ppxscal/embedding_network huggingface dataset:
Context Aware Programmable Trackers for the Next Generation Internet
Authors: Pedro Sousa
Venue: Proceedings of the 15th Open European Summer School and IFIP TC6.6 Workshop on The Internet of the Future (2009)

This work introduces and proposes the concept of context aware programmable trackers for the next generation Internet. The proposed solution gives ground for the development of advanced applications based on the P2P paradigm and will foster collaborative efforts among several network entities (e.g. P2P applications and ISPs). The proposed concept of context aware programmable trackers allows that several peer selection strategies might be supported by a P2P tracker entity able to improve the peer selection decisions according with pre-defined objectives and external inputs provided by specific services. The flexible, adaptive and enhanced peer selection semantics that might be achieved by the proposed solution will contribute for devising novel P2P based services and business models for the future Internet.
Detecting Moving Objects in Noisy Radar Data Using a Relational Database
Authors: Andreas Behrend, Rainer Manthey, Gereon Schüller, Monika Wieneke
Venue: Proceedings of the 13th East European Conference on Advances in Databases and Information Systems (2009)

In moving object databases, many authors assume that number and position of objects to be processed are always known in advance. Detecting an unknown moving object and pursuing its movement, however, is usually left to tracking algorithms outside the database in which the sensor data needed is actually stored. In this paper we present a solution to the problem of efficiently detecting targets over sensor data from a radar system based on database techniques. To this end, we implemented the recently developed probabilistic multiple hypothesis tracking approach using materialized SQL views and techniques for their incremental maintenance. We present empirical measurements showing that incremental evaluation techniques are indeed well-suited for efficiently detecting and tracking moving objects from a high-frequency stream of sensor data in this particular context. Additionally, we show how to efficiently simulate the aggregate function product which is fundamental for combining independent probabilistic values but unsupported by the SQL standard, yet.
Trace-Based Coinductive Operational Semantics for While
Authors: Keiko Nakata, Tarmo Uustalu
Venue: Proceedings of the 22nd International Conference on Theorem Proving in Higher Order Logics (2009)

We present four coinductive operational semantics for the While language accounting for both terminating and non-terminating program runs: big-step and small-step relational semantics and big-step and small-step functional semantics. The semantics employ traces (possibly infinite sequences of states) to record the states that program runs go through. The relational semantics relate statement-state pairs to traces, whereas the functional semantics return traces for statement-state pairs. All four semantics are equivalent. We formalize the semantics and their equivalence proofs in the constructive setting of Coq.
A Bloom Filter-Based User Search Method Based on Movement Records for P2P Network
Authors: Toru Shiraki, Yuichi Teranishi, Susumu Takeuchi, Kaname Harumoto, Shojiro Nishio
Venue: Proceedings of the 2009 Ninth Annual International Symposium on Applications and the Internet (2009)

In this paper, we propose a P2P user search method based on movement records that can be automatically obtained by location detection devices. We assume movement records are treated as a sequence of pairs of spot-ID and time and they are stored in a peer for each user. In our proposal, a Bloom Filter is applied to each spotID and time to combine all movement records for one user as a fixed length bit array.To search a user who followed specified course, we propose a AND/OR search method based on Bloom Finger Table (BFT), which extends a routing table of a Chord DHT system to retrieve elements using Bloom Filter.By this method, user searches based on a sequence of locations with or without time can be realized efficiently. Additionally, in order to reduce the number of messages for a user search, we propose a peer-ID assignment for BFT based on user's geographical foothold. The number of messages for a user search can be reduced by this peer-ID assignment since users who visit same places are located closer to each other on the routing table. Evaluation results of simulations show that our proposal reduces the number of messages compared to a naive implementation using existing P2P retrieval method.
A Secure Model for Electronic Contract Enactment, Monitoring and Management
Authors: Xiao Yu, Yueting Chai, Yi Liu
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01 (2009)

