ppxscal/embedding_network huggingface dataset:
Semi-analytic integration of hypersingular Galerkin BIEs for three-dimensional potential problems
Authors: S. Nintcheu Fata, L. J. Gray
Venue: Journal of Computational and Applied Mathematics (2009)

An accurate and efficient semi-analytic integration technique is developed for three-dimensional hypersingular boundary integral equations of potential theory. Investigated in the context of a Galerkin approach, surface integrals are defined as limits to the boundary and linear surface elements are employed to approximate the geometry and field variables on the boundary. In the inner integration procedure, all singular and non-singular integrals over a triangular boundary element are expressed exactly as analytic formulae over the edges of the integration triangle. In the outer integration scheme, closed-form expressions are obtained for the coincident case, wherein the divergent terms are identified explicitly and are shown to cancel with corresponding terms from the edge-adjacent case. The remaining surface integrals, containing only weak singularities, are carried out successfully by use of standard numerical cubatures. Sample problems are included to illustrate the performance and validity of the proposed algorithm.
Distinguisher and Related-Key Attack on the Full AES-256
Authors: Alex Biryukov, Dmitry Khovratovich, Ivica Nikolić
Venue: Proceedings of the 29th Annual International Cryptology Conference on Advances in Cryptology (2009)

In this paper we construct a chosen-key distinguisher and a related-key attack on the full 256-bit key AES. We define a notion of differential q -multicollision and show that for AES-256 q-multicollisions can be constructed in time q·267 and with negligible memory, while we prove that the same task for an ideal cipher of the same block size would require at least $O(q\cdot 2^{\frac{q-1}{q+1}128})$ time. Using similar approach and with the same complexity we can also construct q-pseudo collisions for AES-256 in Davies-Meyer mode, a scheme which is provably secure in the ideal-cipher model. We have also computed partial q-multicollisions in time q·237 on a PC to verify our results. These results show that AES-256 can not model an ideal cipher in theoretical constructions. Finally we extend our results to find the first publicly known attack on the full 14-round AES-256: a related-key distinguisher which works for one out of every 235 keys with 2120 data and time complexity and negligible memory. This distinguisher is translated into a key-recovery attack with total complexity of 2131 time and 265 memory.
Scaling the dynamic approach to autonomous path planning: planning horizon dynamics
Authors: Edward W. Large, Henrik I. Christensen, Ruzena Bajcsy
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

In the dynamical systems approach to robot path planning both sensed and remembered information contribute to shape a nonlinear vector field that governs the behavior of an autonomous agent. Such systems perform well with partial knowledge of the environment and in dynamically changing environments. Nevertheless, it is a local heuristic approach to path planning, and it is not guaranteed to find existing paths. We describe a method of adjusting the spatial resolution of the planner using a dynamical system that operates at a faster time scale than the planning dynamics. This improves the system's ability to utilize both sensed and remembered information, and to solve a larger range of problems without resorting to global path planning.
Mobile Identity Management Revisited
Authors: Emin Islam Tatli, Stefan Lucks
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

Identity management provides PET (privacy enhancing technology) tools for users to control privacy of their personal data. With the support of mobile location determination techniques based on GPS, WLAN, Bluetooth, etc., context-aware and location-aware mobile applications (e.g. restaurant finder, friend finder, indoor and outdoor navigation, etc.) have gained quite big interest in the business and IT world. Considering sensitive static personal information (e.g. name, address, phone number, etc.) and also dynamic personal information (e.g. current location, velocity in car, current status, etc.), mobile identity management is required to help mobile users to safeguard their personal data. In this paper, we evaluate certain required aspects and features (e.g. context-to-context dependence and relation, blurring in levels, trust management with p3p integration, extended privacy preferences, etc.) of mobile identity management systems from the perspective of a push context-aware application, i.e. the Friend Finder application.
Research on Laser Echo Wireless Acquiring Technique
Authors: Li Jing, Huang Zheng
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

A short-distance wireless transmission program of laser echo signal was proposed to solve the problems: atrocious conditions, wiring in need of special protection, the cost of higher. The digital echo signal was transmitted into embedded single-chip LPC2880, through the wireless transmission module PTR4000, the signal was transmitted to the receiving system. Receiving system will receive the signal and transmit through the Ethernet interface to the PC machine. The echo signal will be stored on the computer in the form of file, According to the demand, the echo signal spectral analysis can be carried, signal and power spectrum will be real-time displayed in the form of graph. The experimental results show that: PC machine can correctly convey control commands, acquisition system can accept PC instructions correctly, implement the process of wireless acquisition, the measured data can be transmitted through the Ethernet interface to PC machine.
Decision support under uncertainties based on robust Bayesian networks in reverse logistics management
Authors: Eduard Shevtshenko, Yan Wang
Venue: International Journal of Computer Applications in Technology (2009)

