analytical framework which enables the base station to predict the energy consumed and the nodes reached according to the rebroadcast probability. Furthermore, we devise a topology discovery protocol that collects the structural information required for the framework. Our analysis shows that the energy savings exceed the energy spent to obtain the required information after a small number of query disseminations in realistic settings. We verified our results both with simulations and experiments using the SUN Spot nodes.
Crossover: Online Pests Plaguing the Offline World
Authors: Elias Levy
Venue: IEEE Security and Privacy (2003)

The telecommunications boom, the rise of the Internet, and the rush to connect everything to it could well be seen as one of humanity's milestones, not far removed from that of the invention of the telephone or telegraph. Computer networking, over the Internet in particular, has democratized the publishing of information, made massive amounts of information and services accessible to the general public, and enabled new business models. But everything has a dark side. Along with its benefits, the Internet has brought about such things as cybercrime, computer worms, online fraud, spam, and denial-of-service attacks, among other online unpleasantness.
Autonomous Learning of Ball Trapping in the Four-Legged Robot League
Authors: Hayato Kobayashi, Tsugutoyo Osaki, Eric Williams, Akira Ishino, Ayumi Shinohara
Venue: RoboCup 2006: Robot Soccer World Cup X (2006)

This paper describes an autonomous learning method used with real robots in order to acquire ball trapping skills in the four-legged robot league. These skills involve stopping and controlling an oncoming ball and are essential to passing a ball to each other. We first prepare some training equipment and then experiment with only one robot. The robot can use our method to acquire these necessary skills on its own, much in the same way that a human practicing against a wall can learn the proper movements and actions of soccer on his/her own. We also experiment with two robots, and our findings suggest that robots communicating between each other can learn more rapidly than those without any communication.
Deciding Innermost Loops
Authors: René Thiemann, Jürgen Giesl, Peter Schneider-Kamp
Venue: Proceedings of the 19th international conference on Rewriting Techniques and Applications (2008)

We present the first method to disprove innermost termination of term rewrite systems automatically. To this end, we first develop a suitable notion of an innermost loop. Second, we show how to detect innermost loops: One can start with any technique amenable to find loops. Then our novel procedure can be applied to decide whether a given loop is an innermost loop. We implemented and successfully evaluated our method in the termination prover AProVE.
A novel fingerprint matching and classification schema based on nested convex polygons
Authors: Hamzeh Khazaei, Ali Mohades
Venue: Proceedings of the American Conference on Applied Mathematics (2008)

In this paper, we present a new approach to fingerprint matching and classification using an onion layer algorithm of computational geometry. In order to extract valid minutiae we apply some image processing steps on input fingerprint. Using an Onion layer algorithm we construct nested convex polygons of minutiae, then based on polygons property, we perform matching and classification of fingerprints; we use the most interior polygon in order to calculate the rigid transformations parameters and perform local matching, consequently, global matching applied. This method rejects non matching fingerprint in local matching and avoid time consuming global matching steps. We develop new classification scheme of fingerprints based on this approach. Unlike classic classification of fingerprints, this novel approach distributed fingerprints in classes equally, and none of image processing techniques are required for this classification. This normal distribution of fingerprints in different classes has great effect on identification time.
A Minimum Zone Method for Evaluating Straightness Errors Using PSO Algorithm
Authors: Ke Zhang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Straightness error is the commonest one of form errors. In this paper, an intelligent evaluation method for straightness errors is provided. According to characteristics of straightness error evaluation, Particle Swarm Optimization (PSO) is proposed to evaluate the minimum zone error. The evolutional optimum model and the calculation process for using the PSO to evaluate minimum zone error are introduced in detail. Compared with conventional optimum methods such as simplex search and Powell method, PSO algorithm can find the global optimal solution, and the precision of calculating result is very good. Compared to genetic algorithms (GA), PSO is easy to implement and there are few parameters to adjust. Finally, a numerical example is carried out. The control experiment results evaluated by using different method such as the least square, simplex search, Powell optimum methods, Simulated Annealing Algorithms (SAA), GA and PSO, indicate that the proposed method does provide better accuracy on straightness error evaluation, and it has fast convergent speed as well as using computer.
A More Natural Way to Construct Identity-Based Identification Schemes
Authors: Guomin Yang, Jing Chen, Duncan S. Wong, Xiaotie Deng, Dongsheng Wang
Venue: Proceedings of the 5th international conference on Applied Cryptography and Network Security (2007)

Constructing identification schemes is one of the fundamental problems in cryptography, and is very useful in practice. An identity-based identification (IBI) scheme allows a prover to identify itself to a public verifier who knows only the claimed identity of the prover and some common information. In this paper, we propose a simple and efficient framework for constructing IBI schemes. Unlike some related framework which constructs IBI schemes from some standard identification schemes, our framework is based on some more fundamental assumptions on intractable problems. Depending on the features of the underlying intractable problems presumed in our framework, we can derive IBI schemes secure against passive, active and concurrent adversaries. We show that the framework can capture a large class of schemes currently proposed, and also has the potential to cover many newly constructed schemes. As an example, based on the Katz-Wang standard signature scheme, we propose a new IBI scheme that is secure against active adversaries in a concurrent manner. It can be seen that our framework also help simplify the security proofs for new IBI schemes. Finally, and of independent interest, we define a new notion for proof systems called Witness Dualism. This notion is weaker than that of witness indistinguishable and we show that it is enough for constructing an IBI scheme secure against the most powerful type of adversaries defined.
Cascade Jump Controlled Sequence Generator and Pomaranch Stream Cipher
Authors: Cees J. Jansen, Tor Helleseth, Alexander Kholosha
Venue: New Stream Cipher Designs: The eSTREAM Finalists (2008)

Jump registers have been proposed as building blocks for stream ciphers. In this paper, a construction based on these principles is described. The proposed encryption primitive is a synchronous stream cipher accommodating a key of 128 bits and an IV of 64 up to 162 bits, or an 80-bit key and 32 to 108 bit IV. The stream cipher is particularly designed to resist side-channel attacks and can be efficiently implemented in hardware for a wide range of target processes and platforms.
Deep Syntactic Analysis and Rule Based Accentuation in Text-to-Speech Synthesis
Authors: Antti Suni, Martti Vainio
Venue: Proceedings of the 11th international conference on Text, Speech and Dialogue (2008)

With the emergence of the HMM-synthesis paradigm, producing natural, expressive prosody has become viable in speech synthesis. This paper describes the development of rule-based prominence prediction model for Finnish Text-to-Speech system, based on deep syntactic analysis and discourse structure.