With the rapid development of e-commerce, electronic contracts are not secure enough for both businessmen and government, due to the absence of authentication, integrality, non-repudiation, uniform specification and centralized management. We propose that e-contract should involve digital signature as its primary element, and the E-Contract Record Center should be introduced into the management of e-contract. In this paper, we present a model for electronic contract enactment, monitoring and management based on the security view. Additional, a framework for e-contract management is presented with the purpose of regularizing the e-commerce market, protecting businessmen’s right and interests, and facilitating governmental monitoring of the e-commerce market, where we define a lifecycle of e-contract and recounted the establishment process of e-contract. Finally, we present implement architecture for the model and framework given above, which give the service and module design of two systems: e-contract system and ECRC system.
Fluxplayer: a successful general game player
Authors: Stephan Schiffel, Michael Thielscher
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

General Game Playing (GGP) is the art of designing programs that are capable of playing previously unknown games of a wide variety by being told nothing but the rules of the game. This is in contrast to traditional computer game players like Deep Blue, which are designed for a particular game and can't adapt automatically to modifications of the rules, let alone play completely different games. General Game Playing is intended to foster the development of integrated cognitive information processing technology. In this article we present an approach to General Game Playing using a novel way of automatically constructing a position evaluation function from a formal game description. Our system is being tested with a wide range of different games. Most notably, it is the winner of the AAAI GGP Competition 2006.
Cryptanalysis of C2
Authors: Julia Borghoff, Lars R. Knudsen, Gregor Leander, Krystian Matusiewicz
Venue: Proceedings of the 29th Annual International Cryptology Conference on Advances in Cryptology (2009)

We present several attacks on the block cipher C2, which is used for encrypting DVD Audio discs and Secure Digital cards. C2 has a 56 bit key and a secret 8 to 8 bit S-box. We show that if the attacker is allowed to choose the key, the S-box can be recovered in 224 C2 encryptions. Attacking the 56 bit key for a known S-box can be done in complexity 248. Finally, a C2 implementation with a 8 to 8 bit secret S-box (equivalent to 2048 secret bits) and a 56 bit secret key can be attacked in 253.5 C2 encryptions on average.
On Generating Independent Random Strings
Authors: Marius Zimand
Venue: Proceedings of the 5th Conference on Computability in Europe: Mathematical Theory and Computational Practice (2009)

It is shown that from two strings that are partially random and independent (in the sense of Kolmogorov complexity) it is possible to effectively construct polynomially many strings that are random and pairwise independent. If the two initial strings are random, then the above task can be performed in polynomial time. It is also possible to construct in polynomial time a random string, from two strings that have constant randomness rate.
TinyBee: Mobile-Agent-Based Data Gathering System in Wireless Sensor Networks
Authors: Kaoru Ota, Mianxiong Dong, Xiaolin Li
Venue: Proceedings of the 2009 IEEE International Conference on Networking, Architecture, and Storage (2009)

This paper proposes a mobile-agent-based data gathering system (called TinyBee) in wireless sensor networks. Most existing mobile-agent-based systems consider only static sinks/servers. In this paper, we consider both mobile servers and lightweight mobile agents. We aim to design a data gathering system using a special kind of mobile agent called TinyBee to collect data all over a network. TinyBee migrates from node to node after being dispatched from a mobile server in order to collect data so that physical movement of mobile servers is greatly reduced. Mobile-agent-based approaches outperform traditional client/server paradigms in terms of execution time and power consumption. Extensive simulation results demonstrate that our proposed schemes achieve significant performance gains.
A novel kernel-based maximum a posteriori classification method
Authors: Zenglin Xu, Kaizhu Huang, Jianke Zhu, Irwin King, Michael R. Lyu
Venue: Neural Networks (2009)