One of the major challenges for product lifecycle management systems is the lack of integrated decision support tools to help decision-making with available information in collaborative enterprise networks. Uncertainties are inherent in such networks due to lack of perfect knowledge or conflicting information. In this paper, a robust decision support approach based on imprecise probabilities is proposed. Robust Bayesian belief networks with interval probabilities are used to estimate imprecise posterior probabilities in probabilistic inference. This generic approach is demonstrated with decision-makings in design for closed-loop supply chain. The ultimate goal of robust intelligent decision support systems is to enhance the effective use of information available in collaborative engineering environments.
From spaces to places: emerging contexts in mobile privacy
Authors: Clara Mancini, Keerthi Thomas, Yvonne Rogers, Blaine A. Price, Lukazs Jedrzejczyk, Arosha K. Bandara, Adam N. Joinson, Bashar Nuseibeh
Venue: Proceedings of the 11th international conference on Ubiquitous computing (2009)

Mobile privacy concerns are central to Ubicomp and yet remain poorly understood. We advocate a diversified approach, enabling the cross-interpretation of data from complementary methods. However, mobility imposes a number of limitations on the methods that can be effectively employed. We discuss how we addressed this problem in an empirical study of mobile social networking. We report on how, by combining a variation of experience sampling and contextual interviews, we have started focusing on a notion of context in relation to privacy, which is subjectively defined by emerging socio-cultural knowledge, functions, relations and rules. With reference to Gieryn's sociological work, we call this place, as opposed to a notion of context that is objectively defined by physical and factual elements, which we call space. We propose that the former better describes the context for mobile privacy.
Power Transformer State Assessment Based on Grey Target Theory
Authors: Jianpo Li, Xiaojuan Chen, Chunming Wu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

The state assessment of power transformer is the precondition and key to realize power transformer maintenance. The fault system of power transformer can be recognized as a typical grey system. A new method is given to recognize power transformer state without the standard fault model. It introduces grey target theory into state assignment of power transformer. Combining the popular technology of dissolved gases analyses, the arithmetic step for state assessment of power transformer is given. The method uses variable weight to replace equal weight, which is closer to the actual state of power transformer. Variable weight is ascertained by grey target contribution degree technology. The experiment results show it is a new and available method for state assessment of power transformer without the standard fault model, and its validity and efficiency is proved by many examples.
Semiparametric analysis of survival data with left truncation and right censoring
Authors: Pao-sheng Shen
Venue: Computational Statistics Data Analysis (2009)

Let T, C and V denote the lifetime, censoring and truncation variables, respectively. Assume that (C,V) is independent of T and P(C>=V)=1. Let F, Q and G denote the common distribution functions of T, C and V, respectively. For left-truncated and right-censored (LTRC) data, one can observe nothing if T=V. For LTRC data, the truncation product-limit estimate F@?"n is the maximum likelihood estimate (MLE) for nonparametric models. If the distribution of V is parameterized as G(x;@q) and the distributions of T and C are left unspecified, the product-limit estimate F@?"n is not the MLE for this semiparametric model. In this article, for LTRC data, two semiparametric estimates are proposed for the semiparametric model. A simulation study is conducted to compare the performances of the two semiparametric estimators against that of F@?"n. The proposed semiparametric method is applied to a Channing House data.
An Improved Viterbi Algorithm for PMMW Moving Targets Detection
Authors: Li Liangchao, Yang Jianyu, Wang Junli
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

For the detecting moving target, an Improved Viterbi Algorithm (IVA) is a useful technique for a Track Before Detect (TBD) architecture implementation, designed to track and detect dim maneuvering targets from an image sequence under low signal-to-noise ratio(SNR) conditions. It especially suits real passive millimeter wave (PMMW) as the objects radiant energy is very weak. The IVA does a search over all the possible state sequences, marking probable tracks by scanning each pixel in each frame, and determining where it was likely to originate from in the previous image. In this paper the real time calculation of detecting threshold and the IVA process is described. The experimental results show that the IVA performs well for dim PMMW image sequences at low SNR environment with complex background.
A Parallel Algorithm for Computer Simulation of Electrocardiogram Based on MPI
Authors: Wenfeng Shen, Weijia Lu, Daming Wei, Weimin Xu, Xin Zhu, Shizhong Yuan
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

