ppxscal/embedding_network huggingface dataset:
Forensic Analysis of Document Fragment Based on SVM
Authors: Binglong Li, Qingxian Wang, Junyong Luo
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

The ability to automatically classify document fragments based on their contents is important in digital forensics. This paper proposes an Enhanced String Kernel (ESK) to classify file header fragments with Support Vector Machine (SVM). ESK can extract a byte sequence feature map about document fragment. The map consists of byte-level patterns of document fragments, and captures the characteristic of document fragments. An extended suffix array (ESA) data structure is presented to efficiently store and manipulate the feature map. We can compute the ESK by using the feature map. This method can efficiently categorize a variety of different systems and application file header fragment types. Experiments have provided good classification performance results about file header fragments.
BORGS: A System That Supports Synchronized Surfing
Authors: Ko-Kang Chu, Ming-Chaun Li, Rita Kuo, Yen-Teh Hsia
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

The Broadcast Over Remote Guide System (BORGS) is a web based system that supports teachers to synchronously broadcast the global web pages and other electronic files to students.
An Attack Simulator for Systematically Testing Program-based Security Mechanisms
Authors: Ben Breech, Mike Tegtmeyer, Lori Pollock
Venue: Proceedings of the 17th International Symposium on Software Reliability Engineering (2006)

The use of insecure programming practices has led to a large number of vulnerable programs that can be exploited for malicious purposes. These vulnerabilities are often difficult to find during traditional software testing. In response to these difficulties, various program-based security mechanisms have been proposed to help protect potentially vulnerable programs. Testing these security mechanisms, however, also can be difficult and is currently rather adhoc. In this paper, we describe the design, implementation, and evaluation of an attack simulator that enables the systematic and semi-automatic testing and evaluation of the effectiveness of current and future security mechanisms by automatically providing numerous contexts for testing the reliability of the mechanisms. Capable of automatically creating attacks on running programs by dynamically adding code (but not modifying existing code), the attack simulator can run in different modes and simulate attacks at various program points systematically. Through a case study, we demonstrate how our tool can be used to test two wellknown security mechanisms for stack smashing attacks in several different testing modes.
OCEAN: 2 1/2D Interactive Visual Data Mining of Text Documents
Authors: Christian Jacquemin, Helka Folch, Sylvaine Nugier
Venue: Proceedings of the conference on Information Visualization (2006)

OCEAN is a tool for a posteriori visual data mining that uses the output of a text miner to help users better explore a document space. Clustered documents are transformed into a hierarchical 3D representation analog to Reconfigurable Disk Trees. An intermediary document representation allows for interface customization and offers a generic approach to 3D structuring of text miner outputs. An interactive exploration is offered that avoids tree manipulation and provides local 2 1/2D view of the disks. A user evaluation is reported that outlines the benefit of controlled document hierarchy traversal and 2 1/2D document layout.
Image Restoration by Partial Differential Equations
Authors: MaouniI Messaoud, F. Z. Nouri
Venue: Proceedings of the conference on Geometric Modeling and Imaging: New Trends (2006)

In this paper, we propose a technique that has been recently introduced for a research in contors. This has been applied to di¤erent physical problems to detect noises in images and signals. For this pur- pose, our technique is based on the snake.s (Serpent) method. Here, we present a mathematical analysis for the method and some numerical experiments.
Preventing Spam in Publish/Subscribe
Authors: Sasu Tarkoma
Venue: Proceedings of the 26th IEEE International ConferenceWorkshops on Distributed Computing Systems (2006)

Publish/subscribe protocols are becoming popular on the Internet with the advent of RSS-feeds and Session Initiation Protocol (SIP) events. Since publish/subscribe is by nature many-to-many form of communication, it is vital to prevent spam and bogus messages. This problem has not yet been fully addressed. In this paper, we investigate the spam problem in distributed content-based publish/ subscribe overlay networks and outline several solutions inspired by current email spam prevention techniques. We analyze filter-based spam in distributed pub/sub systems and focus on the detection and mitigation of bogus publishers and brokers.
A bayesian framework for statistical signal processing and knowledge discovery in proteomic engineering
Authors: Marco F. Ramoni, Isaac S. Kohane
Venue:  (2005)