Kernel methods have been widely used in pattern recognition. Many kernel classifiers such as Support Vector Machines (SVM) assume that data can be separated by a hyperplane in the kernel-induced feature space. These methods do not consider the data distribution and are difficult to output the probabilities or confidences for classification. This paper proposes a novel Kernel-based Maximum A Posteriori (KMAP) classification method, which makes a Gaussian distribution assumption instead of a linear separable assumption in the feature space. Robust methods are further proposed to estimate the probability densities, and the kernel trick is utilized to calculate our model. The model is theoretically and empirically important in the sense that: (1) it presents a more generalized classification model than other kernel-based algorithms, e.g., Kernel Fisher Discriminant Analysis (KFDA); (2) it can output probability or confidence for classification, therefore providing potential for reasoning under uncertainty; and (3) multi-way classification is as straightforward as binary classification in this model, because only probability calculation is involved and no one-against-one or one-against-others voting is needed. Moreover, we conduct an extensive experimental comparison with state-of-the-art classification methods, such as SVM and KFDA, on both eight UCI benchmark data sets and three face data sets. The results demonstrate that KMAP achieves very promising performance against other models.
Avoiding repetition in generated text
Authors: Mary Ellen Foster, Michael White
Venue: Proceedings of the Eleventh European Workshop on Natural Language Generation (2007)

We investigate two methods for enhancing variation in the output of a stochastic surface realiser: choosing from among the highest-scoring realisation candidates instead of taking the single highest-scoring result (&epsilon;-best sampling), and penalising the words from earlier sentences in a discourse when generating later ones (anti-repetition scoring). In a human evaluation study, subjects were asked to compare texts generated with and without the variation enhancements. Strikingly, subjects judged the texts generated using these two methods to be better written and less repetitive than the texts generated with optimal n-gram scoring; at the same time, no significant difference in understandability was found between the two versions. In analysing the two methods, we show that the simpler &epsilon;-best sampling method is considerably more prone to introducing dispreferred variants into the output, indicating that best results can be obtained using anti repetition scoring with strict or no &epsilon;-best sampling.
Poster abstract: IP-based testbed for herd monitoring
Authors: Anthony Schoofs, Charles Daymand, Robert Sugar, Ulrich Mueller, Andreas Lachenmann, Syed M. Kamran, Alain Gefflaut, Lasse Thiem, Mario Schuster
Venue: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks (2009)

An approach to monitoring herd health is to utilize IPbased services and applications, to process and communicate data from sensors attached to the animals to a remote monitoring station. This paper presents a testbed that will serve as a framework for the development of IP-based herd monitoring.
Design of communication in multimodal web interfaces
Authors: Americo Talarico Neto, Renata Pontin de Mattos Fortes, Alessandro Rubim Assis, Júnia Coutinho Anacleto
Venue: Proceedings of the 27th ACM international conference on Design of communication (2009)

In this paper we present our considerations for the design, development and evaluation of Web multimodal interfaces using as example the analysis and the results of three Case Studies. Two usability methods were applied in these Case Studies as part of our approach for Web multimodal interfaces design. The objective is to smooth the progress of the design activities provided by the Multimodal Web Approach (MMWA) recovering Design Rationale from previous projects and improving the usability and user experience in the multimodal interaction. From the experience got performing three case studies with the MMWA, we derive a general framework for design of communication in Web Multimodal Interfaces.
High performance TaYOx-based MIM capacitors
Authors: C. Mahata, M. K. Bera, M. K. Hota, T. Das, S. Mallik, B. Majhi, S. Verma, P. K. Bose, C. K. Maiti
Venue: Microelectronic Engineering (2009)

