ppxscal/embedding_network huggingface dataset:
Uniform Budgets and the Envy-Free Pricing Problem
Authors: Patrick Briest
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

We consider the unit-demand min-buying pricing problem, in which we want to compute revenue maximizing prices for a set of products $\mathcal{P}$ assuming that each consumer from a set of consumer samples $\mathcal{C}$ will purchase her cheapest affordable product once prices are fixed. We focus on the special uniform-budget case, in which every consumer has only a single non-zero budget for some set of products. This constitutes a special case also of the unit-demand envy-free pricing problem.We show that, assuming specific hardness of the balanced bipartite independent set problem in constant degree graphs or hardness of refuting random 3CNF formulas, the unit-demand min-buying pricing problem with uniform budgets cannot be approximated in polynomial time within $\mathcal{O}(\log ^{\varepsilon} |\mathcal{C}|)$ for some ¿> 0. This is the first result giving evidence that unit-demand envy-free pricing, as well, might be hard to approximate essentially better than within the known logarithmic ratio.We then introduce a slightly more general problem definition in which consumers are given as an explicit probability distribution and show that in this case the envy-free pricing problem can be shown to be inapproximable within $\mathcal{O}(|\mathcal{P}|^{\varepsilon})$ assuming NP $\nsubseteq \bigcap _{\delta >0}$ BPTIME($2^{\mathcal{O}(n^{\delta})}$). Finally, we briefly argue that all the results apply to the important setting of pricing with single-minded consumers as well.
Tamper proofing mechanisms for motion capture data
Authors: Parag Agarwal, Balakrishnan Prabhakaran
Venue: Proceedings of the 10th ACM workshop on Multimedia and security (2008)

Repositories of motion captured (Mocap) data can be reused for human motion analysis in physical medicine, biomechanics, and animation related entertainment industry. Mocap data expressed as a matrix can be subject to tampering from shuffling of its elements or change in element values due to motion editing operations. Tampering of the archival system intentionally or due to machine/human errors, may result in loss of research, money and effort. In order to detect and correct errors induced due to tampering; this paper proposes a tamper proofing methodology that combines hash function and watermarking based methods. These patterns (fingerprints) resulting from hash functions help in error detection by identifying the type of attack such as row shuffling, column shuffling, row element shuffling, column element shuffling and their combinations. Random attacks that change data element values are detected by change in watermarks embedded in data elements. Finger prints help in solving the attacks reversal such as column shuffling and element shuffling, whereas watermarking helps in reversing attacks such as column element or row element shuffling. As compared to other attacks, random attacks cannot be reversed, and can be improved using interpolation. Analysis shows that the proposed method uses O(n) space to detect and correct errors, and the time complexity for correction varying from o(n log n) to O(n!).
Real-Time Integration of Geospatial Raster and Point Data Streams
Authors: Carlos Rueda, Michael Gertz
Venue: Proceedings of the 20th international conference on Scientific and Statistical Database Management (2008)

Sensor and network technology advances are increasingly placing an immense amount of real-time geospatial data streams at the scientist's disposal. The effective integration and assimilation of such datasets, however, is still a challenging goal. In this paper, we describe a computational framework that simplifies the design, execution, and visualization of processing workflows involving the integration of satellite raster and ground point data streams. The framework is enabled for interoperability by adhering to open sensor data standards, and demonstrated with the evaluation of key environmental inputs needed for the estimation of reference evapotranspiration over California.
Soft-Sensor Method Based on Least Square Support Vector Machines Within Bayesian Evidence Framework
Authors: Wei Wang, Tianmiao Wang, Hongxing Wei, Hongming Zhao
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

Based on the character and requirement of the dynamic weighing of loader, the soft sensor technique was adapted as the weighing method, and the least square support vector machine (LS-SVM) as its modelling method. Also the Bayesian evidence framework was used in LS-SVM for selecting and tuning its parameter. And then, after the nonlinear regression algorithms of LS-SVM and the principle of Bayesian evidence framework were introduced, the soft sensor model based on LS-SVM was given. In the end, emulation analysis results indicate that soft-sensor method based on LS-SVM within Bayesian evidence framework is a valid means for solving dynamic weighing of loader.
An Integrative Framework to Protocol Analysis and Repair: Bellare-Rogaway Model + Planning + Model Checker
Authors: Kim-Kwang Raymond Choo
Venue: Informatica (2007)