This paper presents a parallel algorithm for computer simulation of Electrocardiogram (ECG) based on a 3-dimensional (3D) whole-heart model. The computer heart model includes approximately 50,000 discrete elements (model cells) inside a torso model represented by 344 nodal points with 684 triangle meshes. The Poison question is applied to the volume conductor problem for simulation of ECG, which involves a maximum of about 50,000 electric current dipole sources and four boundaries including the torso surface and three surfaces of heart. A parallel algorithm was introduced to solve this problem based on Message Passing Interface (MPI). An implementation is conducted with a cluster computer system consisting of up to eight PCs, each of which has a dual-core processor. It was shown that the speedup is close to 2 in one PC and close to 8 with 8 processors, as compared to the serial algorithm. This study demonstrates a useful way of parallel computing in biomedical simulation study.
Efficient maximization in solving POMDPs
Authors: Zhengzhu Feng, Shlomo Zilberstein
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

We present a simple, yet effective improvement to the dynamic programming algorithm for solving partially observable Markov decision processes. The technique targets the vector pruning operation during the maximization step, a key source of complexity in POMDP algorithms. We identify two types of structures in the belief space and exploit them to reduce significantly the number of constraints in the linear programs used for pruning. The benefits of the new technique are evaluated both analytically and experimentally, showing that it can lead to significant performance improvement. The results open up new research opportunities to enhance the performance and scalability of several POMDP algorithms.
Developing search strategies for detecting relevant experiments
Authors: Oscar Dieste, Anna Grimán, Natalia Juristo
Venue: Empirical Software Engineering (2009)

Our goal is to analyze the optimality of search strategies for use in systematic reviews of software engineering experiments. Studies retrieval is an important problem in any evidence-based discipline. This question has not been examined for evidence-based software engineering as yet. We have run several searches exercising different terms denoting experiments to evaluate their recall and precision. Based on our evaluation, we propose using a high recall strategy when there are plenty of resources or the results need to be exhaustive. For any other case, we propose optimal, or even acceptable, search strategies. As a secondary goal, we have analysed trends and weaknesses in terminology used in articles reporting software engineering experiments. We have found that it is impossible for a search strategy to retrieve 100% of the experiments of interest (as happens in other experimental disciplines), because of the shortage of reporting standards in the community.
Model Design of Job Shop Scheduling Based on Multi-agent System
Authors: Qing-song Li, Li-ming Du
Venue: Proceedings of the 2009 IITA International Conference on Services Science, Management and Engineering (2009)

Job-Shop Scheduling is the core contents of the CIMS research area and production logistics in the discrete manufacturing industry. To solve Job-Shop Scheduling problems, a scheduling mode1 based on MAS (Multi-Agent-System) is presented with multiple applications of genetic algorithm (GA) and contract-net mechanism. In the model, the entities in the job-shop are abstracted as Task Agent, Resource Agent, Control Agent and Cooperation agent. The scheduling mode1 is able to combine the flexibility of MAS and optimization through algorithms mentioned above. This model improves the literature proposed genetic algorithm, solves the dynamic job-shop scheduling problem by multi-agent consultative mechanism. According to compute the stimulating degree and equipment threshold, the new mission can be directly access to the appropriate sequence. At the same time, the use of genetic algorithm processing of the final route selection makes a reasonable allocation of resources. At the same time, the scheduling optimization objectives and the factors disturbing job-shop scheduling are analyzed in the paper.
The Classification Method Study of Two-Dimension Iteration Transductive Support Vector Machine
Authors: Xu Yi, Wang Rui
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

Because of the restriction caused by the practical application, the semi-supervised learning is generally adopted in pattern recognition. The paper proposed the method, which takes the Support Vector Machine (SVM) as a basic tool with absorbing the transductive inference to make the full use of concerned training sample information so that high-quality separating hyperplane of transductive sample set can be generated. The method is composed of two transductive inferences that 1) based on time-varied separating hyperplane the number of labeled transductive samples is increased while the samples in the training set is simultaneously deleted, so-called y-dimension iteration transduction and 2) labeled training sample subsets are offered the gradually increasing punishment factor coefficients as well as the punishment factor of training set is decreased by steps, the so-called x-dimension iteration transduction. During the period x-dimension iteration transductions are nested in y-dimension iteration transductions, which end at the time when the training set is empty. Simulation proves the method has the higher accuracy and stronger robust than correlation knowledge induction SVM and prior knowledge induction SVM in the situation where the label of training set is unavailable, such as remote sensing thermal imaging cognition.
A model to measure the characterizing parameters of the deep fascia
Authors: L. Benetazzo, G. Frigo, C. Stecco
Venue: Proceedings of the 2009 IEEE International Workshop on Medical Measurements and Applications (2009)