TaYO"x-based metal-insulator-metal (MIM) capacitors with excellent electrical properties have been fabricated. Ultra-thin TaYO"x films in the thickness range of 15-30nm (EOT~2.4-4.7nm) were deposited on Au/SiO"2 (100nm)/Si (100) structures by rf-magnetron co-sputtering of Ta"2O"5 and Y"2O"3 targets. TaYO"x layers were characterized by X-ray photoelectron spectroscopy (XPS), energy dispersive X-ray (EDX) and X-ray diffraction (XRD) to examine the composition and crystallinity. An atomic percentage of Ta:Y=58.32:41.67 was confirmed from the EDX analysis while XRD revealed an amorphous phase (up to 500^oC) during rapid thermal annealing. Besides, a high capacitance density of ~3.7-5.4fF/@mm^2 at 10kHz (@e"r~21), a low value of VCC (voltage coefficients of capacitance, @a and @b) have been achieved. Also, a highly stable temperature coefficient of capacitance, TCC has been obtained. Capacitance degradation phenomena in TaYO"x-based MIM capacitors under constant current stressing (CCS at 20nA) have been studied. It is observed that degradation depends strongly on the dielectric thickness and a dielectric breakdown voltage of 3-5MV/cm was found for TaYO"x films. The maximum energy storage density was estimated to be ~5.69J/cm^3. Post deposition annealing (PDA) in O"2 ambient at 400^oC has been performed and further improvement in device reliability and electrical performances has been achieved.
A Kind of Visual Cryptography Scheme for Color Images Based on Halftone Technique
Authors: Wei Qiao, Hongdong Yin, Huaqing Liang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

This paper proposes a new secret visual cryptography scheme for color images based on halftone technique. Firstly, a chromatic image is decomposed into three monochromatic images in tones of cyan, magenta and yellow. Secondly, these three images are transformed into binary images by halftone technique. Finally, the traditional binary secret sharing scheme is used to get the sharing images. This scheme provides a more efficient way to hide natural images in different shares. Furthermore, the size of the shares does not vary when the number of colors appearing in the secret image differs.
Enhanced Industrial Maintenance Work Task Planning by Using Virtual Engineering Tools and Haptic User Interfaces
Authors: Simo-Pekka Leino, Salla Lind, Matthieu Poyade, Sauli Kiviranta, Petteri Multanen, Arcadio Reyes-Lecuona, Ari Mäkiranta, Ali Muhammad
Venue: Proceedings of the 3rd International Conference on Virtual and Mixed Reality: Held as Part of HCI International 2009 (2009)

Good maintainability is an essential feature for machines and processes in industry. It promotes, among others, maintenance safety, post-maintenance reliability and cost-effective maintenance by ensuring quick and easy operation and short downtime. Virtual engineering tools provide an effective way for maintainability design already during the design phase. Machine designers may not consider maintenance tasks systematically, which can leave important task details open. The missing detail planning can contribute significantly to the probability of safety or reliability risks. So far, generic tools or facilities for planning demanding maintenance tasks in detail have not been available for companies' independent use. Another challenge is to develop and apply better user interfaces for design processes. Virtual engineering tools, such as virtual reality (VR) and haptics, provide a potential solution for improving maintenance planning and maintainability design. This paper introduces development and benefits of a new haptic interface for planning and training industrial maintenance tasks. The paper introduces a test with haptics tools in virtual maintenance case examples. As a conclusion we will sum up, whether the use of a haptic user interface would enhance task planning and maintainability design. In addition, we propose a set of recommendations regarding use of haptics in maintenance planning and maintainability design.
Towards Relational Schema Uncertainty
Authors: Matteo Magnani, Danilo Montesi
Venue: Proceedings of the 3rd International Conference on Scalable Uncertainty Management (2009)

In this paper we introduce the problem of managing uncertainty on the schema of a relational database. We formalize this problem using a possible world semantics, identify the challenges posed by the co-existence of many alternative schemata, and define some basic properties of a system with uncertain schemata. Finally, we describe a query rewriting system, i.e., the technique used to produce valid queries for each alternative schema, and study its properties.
Content-Based Personalization Services Integrating Folksonomies
Authors: Cataldo Musto, Fedelucio Narducci, Pasquale Lops, Marco Gemmis, Giovanni Semeraro
Venue: Proceedings of the 10th International Conference on E-Commerce and Web Technologies (2009)