A modified version of the Bellare and Rogaway (1993) adversarial model is encoded using Asynchronous Product Automata (APA). A model checker tool, Simple Homomorphism Verification Tool (SHVT), is then used to perform state-space analysis on the Automata in the setting of planning problem. The three-party identity-based secret public key protocol (3P-ID-SPK) protocol of Lim and Paterson (2006), which claims to provide explicit key authentication, is used as a case study. We then refute its heuristic security argument by revealing a previously unpublished flaw in the protocol using SHVT. We then show how our approach can automatically repair the protocol. This is, to the best of our knowledge, the first work that integrates an adversarial model from the computational complexity paradigm with an automated tool from the computer security paradigm to analyse protocols in an artificial intelligence problem setting - planning problem - and, more importantly, to repair protocols. The views and opinions expressed in this paper are those of the author and do not reflect those of the Australian Government and Australian Institute of Criminology. Research was performed while the author was with the Intelligent Systems Laboratory / University of Western Sydney.
Computational Semantics and Knowledge Engineering
Authors: Johan Bos
Venue: Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns (2008)

Computational semantics is the business of associating meaning representations with natural language expressions (words, phrases, sentences, and texts), and drawing inferences from these meaning representations [1]. It is an area that has recently matured to a state in which we have at our disposal robust, widecoverage systems that are capable of producing formal semantic representations for open-domain texts. One of such system is Boxer, developed by myself over the last four years [2,3].
Deploying Application Services Using Service Delivery Platform (SDP)
Authors: Jae Hyoung Cho, Bi-Feng Yu, Jae-Oh Lee
Venue: Proceedings of the 10th Asia-Pacific Network Operations and Management Symposium on Managing Next Generation Networks and Services (2007)

Nowadays in communication and network businesses, architectures and systems are independently constructed with existing service or new service deployment without considering common functions and services between them. Consequently, the study of standardized Service Delivery Platform (SDP) structure and its related interfaces is needed to provide the methodology of existing or new services in an efficient way. Therefore, in this paper, we intend to view various solutions about SDP structure with the proposed interfaces which are able to support them, and then recommend various application services which SDP can offer to end users.
Nominal Matching and Alpha-Equivalence
Authors: Christophe Calvès, Maribel Fernández
Venue: Proceedings of the 15th international workshop on Logic, Language, Information and Computation (2008)

Nominal techniques were introduced to represent in a simple and natural way systems that involve binders. The syntax includes an abstraction operator and a primitive notion of name swapping. Nominal matching is matching modulo &alpha;-equality, and has applications in programming languages and theorem proving, amongst others. In this paper we describe efficient algorithms to check the validity of equations involving binders, and also to solve matching problems modulo &alpha;-equivalence, using the nominal approach.
Dynamic Configurable Auctions for Coordinating Industrial Waste Discharges
Authors: Javier Murillo, Víctor Muñoz, Beatriz López, Dídac Busquets
Venue: Proceedings of the 5th German conference on Multiagent System Technologies (2007)

The use of auctions for distributing resources in competing environments has produced a large variety of auctions types and algorithms to treat them. However, auctions have some problems when faced with some real-world applications containing renewable and perishable resources. In this paper we present a mechanism to deal with such issues by dynamically configuring some of the auction parameters taking into account the past experience. The mechanism has been used to coordinate industrial discharges and a Waste Water Treatment Plant, so that the treatment thresholds of the plant are never exceeded. We have performed some simulations to evaluate the system, and the results show that with this mechanism the coordination between the industries improves the treatment of the water.
Simulation Analysis for the Pricing of Bond Option on Arbitrage-Free Models with Jump
Authors: Kisoeb Park, Moonseong Kim, Seki Kim
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

We derive a closed-form solutions for bond option pricing on arbitrage-free models with jump and perform Monte Carlo simulation for them. We know that the bond option price on arbitrage-free models with jump is humped. The fact shows that valuations of this model estimate highly precision. In this paper, we simulate the proposed models by the Monte Carlo simulation with scenarious. By simulation analysis, we obtain that bond option prices on arbitrage-free models are larger than bond option prices on arbitrage-free models with jump. Lower value of precision in arbitrage-free models with jump correspond to sharper estimates.
Automatic detection of lesion border and edge-related structures in dermoscopy images
Authors: R. H. Moss
Venue:  (2007)