Proteomics has been revolutionized in the last couple of years through integration of new mass spectrometry technologies such as Surface-Enhanced Laser Desorption/Ionization (SELDI) mass spectrometry. As data is generated in an increasingly rapid and automated manner, novel and application-specific computational methods will be needed to deal with all of this information. This work seeks to develop a Bayesian framework in mass-based proteomics for protein identification. Using the Bayesian framework in a statistical signal processing manner, mass spectrometry data is filtered and analyzed in order to estimate protein identity. This is done by a multi-stage process which compares probabilistic networks generated from mass spectrometry-based data with a mass-based network of protein interactions. In addition, such models can provide insight on features of existing models by identifying relevant proteins. This work finds that the search space of potential proteins can be reduced such that simple antibody-based tests can be used to validate protein identity. This is done with real proteins as a proof of concept. Regarding protein interaction networks, the largest human protein interaction meta-database was created as part of this project, containing over 162,000 interactions. A further contribution is the implementation of the massome network database of mass-based interactions---which is used in the protein identification process. This network is explored in terms potential usefulness for protein identification. The framework provides an approach to a number of core issues in proteomics. Besides providing these tools, it yields a novel way to approach statistical signal processing problems in this domain in a way that can be adapted as proteomics-based technologies mature. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
MedEdit: a computer assisted image processing and navigation system for orthopedic trauma surgery
Authors: Krisztián Ollé, Balázs Erdöhelyi, Attila Kuba, Csongor Halmai, Endre Varga
Venue: Acta Cybernetica (2006)

The surgery of fractured bones is often a very complex problem. That is the reason why it would be beneficial to create a geometric and mechanic model of the bones before surgical intervention. The model geometry is based on the CT images of the patient and the known physical properties of the bone. A computerised system is presented here, called MedEdit, which helps a surgeon plan an operation. The system includes a Finite Element Analysis (FEA) program to measure the stress effects of the possible surgical solutions. Following the simulation and analysis of the behaviour of the modelled bone, surgeons can find the best surgical solution for the patient.
An Architecture for Dynamical News Providers
Authors: Emanuela Falcinelli, Stefano Marcugini, Alfredo Milani
Venue: Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology (2006)

In this work we introduce an adaptive architecture for supporting news information services in a dynamical web environment. In the news provider problem, a system continuously generates service instances (e.g.the news of a online newspaper) which should meet the requirements of a market of readers/agents which are supposed unknown. The only way for the system to know the evaluation of a service instance, i.e. a newspaper instance, is the feedback obtained after delivering it to the reader. In a dynamical environment the domain of the service offered is changing and the readers/agents are changing their preferences over the time. The proposed algorithm for newpapers production employs typical genetic operators in order to optimize the product delivered and to adapt it to the environment feedback and domain evolution. Experiments shows the capability of dynamical adaptation of the algorithm..
An ego-centric citation analysis of the works of Michael O. Rabin based on multiple citation indexes
Authors: Judit Bar-Ilan
Venue: Information Processing and Management: an International Journal (2006)

The primary goal of this study was to carry out an ego-centric citation and reference analysis of the works of the mathematician and computer scientist, Michael O. Rabin. Until recently only a single citation database was available for such research-the ISI Citation Indexes. In this study we utilized and compared three major sources that provide citation data: the Web of Science, Google Scholar and Citeseer. Most cited works, citation identity, citation image makers and coauthors were identified. The citation image makers acquired through these sources differ considerably. Advantages and shortcomings of each of the tools are discussed in the context of computer science. A major issue in computer science is multiple manifestations of a work, i.e., its publication in several venues (technical reports, proceedings, journals, collections). The implications of multiple manifestations for citation analysis are discussed.
Hidden Conditional Random Fields for Gesture Recognition
Authors: Sy Bor Wang, Ariadna Quattoni, Louis-Philippe Morency, David Demirdjian
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (2006)

We introduce a discriminative hidden-state approach for the recognition of human gestures. Gesture sequences often have a complex underlying structure, and models that can incorporate hidden structures have proven to be advantageous for recognition tasks. Most existing approaches to gesture recognition with hidden states employ a Hidden Markov Model or suitable variant (e.g., a factored or coupled state model) to model gesture streams; a significant limitation of these models is the requirement of conditional independence of observations. In addition, hidden states in a generative model are selected to maximize the likelihood of generating all the examples of a given gesture class, which is not necessarily optimal for discriminating the gesture class against other gestures. Previous discriminative approaches to gesture sequence recognition have shown promising results, but have not incorporated hidden states nor addressed the problem of predicting the label of an entire sequence. In this paper, we derive a discriminative sequence model with a hidden state structure, and demonstrate its utility both in a detection and in a multi-way classification formulation. We evaluate our method on the task of recognizing human arm and head gestures, and compare the performance of our method to both generative hidden state and discriminative fully-observable models.
A speech enhancement system based on data clustering and cumulative histogram equalization
Authors: Tran Huy Dat, Kazuya Takeda, Fumitada Itakura
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