Basic content-based personalization consists in matching up the attributes of a user profile, in which preferences and interests are stored, with the attributes of a content object. The Web 2.0 (r)evolution has changed the game for personalization, from `elitary' Web 1.0, written by few and read by many, to web content generated by everyone (user-generated content - UGC), since the role of people has evolved from passive consumers of information to that of active contributors.One of the forms of UGC that has drawn most attention of the research community is folksonomy, a taxonomy generated by users who collaboratively annotate and categorize resources of interests with freely chosen keywords called tags.FIRSt (Folksonomy-based Item Recommender syStem) is a content-based recommender system developed at the University of Bari which integrates UGC (through social tagging) in a classic content-based model, letting users express their preferences for items by entering a numerical rating as well as to annotate rated items with free tags. FIRSt is capable of providing recommendations for items in several domains (e.g., movies, music, books), provided that descriptions of items are available as text documents (e.g. plot summaries, reviews, short abstracts). This paper describes the system general architecture and user modeling approach, showing how this recommendation model has been applied to recommend the artworks located at the Vatican Picture Gallery (Pinacoteca Vaticana), providing users with a personalized museum tour tailored on their tastes.
Auto-calibration of a Laser 3D Color Digitization System
Authors: Xiaojie Li, Bao-Zhen Ge, Dan Zhao, Qing-Guo Tian, K. David Young
Venue: Proceedings of the 2nd International Conference on Digital Human Modeling: Held as Part of HCI International 2009 (2009)

A typical 3D color digitization system is composed of 3D sensors to obtain 3D information, and color sensors to obtain color information. Sensor calibration plays a key role in determining the correctness and accuracy of the 3D color digitization data. In order to carry out the calibration quickly and accurately, this paper introduces an automated calibration process which utilizes 3D dynamic precision fiducials, with which calibration dot pairs are extracted automatically, and as the corresponding data are processed via a calibration algorithm. This automated was experimentally verified to be fast and effective. Both the 3D information and color information are extracted such that the 3D sensors and the color sensors are calibrated with one automated calibration process. We believe it is the first such calibration process for a 3D color digitization system.
A novel approach to model generation for heterogeneous data classification
Authors: Rong Jin, Huan Liu
Venue: Proceedings of the 19th international joint conference on Artificial intelligence (2005)

Ensemble methods such as bagging and boosting have been successfully applied to classification problems. Two important issues associated with an ensemble approach are: how to generate models to construct an ensemble, and how to combine them for classification. In this paper, we focus on the problem of model generation for heterogeneous data classification. If we could partition heterogeneous data into a number of homogeneous partitions, we will likely generate reliable and accurate classification models over the homogeneous partitions. We examine different ways of forming homogeneous subsets and propose a novel method that allows a data point to be assigned multiple times in order to generate homogeneous partitions for ensemble learning. We present the details of the new algorithm and empirical studies over the UCI benchmark datasets and datasets of image classification, and show that the proposed approach is effective for heterogeneous data classification.
Research on the Needle Selecting Machine of Computerized Jacquard Circle Knitting Machine Based on Piezoelectric Ceramics
Authors: Zhang Zhiming, Xu Qiao, Mei Shunqi, Yu Lianqing
Venue: Proceedings of the 2009 IITA International Conference on Services Science, Management and Engineering (2009)

In order to overcome the shortage in the traditional mechanical needle selecting machine of jacquard circle knitting machine, a new needle selecting machine based on piezoelectric ceramics is designed. This paper expands on the structure of needle selecting machine and its principle. The piezoelectric ceramics have a micro-displacement with the different flower type. The movement is enlarged by the needle piece and the needle moves to the requested location. Therefore, the three movements of needle selecting machine are realized such as the loop formation, loop accumutional and float adjustment loop.