Early detection of malignant melanoma is critical because early stage diagnosis results in a higher survival rate. As pre-processing steps of digital dermoscopy images in an automatic diagnosis system, line structure identification and lesion border identification algorithms are important for accuracy of diagnosis.This work presents the methodology and procedures to process dermoscopy images using computer vision and data mining methods.A watershed-based adaptive skin lesion border finder was developed and implemented for dermoscopy images. The boundaries found using this algorithm were compared to those found by three existing automated boundary finders and were also compared to boundaries manually drawn by three dermatologists. On the 100-image test set, the watershed algorithm substantially outperforms the other automated techniques and produces boundaries within inter-dermatologist agreement rates.An improved SharpRazor algorithm was developed to remove hairs from dermoscopy images, based on a previously existing DullRazor&reg; algorithm for hair removal. Analysis of the signal-to-noise ratio and hit rate was studied and the improvements were quantified. The new algorithm is significantly better with respect to leaving texture features, such as pigment network, intact while still removing hairs well.Work is also reported here on classifiers for detecting atypical pigment network in skin lesions based on texture.Some other work including a program to remove the black border introduced by some image digitizers; and an application of the watershed algorithm to a larger set of images is also introduced in this dissertation.
BSP Functional Programming: Examples of a Cost Based Methodology
Authors: Frédéric Gava
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

Bulk-Synchronous Parallel ML (BSML) is a functional dataparallel language for the implementation of Bulk-Synchronous Parallel (BSP) algorithms. It makes an estimation of the execution time (cost) possible. This paper presents some general examples of BSML programs and a comparison of their predicted costs with the measured execution time on a parallel machine.
Vocal folds objective evaluation measuring vascularization level and texture
Authors: Amaia Méndez, Begoña García, Ibon Ruiz, Ibai Iturricha
Venue: Proceedings of the 7th WSEAS International Conference on Signal Processing, Robotics and Automation (2008)

This paper presents the design of an algorithm that joins different digital image processing techniques; witch is applied to endoscopic images of vocal folds. The aim of this research is to provide objective indicators of the vascularization level and the texture to the doctor, in order to support his diagnosis and change the current subjective view. The processing is based on the FFT Band Pass Filter and the mathematical operations between treated images, in order to enhance the level of vascularization. Both the final result and the texture measures will be presented in a results report.
Time-Series Alignment by Non-negative Multiple Generalized Canonical Correlation Analysis
Authors: Bernd Fischer, Volker Roth, Joachim M. Buhmann
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

For a quantitative analysis of differential protein expression, one has to overcome the problem of aligning time series of measurements from liquid chromatography coupled to mass spectrometry. When repeating experiments one typically observes that the time axis is deformed in a non-linear way. In this paper we propose a technique to align the time series based on generalized canonical correlation analysis (GCCA) for multiple datasets. The monotonicity constraint in time series alignment is incorporated in the GCCA algorithm. The alignment function is learned both in a supervised and a semi-supervised fashion. We compare our approach with previously published methods for aligning mass spectrometry data on a large proteomics dataset.
Computing Alignment Seed Sensitivity with Probabilistic Arithmetic Automata
Authors: Inke Herms, Sven Rahmann
Venue: Proceedings of the 8th international workshop on Algorithms in Bioinformatics (2008)

Heuristic sequence alignment and database search algorithms, such as PatternHunter and BLAST, are based on the initial discovery of so-called alignment seeds of well-conserved alignment patterns, which are subsequently extended to full local alignments. In recent years, the theory of classical seeds (matching contiguous q-grams) has been extended to spaced seeds, which allow mismatches within a seed, and subsequently to indel seeds, which allow gaps in the underlying alignment.Different seeds within a given class of seeds are usually compared by their sensitivity, that is, the probability to match an alignment generated from a particular probabilistic alignment model.We present a flexible, exact, unifying framework called probabilistic arithmetic automaton for seed sensitivity computation that includes all previous results on spaced and indel seeds. In addition, we can easily incorporate sets of arbitrary seeds. Instead of only computing the probability of at least one hit (the standard definition of sensitivity), we can optionally provide the entire distribution of overlapping or non-overlapping seed hits, which yields a different characterization of a seed. A symbolic representation allows fast computation for any set of parameters.
An interactive sketching method for 3D object modeling
Authors: Sofia Kyratzi, Nickolas Sapidis
Venue: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (2008)

The subject of this paper is "automatic construction of a Polyhedron from a Single Sketch (PSS)". Published works on the PSS problem view it as an "image processing"/"computer vision" problem where emphasis is placed at analyzing the given input (sketch) using various heuristics. This paper proposes a new methodology to solve the PSS problem based on robust methods and tools from Graph Theory, Solid Modeling and Euclidean Geometry.
Ball detection from broadcast soccer videos using static and dynamic features
Authors: V. Pallavi, Jayanta Mukherjee, Arun K. Majumdar, Shamik Sural
Venue: Journal of Visual Communication and Image Representation (2008)