The aim of this work is to create a computerized tridimensional model of the deep fascia, as useful and flexible tool suitable for any histological section's analysis. It allows determinations, also quantitative, of the elements that formed the evaluated tissue, their spatial dispositions and relationships. Every manipulation and elaboration do not necessarily ask an irreversible alteration of the original tissue, as happen with the biological specimens. The present study considers a crural fascia specimen, taken from the posterior region of the knee.
Loss minimization in parse reranking
Authors: Ivan Titov, James Henderson
Venue: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (2006)

We propose a general method for reranker construction which targets choosing the candidate with the least expected loss, rather than the most probable candidate. Different approaches to expected loss approximation are considered, including estimating from the probabilistic model used to generate the candidates, estimating from a discriminative model trained to rerank the candidates, and learning to approximate the expected loss. The proposed methods are applied to the parse reranking task, with various baseline models, achieving significant improvement both over the probabilistic models and the discriminative rerankers. When a neural network parser is used as the probabilistic model and the Voted Perceptron algorithm with data-defined kernels as the learning algorithm, the loss minimization model achieves 90.0% labeled constituents F1 score on the standard WSJ parsing task.
An Effective Signal Processing Method to Musical Information Retrieval
Authors: Li Peng, Zhou Mingquan, Wang Xuesong, Li Nansha
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

In this paper, an effective acoustic signal processing method has been presented in research of Musical Information Retrieval (MIR). Firstly, the raw acoustic signal was pretreated by a adaptive wavelet soft-threshold of gain factor and teager energy operator (AWSTD_GF&TEO), then it needs to extract the fundamental frequency form it. Secondly, proposed a new effective "cabinet" method to filter the waveform, after that, the waveform is available compared with the one unfiltered, at last, implemented the retrieval operations with an improved melody representation method and string fuzzy matching method. The evaluation result shows that the AWSTD_GF&TEO and the new "cabinet" method could help to retrieval the object more accurate.
Real-Time Crying Simulation
Authors: Wijnand Tol, Arjan Egges
Venue: Proceedings of the 9th International Conference on Intelligent Virtual Agents (2009)

Displaying facial motions such as crying or laughing is difficult to achieve in real-time simulations and games. Not only because of the complicated simulation of the physical characteristics such as muscle motions or fluid simulations, but also because one needs to know how to control these motions on a higher level. In this paper, we propose a method that uses the MPEG-4 Facial Animation standard to control a realistic crying face in real-time. The tear simulation is based on the Smoothed Particle Hydrodynamics technique, which we optimized for real-time tear generation and control. Through simple parameters, a wide range of expressions and tears can be generated on the fly. Additionally, our method works independently of the graphics and physics engines that are used.
Design and Reliability Analysis of Data Logging and Management System for AUV
Authors: Bo He, Ke Yao, Bingsen Li, Chunyun Ren, Jing Luo
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

The data logging and management system (DLAM) of the autonomous underwater vehicle (AUV) running on the on-board PC/104 module uses the synchronization and communication mechanism by using multi-threading to implement the function of the collection of data from different devices through multi-serial-port card for sonar, compass, gyro and the USB port for accelerometer, as well as the function of enveloping and transmitting the data to the on-board Industrial PC (IPC) via Ethernet and the function of managing and recording the data locally. Circular buffer management class designed by ourselves and the sequence table are used to manage the data in the memory. By using the circular buffer, we can be free from those trivia like allocating and releasing the resources of memory all the time. The software reliability is analysed and evaluated as well. White-box testing method is employed to test the system, and Musa execution time model is used to estimate the reliability. The result of the estimation shows that the system achieves the expected requirement.
IT Enabled Risk Management for Taxation and Customs: The Case of AEO Assessment in the Netherlands
Authors: Jianwei Liu, Yao-Hua Tan, Joris Hulstijn
Venue: Proceedings of the 8th International Conference on Electronic Government (2009)

Building collaborative relationships with trusted businesses is a long-term strategy for EU governments. Recently, for the EU Tax and Customs Administration (TCA), the realization of this goal has become more visible with the emerging concept of the Authorized Economic Operator (AEO). Businesses in the member states can apply for the AEO certificate. When it is being granted, simplified control procedures and trade facilitation will be provided by the TCA. A possible "win-win situation" can be achieved, with increased trade efficiency and lowered administrative burden. However, without proper selection of trusted business partners, governments may be worse off due to the adverse selection problem caused by information asymmetry. In this paper, we analyze the cause and effect of the adverse selection in the Government-to-Business relationship building. Further, we show that an IT enabled risk assessment approach can effectively eliminate the G2B information asymmetry and solve the adverse selection problem. The AEO assessment approach of DutchTCA is analysed to give a real life application on how IT is enabling the general risk management approach of the DutchTCA.