We present a data driven noise suppression filtering system which combines the data clustering and the cumulative histogram equalization techniques.This method uses the SNRGMM index, which has been developed in our previous works, for clustering a speech data into sub-data with the same index. Furthermore,for each sub-data, the cumulative histogram equalization filtering is learned on each the subband log-spectral magnitude domain. The case, when a noisy speech data is not available, is also consdirered in this work. For that case the SNRGMM can be used for the very quick and flexible simulation of a noisy speech data and without any loss of quality in the final system. The experimental evaluation on the AURORA2 Japansese version shows the improvement of the proposed system in both SNR and ASR performances.
Infrastructure for Language Service Composition
Authors: Yohei Murakami, Toru Ishida, Takao Nakaguchi
Venue: Proceedings of the Second International Conference on Semantics, Knowledge, and Grid (2006)

Although English has become the standard language in various areas, most people do not use it in local activities. To increase the mutual understanding of different cultures with different languages, it is essential to build a language infrastructure on top of the Internet that improves the accessibility and usability of existing online language services so that users can create new cross-language services for their communities. To realize this infrastructure, this paper proposes the language grid. The language grid consists of the "horizontal language grid," which connects the standard languages of nations, and "vertical language grid," which combines the language services generated by communities. This approach can facilitate intercultural collaboration through the Internet, such as international online collaborative learning.
Fractal Algorithm for Finding Global Optimal Solution
Authors: Ju-long Song, Fu-cai Qian
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

For solving global optimization problems, a new algorithm, which is called Fractal Algorithm, is presented. Feasible region is partitioned by fractal combining with golden section. Bad region is deleted gradually and finally optimal solution is remained. The full advantage of the local fine structure of fractal and the quick convergence of golden section method were taken. Hence it is high efficient and high speedy. The algorithm has following character: strong adaptability, adapting to a class of complex function. It needs only that the object function has one order derivative. The minimum can be found at any precision at which a computer can work. On the other hand, this method needs so little memory that it almost can be implemented on any personal computer and its efficiency is not almost influenced. The proof of convergence of the algorithm is given. The illustrations show the algorithm is effective.
Type-safe modular hash-consing
Authors: Jean-Christophe Filliâtre, Sylvain Conchon
Venue: Proceedings of the 2006 workshop on ML (2006)

Hash-consing is a technique to share values that are structurally equal. Beyond the obvious advantage of saving memory blocks, hash-consing may also be used to speed up fundamental operations and data structures by several orders of magnitude when sharing is maximal. This paper introduces an \ocaml\ hash-consing library that encapsulates hash-consed terms in an abstract datatype, thus safely ensuring maximal sharing. This library is also parameterized by an equality that allows the user to identify terms according to an arbitrary equivalence relation.
Live, Runtime Phase Monitoring and Prediction on Real Systems with Application to Dynamic Power Management
Authors: Canturk Isci, Gilberto Contreras, Margaret Martonosi
Venue: Proceedings of the 39th Annual IEEE/ACM International Symposium on Microarchitecture (2006)

Computer architecture has experienced a major paradigm shift from focusing only on raw performance to considering power-performance efficiency as the defining factor of the emerging systems. Along with this shift has come increased interest in workload characterization. This interest fuels two closely related areas of research. First, various studies explore the properties of workload variations and develop methods to identify and track different execution behavior, commonly referred to as "phase analysis". Second, a large complementary set of research studies dynamic, on-the-fly system management techniques that can adaptively respond to these differences in application behavior. Both of these lines of work have produced very interesting and widely useful results. Thus far, however, there exists only a weak link between these conceptually related areas, especially for real-system studies. Our work aims to strengthen this link by demonstrating a real-system implementation of a runtime phase predictor that works cooperatively with on-the-fly dynamic management. We describe a fully-functional deployed system that performs accurate phase predictions on running applications. The key insight of our approach is to draw from prior branch predictor designs to create a phase history table that guides predictions. To demonstrate the value of our approach, we implement a prototype system that uses it to guide dynamic voltage and frequency scaling. Our runtime phase prediction methodology achieves above 90% prediction accuracies for many of the experimented benchmarks. For highly variable applications, our approach can reduce mispredictions by more than 6X over commonly-used statistical approaches. Dynamic frequency and voltage scaling, when guided by our runtime phase predictor, achieves energy-delay product improvements as high as 34% for benchmarks with non-negligible variability, on average 7% better than previous methods and 18% better than a baseline unmanaged system.
Formalizing typicality of objects and context-sensitivity in ontologies
Authors: Ching-man Au Yeung, Ho-fung Leung
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