In this paper, we propose an approach for detecting ball in broadcast soccer videos. We use hybrid techniques for identifying ball in medium and long shots. Candidate ball positions are first extracted using features based on shape and size. For medium shots, a ball is identified by filtering the candidates with the help of motion information. In long shots, after motion based filtering of the non-ball candidates, a directed weighted graph is constructed for the remaining ball candidates. Each node in the graph represents a candidate and each edge links candidates in a frame with the candidates in next two consecutive frames. Finally, dynamic programming is applied to find the longest path of the graph, which gives the actual ball trajectory. Experiments with several soccer sequences show that the proposed approach is very efficient.
On algorithms for technology mapping
Authors: Robert Brayton
Venue:  (2007)

The task of technology mapping in logic synthesis is to express a given Boolean network as a network of gates chosen from a given library with the goal of optimizing some objective function such as total area or delay. In these general terms, technology mapping is intractable. The problem is usually simplified by first representing the Boolean network as a good initial multi-level network of simple gates called the subject graph. The subject graph is then transformed into a multilevel network of library gates by enumerating the different library gates that match at each node in the subject graph (the matching step) and selecting the best subset of matches (the selection step). However, this simplification means that the structure of the initial network dictates to a large extent the structure of the mapped network; this is known as structural bias. In this work we improve the quality and run-time of technology mapping by introducing new methods and improving existing methods for mitigating structural bias. To this end we propose some new algorithms addressing both matching and selection. Our methods are useful for mapping to standard cell libraries and to lookup table-based FPGAs. We start with matching. We present a scalable and robust algorithm (based on recent advances in combinational equivalence checking) to combine multiple networks into a single subject graph with choices. This enables lossless synthesis where different snapshots taken during synthesis can be combined into one subject graph on which mapping is done. We improve on existing Boolean matching methods with a simpler and faster algorithm (based on improved cut computation and avoiding canonization) that finds matches across all networks encoded in the subject graph. We also introduce a new construct called a supergate that increases the number of matches found for standard cell mapping. Having increased the set of matches found in the matching step, we turn to selection. For some cost functions such as delay under the constant-delay model, optimal selection is easy, but for an area cost function, optimal selection is NP-hard. We present a simple heuristic procedure that works well in practice even with the larger search space due to the increased set of matches with choices, and it outperforms the methods proposed in the literature. Although we focus on area for concreteness, the same procedure can be used to optimize for power since the two objectives are very similar.
A mathematical method to minimize the measurement errors
Authors: Lidia Niculita, Radu Adrian Niculita
Venue: Proceedings of the 7th WSEAS International Conference on Signal Processing, Robotics and Automation (2008)

In this paper we present o mathematical method use for minimize the measurement error in the case of automated measurement systems that are integrated into processing systems. The problems of the palpation systems of the measurement systems, starting from a general approach, consists of the optimization of the palpation systems in such a way that the measurement errors generated by them to be as small as possible.
Super-resolution and facial expression for face recognition in video
Authors: Bir Bhanu
Venue:  (2007)

Face recognition based on video has received significant attention in the past a few years. However, the acquainted facial images in video from a distance are usually small and the quality of them is low. Enhancing low-resolution (LR) facial images from the video sequence is of importance for performing face recognition. Super-resolution (SR) reconstruction is one of the most difficult and ill-posed problems due to the demand of accurate alignments between multiple images and multiple solutions for a given set of images. In particular, human face is much more complex compared to other objects which are addressed by the majority of the super-resolution literature. Super-resolution from facial images may suffer from subtle facial expression variation, non-rigid complex motion model, visibility and occlusion, and illumination and reflectance variations. In this dissertation, the objective is to design algorithms to tackle the problems brought by the special characteristics of human face. The techniques we present in this dissertation address facial expression variations, non-rigidity of face and illumination changes as follows: (1) Closed-loop Construction of Super-resolved 3D Facial Texture in Video. A closed-loop system for incremental super-resolution of video and its use for face recognition. The system uses a generic 3D model of the face and compensates for changing illumination and 3D pose in video. (2) Super-resolve LR Facial Images by Treating Face Images Non-uniformly. A super-resolution system that explicitly accounts for facial expressions by treating the face as the composition of local face entities (eyes, nose, mouth, eyebrows and rest of the face) and performing appropriate distortions to the face. (3) Register LR Facial Images Using Global Parametric Model and Free Form Deformation. We propose a new method for enhancing the resolution of low-resolution (LR) facial image by handling the facial image in a non-rigid way: firstly a global model is employed to track the faces through the video sequence; then a B-spline based Resolution Aware Incremental Free Form Deformation (RAIFFD) model is used to recover a dense local non-rigid flow field. (4) Evolutionary Feature Synthesis for Facial Expression Recognition. A genetically-inspired learning method for facial expression recognition. Unlike current research on facial expression recognition that generally selects visually meaningful feature by hands, our learning method can discover the features automatically in a genetic programming-based approach.