In multiagent systems ontologies are essential because they facilitate tasks like communications and reasoning. In this paper, inspired by studies in cognitive psychology, we present a theoretical framework of ontologies that model concepts and properties in a way that typicality of objects can be reflected, and in which context plays a major role in determining the interpretation of the concepts. Typicality is a very common phenomenon observed in different cognitive tasks, while context has been proved to have significant influences on reasoning and categorization. This framework brings together these issues and gives a formal representation of context-sensitive ontologies.
Engaging the Public through Mass-Scale Multimedia Networks
Authors: Milena Radenkovic, Tom Lodge
Venue: IEEE MultiMedia (2006)

The authors investigate the technological challenges and social implications of multimedia applications that will be driven by national campaigns. These applications offer the opportunity to achieve a level of public participation and engagement that's more massive than we as readers might initially imagine.
Grid Portal System Based on GPIR
Authors: Fang Juan, Geoffrey Fox, Marlon Pierce
Venue: Proceedings of the Second International Conference on Semantics, Knowledge, and Grid (2006)

Grid portal is the bridge between Grid and user. In this paper a Grid portal system is set up based on GPIR of GridPort. The Grid portal system provides an efficient means to user for utilizing grid resources, and provides advantaged condition for achieving effective information of database. The user can customize the application by portlet framework. In this paper we also review multiple choices for portal technology and explain why we choose GPIR.
Optimal computing budget allocation under correlated sampling
Authors: Michael C. Fu, Jian-Qiang Hu, Chun-Hung Chen, Xiaoping Xiong
Venue: Proceedings of the 36th conference on Winter simulation (2004)

We consider the optimal computing budget allocation (OCBA) problem where the simulated designs are correlated. The exact optimal allocation is presented for two designs, and an approximation proposed for more than two designs. Numerical experiments for several examples compare the approximation with some other allocation procedures. Results on convergence rates and the non-Gaussian setting are also discussed.
Analysis of Current Steganography Tools: Classifications & Features
Authors: Ming Chen, Ru Zhang, Xinxin Niu, Yixian Yang
Venue: Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia (2006)

The technology of information hiding has developed rapidly in recent years. The number of steganography software has reached more than 200 at present. This paper focuses on the steganography tools' algorithms. Based on the analyses of these algorithms, we partition these tools into five categories: (1). Spatial domain based steganography tools; (2). Transform domain based steganography tools; (3). Document based steganography tools; (4) File structure based steganography tools; (5). Other categories, e.g. video compress encoding and spread spectrum technique based. Moreover, we give an in-depth analysis of the feature of each category.
The Walker's Perspective: strategies for conveying landscape perception using audiovisual media.
Authors: Christophe Girot, Fred Truniger
Venue: Proceedings of the conference on Information Visualization (2006)

This paper presents a method and three case studies for the integration of video into the practice of landscape architecture. As a design practice, landscape architecture is heavily dependent on visualisations. Traditionally maps, perspectives and photographic stills were used, but today these techniques are clearly no longer up to the task: they convey little information about the way we perceive landscape. Landscape perception has changed dramatically since the introduction of the moving image and highspeed travel. Contemporary visualisations of landscapes must therefore include these dynamic parameters in order to meet the profession's needs. We propose video as a new tool for visualizing the perception of, and communicating about, landscape. In this paper we first introduce an analytical grid for the evaluation of video as a means of visualising landscape perception, from the vantage point of the slowest traveller, the pedestrian. Using three case studies, we then describe how video may be used to understand the specific situation of a walking perceiver. The findings are important both for practitioners and researchers in landscape architecture and for researchers of all disciplines interested in human perception.